Instruction Monitoring for Dynamic Cloud Workload Reallocation Based on Ransomware Attacks

Abstract

This embodiment relates to identifying a ransomware attack. One embodiment relates to a method that includes configuring an operating system to collect metrics associated with hardware components. Messages are receivable from a user space library to verify instructions detected in a cache, and the instructions are associated with the hardware components. The metrics can be compared to threshold metrics. The metrics can be associated with the hardware components. The likelihood of a ransomware attack can be determined based at least in part on the comparison. A message including the determination of the likelihood of ransomware can be sent to the user space library.

Description

Technical Field

[0001] Cross - Reference to Related Applications This application claims the benefit of priority of U.S. Non - Provisional Patent Application No. 17 / 743,945, filed on May 13, 2022, the content of which is hereby incorporated by reference in its entirety for all purposes.

[0002] Field This application relates to the field of network security, and more particularly to instruction monitoring for dynamic cloud workload reallocation based on ransomware attacks.

Background Art

[0003] Background A cloud computing environment includes a combination of a cloud computing infrastructure layer, a cloud platform layer, and an application layer. Each of these layers further includes sub - elements that enable the cloud computing system to deliver services to its customers. Each of these cloud computing layers and elements can provide an opportunity for a bad actor to break security means and harm the functionality of the cloud computing environment.

Summary of the Invention

Means for Solving the Problems

[0004] Summary This embodiment relates to dynamic cloud workload reallocation based on active ransomware attacks. A first exemplary embodiment provides a method executed by a computer for dynamic cloud workload reallocation. The method can include configuring an operating system to collect metrics related to hardware components.

[0005] The method executed by a computer may further include receiving a message from a user space library to verify an instruction detected in a cache, the instruction being associated with a hardware component.

[0006] The method executed by a computer may further include comparing a metric to a threshold metric, the metric being associated with a hardware component based at least in part on the message.

[0007] The method executed by a computer may further include determining a likelihood of a ransomware attack based at least in part on the comparison.

[0008] The method executed by a computer may further include sending a message including the determination of the likelihood of ransomware to a user space library.

[0009] A second embodiment relates to a cloud infrastructure node. The cloud infrastructure node may include a processor and a non-transitory computer-readable medium. The non-transitory computer-readable medium may include instructions that, when executed by the processor, cause the processor to configure an operating system to collect a metric associated with a hardware component.

[0010] The instructions may further cause the processor to receive a message from a user space library to verify an instruction detected in a cache, the instruction being associated with a hardware component.

[0011] The instructions may further cause the processor to compare a metric to a threshold metric, the metric being associated with a hardware component based at least in part on the message.

[0012] The instructions may further cause the processor to determine a likelihood of a ransomware attack based at least in part on the comparison.

[0013] The command may further cause the processor to send a message including a determination of the likelihood of ransomware to a user space library.

[0014] A third embodiment relates to a non-transitory computer-readable medium. The non-transitory computer-readable medium may include a sequence of instructions stored thereon, which when executed by a processor, cause the processor to execute a process. The process may include configuring an operating system to collect metrics related to hardware components.

[0015] The process may further include receiving a message from a user space library to verify an instruction detected in a cache, the instruction being associated with a hardware component.

[0016] The process may further include comparing a metric to a threshold metric, the metric being associated with a hardware component based at least in part on the message.

[0017] The process may further include determining the likelihood of a ransomware attack based at least in part on the comparison.

[0018] The process may further include sending a message including a determination of the likelihood of ransomware to a user space library.

Brief Description of the Drawings

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DETAILED DESCRIPTION OF THE INVENTION

[0020] Detailed Description In the following description, various embodiments are described. For the purpose of explanation, specific configurations and details are set forth in order to achieve a thorough understanding of the embodiments. However, it will be apparent to those skilled in the art that the embodiments can be practiced without those specific details. Additionally, well-known features may be omitted or simplified in order not to obscure the described embodiments.

[0021] Many cloud computing systems are vulnerable to active security exploitation, such as by ransomware attacks. Ransomware attacks may involve malicious memory / disk encryption using a private key. Additionally, ransomware attackers may encrypt client data and hold the data for ransom. Failure to provide the ransom may result in, among other things, deletion of the client data or inappropriate dissemination of the client data.

[0022] Ransomware attacks have evolved to the point where many attacks can evade standard antivirus protection. Additionally, ransomware may be designed to target specific targets, such as the hardware components of a cloud computing system. Two such ransomware attacks are Full Disk Encryption and Broken Object Level Authorization (BOLA). Laptops and servers are particularly vulnerable to these hardware-level ransomware attacks. When a laptop or server connected to a cloud environment is successfully attacked by ransomware, the laptop or server becomes a gateway for malicious behavior to cause further damage to the cloud system.

[0023] The embodiments described herein address the above-mentioned problems by countering hardware-level ransomware methods using cloud computing technology. In particular, the embodiments described herein can counter ransomware by connecting a high-level microprocessor instruction set category to cloud computing technology. In other words, connect cloud technology at the hardware level to the instruction set. Additionally, the embodiments herein are more beneficial than prior methods of countering ransomware by connecting repackaging and migration services to address the security threats posed by ransomware.

[0024] When embodiments herein execute cancellation-exclusive microprocessor-level instructions, a monitoring solution can always be provided in the lower processing space. Embodiments can further provide a set of intermediate layers of services and a library of solutions for utility functions. Furthermore, embodiments can provide a glue logic function that connects and / or converts memory map-to-monitoring artifacts in key performance indicators (KPIs) for the input of cloud-native schedulers. Embodiments can further permit changes to the algorithms used in the migration of workloads from one set of cloud computing instances to another. Additionally, embodiments can enable the freezing of victim compute instances. The embodiments described herein provide a more beneficial ransomware countermeasure methodology than before. For example, embodiments provide control across areas in cloud computing systems implementing the embodiments. Additionally, ransomware can be removed at the microprocessor level.

[0025] FIG. 1 is a block diagram showing an exemplary system 100 for the identification and mitigation of ransomware attacks in a cloud computing infrastructure 102. The system 100 can include an instruction detector 104 for detecting and monitoring the encryption / decryption of assembly instructions at the kernel level. The instruction detector 104 can detect and monitor, for example, encryption instructions when an instruction is read from memory into the instruction cache or when an assembly-level instruction is executed. The instruction detector 104 can include lower memory monitoring resources for detecting encryption / decryption instructions. The instruction detector 102 can read memory lines to identify any encryption instructions provided in the memory. Encryption / decryption instructions can be aggregated to determine whether a threshold number of changes have occurred in the memory to verify a ransomware attack in the memory.

[0026] System 100 may further include a user space library 106 in the user space in a cloud infrastructure that can initiate monitoring of lower-level memory. The user space library 106 can be a collection of functions that enable communication between the operating system and applications running on the operating system. In some embodiments, the user space library 106 can be multiplexed across libraries in the platform layer of the cloud environment. The user space library 106 can detect and monitor encryption / decryption instructions loaded into the instruction cache. The instruction cache stores instructions for which the lower-level hardware proceeds with execution. In particular, the user space library 106 can monitor the instructions loaded into the instruction cache and determine whether there are changes to the instructions. By way of example, the instruction detector 104 can detect and monitor encryption / decryption routines at the kernel level. On the other hand, the user space library 106 can detect and monitor encryption / decryption routines at the user space level.

[0027] System 100 may further include a memory translator 108. The memory translator 108 can interact with the memory map to provide cache mapping and unmapping functions to the application. Each time an application is introduced to the cloud, the application provides a set of instructions for interacting with the hardware to a cloud computing instance. The memory translator 108 can instruct the application regarding, for example, placement strategies and replacement strategies, as well as read and write policies for the instructions provided by the application.

[0028] System 100 can interact with an application 110. The application 110 may potentially include ransomware that performs malicious encryption of data within the cloud computing infrastructure.

[0029] The embodiments described herein provide various functions. One function is timer-based polling of the instruction cache. As described above, the user space library 106 can detect and monitor encryption / decryption instructions when they are sent to and from the instruction cache. In some embodiments, the system 100 monitors the instruction cache over a configurable time interval that can be periodic or aperiodic. The system 100 can be configured to decrease or increase the time interval. Thus, if the system 100 determines to increase the length of the time interval for monitoring the instruction cache, the time interval can be increased. On the other hand, the user space library 106 can also decrease the length of the time interval.

[0030] Another feature of the embodiments described herein is the dynamic random access memory (DRAM) scan detection threshold for optimization of the detection methodology described herein. The system 100 can scan the DRAM for encryption / decryption verification of assembly instructions. The scan can provide information related to determining when an instruction was validly encrypted or maliciously encrypted. In particular, the scan can further provide information related to determining the weights of the scoring algorithms described below and whether the cloud computing system is operating normally or abnormally.

[0031] Yet another feature of the embodiments described herein is the ability to register and connect a host instance to a repaver. The repaver can be a cloud-native repaver, particularly a microservice built for and periodically updated for a cloud computing environment. This embodiment can further analyze system parameters for determining at what level repaving was performed. For example, repaving can be performed at different system levels, such as the host level, container level, point of delivery (POD) level.

[0032] Referring to FIG. 2, a repackaging system 200 is shown for migrating computing resources (e.g., or workloads) and requesting to execute computing tasks from an affected computing instance. Repackaging may include restoring the state of the instance to its state prior to the security violation. For example, the repairer 202 can restore the state of the workload if ransomware has been incorporated into the workload. The repairer 202 may include a host-level repackaging unit 204 for repackaging resources at the host level and a container-level repackaging unit 206 for repackaging resources at the container level. The host-level repackaging unit 204 may include a workload migration unit 208 for repackaging the workload from the affected computing instance at the host level. Further, the host-level repackaging unit 204 may include a reboot host image unit 210 for repackaging the host image for the affected computing instance. The container-level repackaging unit 206 may include a workload migration and pod migration module 212 for repackaging the workload from the affected computing instance.

[0033] Referring to FIG. 3, there is shown a signaling diagram 300 for registration / deregistration of encrypted assembly instruction monitoring. As shown, a user space library 302, an instruction detector 304, a kernel image 306, and a logging service 308 can interact with each other. Although the operations of processes 300, 500, 600, and 700 are described as being executed by a general-purpose computer, it should be understood that any suitable device (e.g., a user device, a server device) can be used to execute one or more of the operations of those processes. Processes 300, 500, 600, and 700 (described below) are each shown in a logical flow diagram, and each of their operations represents a series of operations that can be implemented in hardware, computer instructions, or a combination thereof. In the context of computer instructions, an operation represents computer-executable instructions that, when stored on one or more computer-readable storage media and executed by one or more processors, perform the described operations. Generally, computer-executable instructions include routines, programs, objects, components, data structures, etc. that execute a function or implement a data type. The order in which the operations are described is not intended to be construed as a limitation, and any number of the described operations can be combined in any order and / or in parallel to implement the process.

[0034] At 310, the user space library 302 can insert kernel-level detection instructions into the instruction detector 304. The user space library 302 can include, for example, a user space library, and the user space library 302 can retrieve detection instructions regarding how to detect encryption / decryption from the library and insert the detection instructions into the instruction detector 304. The detection instructions can include a kernel driver, and the kernel driver can have the ability to directly access the kernel application programming interface (API) and memory. The user space library 302 can be triggered to retrieve and insert the detection instructions based on its interaction with an application. The application can be, for example, an application that may be infected by ransomware.

[0035] At 312, the instruction detector 304 can insert the detected instruction into the kernel image. In some embodiments, the instruction detector 304 can insert the detected instruction into a kernel tree, which can be a source directory or repository that includes the kernel source. Steps 310 and 312 may result in the insertion of the detected instruction at the core processor level.

[0036] At 314, the user space library 302 can monitor instructions, such as assembly-level instructions, that are loaded into or retrieved from a cache, such as an instruction cache. The instructions can be assembly-level instructions that are sent to a cache associated with the hardware based on the application. The user space library 314 can further monitor assembly instructions regarding memory map changes. Memory mapping can be the process by which the contents of main memory are brought to a cache, such as an instruction cache. Memory mapping can also include the process by which a block of main memory is mapped to the cache in the case of a cache miss. Changes in memory mapping can indicate changing the map because legitimate instructions are retrieved from memory and because instructions that can lead to malicious encryption are retrieved.

[0037] If the user space library 302 detects a change to the assembly instruction mapping at the cache level, at 316, the instruction detector can be requested to check the mapped assembly instructions. At 318, the instruction detector 304 can send a message to construct the kernel image 306 for metric collection. The kernel image can be in the binary form of the operating system. For example, the instruction detector 304 can configure a central processing unit (CPU) and a graphics processing unit (GPU) for metric collection at the hardware level.

[0038] At 320, when one or more of the collected metrics exceed a threshold, the instruction detector 304 can register a callback function that provides a callback to the user space library 302. A callback is executable code passed as an argument to another piece of code. The callback can further provide a message to a higher-level function (e.g., the user space library) to perform some post-processing on the collected metrics.

[0039] At 322, the kernel image 306 can return hardware metrics to the instruction detector 304. The hardware metrics can be retrieved from multiple hardware-related sources. The hardware metrics can be continuously received by the instruction detector 304 from the kernel image 306. The instructor detector 304 can continuously compare the hardware metrics to one or more thresholds. The thresholds can be related to key performance indicators (KPIs). The instruction detector 304 can perform the comparison to identify instructions in the cache related to ransomware.

[0040] At 324, the instruction detector 304 can send a notification to the user space library 302 that an instruction may be problematic. For example, an assembly instruction may be related to a malicious encryption instruction. The notification can be included in the above-described callback. In response to receiving the notification, the user space library 302 can initiate post-processing to record the incident. For example, the user space library 302 can start updating key performance indicators (KPIs), updating the footprint of the hardware device, identifying which memory maps are updated, and identifying any generated artifacts. The user space library 302 can further timestamp the collected data and store it in a bucket.

[0041] At 326, the instruction detector 304 can send a notification to the logging service 308 that the metric has exceeded a threshold. The instruction detector 304 can further indicate that the user space library 302 has been triggered to perform post - processing of the collected data related to a potential ransomware incident at the hardware level. In other cases, the instruction detector 304 can send a notification of failure. This implies that the user space library 302 sent a request to check for specific assembly instructions, and the instruction detector started collecting metrics but the threshold was not exceeded.

[0042] At 328, the user space library 302 can send a notification to the instruction detector 304 regarding whether the memory has been wiped. As illustrated in FIG. 2, the system 100 permits repackaging of an instance that has been compromised by ransomware. Repackaging can include returning the instance from the compromised state to its previous state. For example, the repairer 200 can reload the image of the instance, and the reloaded image is in the state before the ransomware attack. The status can be that the instance has not been repackaged, is being repackaged, or has been repackaged.

[0043] As described above, cache instructions can be identified at the micro - processor level and can be the result of ransomware. In some embodiments, assembly instructions that may be related to ransomware are identified at the cache level. The identified instructions can be compared with a certain KPI to determine whether the instruction is related to ransomware. A mathematical formula using a weighted average can be implemented to dynamically distinguish between legitimate encryption instructions and malicious encryption instructions. Each instruction can be weighted regarding the likelihood that the instruction is related to a ransomware attack. The following exemplary table provides an explanation of each instruction and the weight for each instruction.

[0044] [Table 1]

[0045] Each of the identified instructions pertains to a bucket of encryption / decryption instruction types. An explanation of the instruction class is provided, and a weight for the instruction type is also provided. The weight can be an indication that, if the instruction class is identified within the cache, the instruction may be related to ransomware. The above table is for illustrative purposes only, and it should be understood that the instruction classes, explanations, and weights can be instructions specialized for any situation. For example, a processor can have one architecture and use one set of instruction classes, while another processor with a different architecture can use a different set of instruction classes.

[0046] In some embodiments, the user space library may implement a function to apply the following formula to identify an instruction as being related to ransomware. Total weight = sum of (frequency of each instruction class * weight of each instruction class) (e.g., total weight = [((frequency of the first instruction class)(weight of the first instruction class)) + ((frequency of the second instruction class)(weight of the second instruction class))] As described above, the cache can be monitored over a configurable time window. During the time window, each instruction type can be logged. The user space library can then aggregate instructions based on the instruction type and frequency of a particular instruction. The user space library can multiply the frequency of the instructions based on the instruction type to calculate the total weight. The total weight can be compared to a KPI to determine whether the presence of the instructions indicates a ransomware attack.

[0047] As described above, the detection instructions related to encryption / decryption in the memory set can be aggregated to determine whether a ransomware attack exists. In response to identifying that there may be a ransomware attack, a trigger can be created to initiate a reinstall to migrate resources from the victim's computing instance.

[0048] In some embodiments, the user space library may create a table for hardware that is a potential victim of a ransomware attack. The user space library can add hardware-related metadata to the table. This metadata can be various values composed from the hardware to the kernel image. The metadata is structured in a known pattern and compared to known values such as ground truth values. The user space library can compare the metadata to a known while across the table. For example, a process can be configured as a "while" loop, and the middle part continues to perform the comparison until the metadata is no longer compared to the known value.

[0049] A memory set containing the identified instruction instances in memory lines can be obtained. The memory set can be processed using a ransomware detection structure to detect ransomware-related instructions and to determine whether the instructions contain temporary encryption or persistent encryption that may include a ransomware attack. Each memory line can be accessed according to a specific order. For example, the content of the first line can be read and stored using the preceding and subsequent lines. After reading / writing to a chunk of lines, the preceding line and another subsequent line can be read in that order.

[0050] In response to not detecting an instruction related to encryption, the result may indicate that no encryption was detected. Alternatively, if an instruction to encrypt data is detected, the change in the memory content for each chunk of the memory line can be calculated. The result can be compared to a threshold to determine whether the instruction exceeds the threshold amount. Further, the result can be processed to determine whether the instruction includes a false positive. In response to the result being verified and indicating that a ransomware attack may be occurring, a trigger for cloud repackaging of the victim computing instance can be created.

[0051] In some cases, the instructions to encrypt and decrypt data can be analyzed to verify the results and remove false detection instances that may indicate a detected ransomware attack via an encryption bitmap. As described above, the user space library can observe the cache over a configurable time window. For example, the user space library can observe that data is written to and read from the cache over a 3 - second time window. The user space library can further retrieve historical data from the cache over a similar time window. The historical data, assuming no malicious encryption was observed at that time, functions as a benchmark for the current data. The user space library can compare the two data sets and determine whether the difference (e.g., delta) between the two data sets implies that malicious encryption has occurred.

[0052] In some embodiments, the encryption bitmap can be generated to include a bitmap of the instructions identified for each memory line. A mathematical exclusive - or (XOR) operation can be performed on the bitmaps for adjacent memory lines. A delta value can be derived as a result of the XOR operation for each set of adjacent bitmaps, and the sum of the delta values can be derived by aggregating the delta values. If the sum of the aggregated delta values exceeds a threshold, encryption / decryption can be identified. Alternatively, the system can continue to accumulate the instructions identified in the memory set. In some cases, data analysis functions such as min, max, standard, deviation, etc. can be used to reach possible threshold variants.

[0053] Referring to FIG. 4, an exemplary instruction cache system 400 according to one or more embodiments is shown. As illustrated, memory 402 can provide instructions to instruction cache 404 and data to data cache 406. Processor core 408 can receive instructions from instruction cache 404 and data for use during the execution of instructions from data cache 406. Processor core 408 can return modified or unmodified data to data cache 406, and data cache 406 can return data to memory 402. When processor core 408 is ready to execute the next instruction, it fetches the next instruction from instruction cache 404. When a new instruction is requested, the new instruction can be written from memory 402 to instruction cache 404. This is a continuous process, and thus the instructions currently in instruction cache 404 may vary based on the time at which the instruction cache is observed. As described above, each of the instructions in instruction cache 404 at any given time can belong to respective instruction classes, and weights can be assigned based on the classes. Further, each instruction may be an instruction for malicious encryption.

[0054] As described above, the instruction cache 404 can be observed over a configurable window. This includes instructions read from the memory 402 and written to the instruction cache. This also includes the instructions currently stored in the instruction cache 404 and the instructions read by the processor core 408 for execution. If the state of the instruction cache 404 is a function of time, the embodiments described herein include a configurable time window for observing the instruction cache 404. Thus, the system 100 can configure the time associated with the window for observing the instruction cache. For example, if the window is configured to be X milliseconds (ms), the system 100 can observe the instruction cache over X ms. However, if the system 100 configures the window to be Y ms, the system 100 can observe the instruction cache over Y ms. The system 100 can configure the window based on an optimal window to identify whether a malicious instruction has been received in the instruction cache 404.

[0055] Figure 5 shows a process 500 for identifying a ransomware attack, according to some embodiments. At 502, a computing device may send a detection instruction to an instruction detector. The computing device may include, for example, a node of a cloud infrastructure system. The node may include a user space library that manages communication between an application and a cloud infrastructure device. The computing device may send a detection instruction in response to detecting an interaction between an application and a cloud infrastructure device.

[0056] At 504, the computing device may monitor a cache, such as an instruction cache, to detect changes in the memory mapping. This memory mapping may be the mapping from the instructions written to the instruction cache and the memory from which the instructions are read. The instructions may be assembly-level instructions for the hardware. The computing device can monitor the cache over a configurable window.

[0057] At 506, the computing device can determine whether it has detected any changes to the memory mapping. If no detected changes to the memory mapping are present, process 500 returns to 504, at which point the ongoing device continues to monitor the cache. However, if the computing device has detected a change to the memory mapping, process 500 proceeds to 508.

[0058] At 508, the computing device may send a message to check the instructions. The message can be sent to an instruction detector, and the instructions to be checked can be instructions related to the change in the memory mapping. For example, if the memory mapping initially indicates that the cache is set to fetch instructions from one location in memory and then the mapping is changed to cause the instructions to be fetched from a different location, the computing device can request that those instructions be checked.

[0059] At 510, the computing device may receive a message as to whether there has been a ransomware attack. The message can be received from the instruction detector as a callback. If the message implies a ransomware attack, the computing device can, at 512, repackage the affected instances. However, if the message does not imply a ransomware attack, the computing device does not repackage the instances.

[0060] Figure 6 shows a process 600 for identifying a ransomware attack according to some embodiments. At 602, a computing device may receive a detection instruction. The computing device may be a node of a cloud infrastructure system. The node may further include an instruction detector. The detection instruction may include a kernel driver. At 604, the computing device may send the detection instruction to a kernel image. The kernel image may include an operating system of a cloud computing infrastructure (e.g., a non-Linux-based system). The detection instruction may be used to configure the kernel image for collecting metrics related to the detection of a ransomware attack.

[0061] At 606, the computing device may register a callback function if a threshold is reached. The callback function may be configured to send a message indicating that the threshold has been exceeded to a user space library. The message may further be a message for initiating a post-processing step for the user space library.

[0062] At 608, the computing device can compare the collected metrics with a threshold. The metrics may be collected by the kernel image (or the operating system of a non-Linux-based system). The threshold may be based on configurable KPIs provided to the computing device.

[0063] At 610, the computing device may send a notification to the user space library. The notification may be based on a callback function. The notification may include a message indicating that a ransomware attack has occurred, or the notification may be a message indicating that no ransomware attack has occurred. Before sending the notification, the computing device can determine whether the message of the ransomware attack is a false positive. For example, if the collected metric exceeds one or more thresholds, after analyzing the false positive, the computing device can send a message indicating that a ransomware attack has been detected. However, if the collected metric does not exceed any threshold, the computing device can send a message indicating that no ransomware attack has been detected.

[0064] FIG. 7 is a block diagram of a process for ransomware detection according to at least one embodiment. At 702, the method includes configuring an operating system such that a computing device collects metrics related to hardware components. The computing device can be, for example, a cloud infrastructure node. The metrics can be collected by a kernel image (or an operating system of a non-Linux-based system).

[0065] At 704, the method can include the computing device receiving from a user space library to verify instructions detected in a cache, where the instructions are associated with a hardware component. The cache can include, for example, an instruction cache, and the instructions can include, for example, assembly instructions.

[0066] At 706, the method can include the computing device comparing a metric to a threshold metric, where the metric is associated with a hardware component and the metric is at least partially based on a message. The threshold can be based on a configurable KPI provided to the computing device.

[0067] At 708, the method may include a computing device determining a likelihood of a ransomware attack based at least in part on a comparison. For example, if the collected metrics exceed one or more thresholds, after analyzing for false positives, the computing device can send a message indicating that a ransomware attack has been detected. However, if the collected metrics do not exceed the threshold, the computing device can send a message indicating that no ransomware attack has been detected.

[0068] At 710, the method may include a computing device sending a second message including a determination of the likelihood of ransomware to a user space library.

[0069] As described above, infrastructure as a service (IaaS) is a particular type of cloud computing. IaaS can be configured to provide virtualized computing resources over a public network (e.g., the Internet). In an IaaS model, a cloud computing provider can host infrastructure components (e.g., servers, storage devices, network nodes (e.g., hardware), deployment software, platform virtualization (e.g., hypervisor layer), etc.). In some cases, the IaaS provider can also supply a variety of services to accompany those infrastructure components (exemplary services include billing software, monitoring software, logging software, load balancing software, clustering software, etc.). Thereby, if these services can be policy-driven, an IaaS user may be able to enforce policies to drive load balancing to maintain application availability and performance.

[0070] In some cases, IaaS customers can access resources and services via a wide area network (WAN) such as the Internet and use the cloud provider's services to install the remaining elements of the application stack. For example, a user can log in to an IaaS platform, create virtual machines (VMs), install an operating system (OS) on each VM, deploy middleware such as a database, create storage buckets for workloads and backups, and further install enterprise software on that VM. The customer can then use the provider's services to perform various functions including network traffic balancing, troubleshooting application problems, performance monitoring, and disaster recovery management.

[0071] In most cases, the cloud computing model requires the involvement of a cloud provider. The cloud provider may be a third-party service specialized in providing IaaS (e.g., offer, rental, sale), but this is not essential. An entity may choose to deploy a private cloud that becomes its own provider of infrastructure services.

[0072] In some examples, an IaaS deployment is the process of placing a new application or a new version of an application on a prepared application server, etc. It may also include the process of preparing the server (e.g., installing libraries, daemons, etc.). This is often managed by the cloud provider under the hypervisor layer (e.g., servers, storage, network hardware, and virtualization). Thereby, the customer can be responsible for the deployment of the processing (OS), middleware, and / or application (e.g., in a self-service virtual machine that can be spun up on demand).

[0073] In some cases, IaaS provisioning may refer to obtaining a computer or virtual host for use, and even installing the required libraries or services on it. In many cases, deployment does not include provisioning, and provisioning may need to be done first.

[0074] In some cases, there are two different issues with IaaS provisioning. First, there is the initial issue of pre-configuring an initial set of infrastructure before anything can operate. Second, once everything is pre-configured, there is the issue of evolving the existing infrastructure (e.g., adding new services, changing services, removing services, etc.). In some cases, these two issues can be addressed by enabling the infrastructure configuration to be defined declaratively. In other words, the infrastructure (e.g., which components are needed and how they interact with each other) can be defined by one or more configuration files. Thus, the overall topology of the infrastructure (e.g., which resources depend on which resources and how they cooperate with each other) can be described declaratively. In some cases, once the topology is defined, a workflow can be generated to create and / or manage the different components described in the configuration files.

[0075] In some examples, the infrastructure can have many interconnected elements. For example, there can be one or more virtual private clouds (VPCs), also known as core networks, which are potentially on-demand pools of configurable and / or shared computing resources. In some examples, there can also be one or more incoming / outgoing traffic group rules preconfigured to define how incoming and / or outgoing traffic of the network is set up, and one or more virtual machines (VMs). Other infrastructure elements such as load balancers, databases, etc. can also be preconfigured. As more infrastructure elements are desired and / or added, the infrastructure can evolve gradually.

[0076] In some cases, continuous deployment techniques can be used to enable the deployment of infrastructure code across various virtual computing environments. Additionally, the above techniques can enable infrastructure management within those environments. In some examples, a service team may write code that is desired to be deployed to one or more, but often many, different production environments (e.g., sometimes spanning various different geographical locations across the world). However, in some examples, the infrastructure to which the code is deployed needs to be set up first. In some cases, provisioning may be done manually, provisioning tools may be utilized to preconfigure resources, and / or deployment tools may be utilized to deploy code once the infrastructure is preconfigured.

[0077] FIG. 8 is a block diagram 800 showing an exemplary pattern of an IaaS architecture according to at least one embodiment. A service operator 802 may be communicatively coupled to a secure host tenancy 804, which may include a virtual cloud network (VCN) 806 and a secure host subnet 808. In some examples, the service operator 802 may use one or more client computing devices, which may operate software such as Microsoft Windows Mobile®, and / or a variety of mobile operating systems such as iOS, Windows Phone, Android, BlackBerry 8, Palm OS, and are Internet, email, short message service (SMS), BlackBerry®, or other communication protocol compliant, portable handheld devices (e.g., iPhone®, mobile phone, iPad®, computing tablet, personal digital assistant (PDA)) or wearable devices (e.g., Google® Glass head-mounted display). Alternatively, the client computing device may be, for example, a general-purpose personal computer and / or a laptop computer on which various versions of the Microsoft Windows®, Apple Macintosh®, and / or Linux® operating systems are running. The client computing device may be a workstation computer that runs any of a variety of commercially available UNIX® or UNIX-like operating systems including, but not limited to, various GNU / Linux® operating systems such as Google Chrome OS.Alternatively or additionally, the client computing device may be any other electronic device such as a thin client computer, an Internet-enabled gaming system (e.g., a Microsoft Xbox gaming console with or without a Kinect (registered trademark) gesture input device), and / or a personal messaging device that can communicate via a network accessible to the VCN806 and / or the Internet.

[0078] The VCN806 may include an LPG810 that can be communicatively coupled to an SSH VCN812 via a local peering gateway (LPG) 810 included in a secure shell (SSH) VCN812. The SSH VCN812 may include an SSH subnet 814 and may be communicatively coupled to a control plane VCN816 via an LPG810 included in the control plane VCN816. Also, the SSH VCN812 may be communicatively coupled to a data plane VCN818 via an LPG810. The control plane VCN816 and the data plane VCN818 may be included in a service tenancy 819 that can be owned and / or operated by an IaaS provider.

[0079] The control plane VCN 816 may include a control plane demilitarized zone (DMZ) tier 820 that functions as a border network (e.g., a portion of a corporate network between a corporate intranet and an external network). DMZ-based servers have limited responsibilities and can help maintain a state that includes violations. Additionally, the DMZ tier 820 may include one or more load balancer (LB) subnets 822, a control plane application tier 824 that may include an app subnet 826, and a control plane data tier 828 that may include a database (DB) subnet 830 (e.g., a front-end DB subnet and / or a back-end DB subnet). The LB subnet 822 included in the control plane DMZ tier 820 may be communicatively coupled to the app subnet 826 included in the control plane application tier 824 and to an internet gateway 834 that may be included in the control plane VCN 816. The app subnet 826 may be communicatively coupled to the DB subnet 830 included in the control plane data tier 828, as well as to a service gateway 836 and a network address translation (NAT) gateway 838. The control plane VCN 816 may include a service gateway 836 and a NAT gateway 838.

[0080] The control plane VCN 816 may include a data plane mirror application tier 840 that may include an app subnet 826. The app subnet 826 included in the data plane mirror application tier 840 may include a virtual network interface controller (VNIC) 842 that can run a compute instance 844. The compute instance 844 may communicatively couple the app subnet 826 of the data plane mirror application tier 840 to the app subnet 826 that may be included in a data plane application tier 846.

[0081] The data plane VCN 818 may include a data plane application tier 846, a data plane DMZ tier 848, and a data plane data tier 850. The data plane DMZ tier 848 may include an LB subnet 822 that can be communicatively coupled to the app subnet 826 of the data plane application tier 846 and the internet gateway 834 of the data plane VCN 818. The app subnet 826 may be communicatively coupled to the service gateway 836 of the data plane VCN 818 and the NAT gateway 838 of the data plane VCN 818. The data plane data tier 850 may also include a DB subnet 830 that can be communicatively coupled to the app subnet 826 of the data plane application tier 846.

[0082] The internet gateway 834 of the control plane VCN 816 and the data plane VCN 818 may be communicatively coupled to a metadata management service 852 that can be communicatively coupled to the public internet 854. The public internet 854 may be communicatively coupled to the NAT gateway 838 of the control plane VCN 816 and the data plane VCN 818. The service gateway 836 of the control plane VCN 816 and the data plane VCN 818 may be communicatively coupled to a cloud service 856.

[0083] In some examples, the service gateway 836 of the control plane VCN 816 or the data plane VCN 818 can make an application programming interface (API) call to the cloud service 856 without going through the public internet 854. The API call from the service gateway 836 to the cloud service 856 can be unidirectional, i.e., the service gateway 836 can make an API call to the cloud service 856, and the cloud service 856 can send the requested data to the service gateway 836. However, the cloud service 856 may not initiate an API call to the service gateway 836.

[0084] In some examples, the secure host tenancy 804 can be directly connected to the service tenancy 819, otherwise the service tenancy 819 can be in a separated state. The secure host subnet 808 can communicate with the SSH subnet 814 through the LPG 810, which can enable two-way communication through a separated system otherwise. Connecting the secure host subnet 808 to the SSH subnet 814 can give access to the secure host subnet 808 to other entities within the service tenancy 819.

[0085] The control plane VCN 816 can enable a user of the service tenancy 819 to set up or otherwise pre-configure desired resources. The desired resources pre-configured in the control plane VCN 816 can be deployed to or otherwise used by the data plane VCN 818. In some examples, the control plane VCN 816 can be separable from the data plane VCN 818, and the data plane mirroring fabric 840 of the control plane VCN 816 can communicate with the data plane fabric 846 of the data plane VCN 818 through the VNIC 842 that can be included in the data plane mirroring fabric 840 and the data plane fabric 846.

[0086] In some examples, a user or customer of the system can make requests through the public Internet 854, which can communicate the requests to the metadata management service 852, for example, to perform create, read, update, or delete (CRUD) operations. The metadata management service 852 can communicate the requests to the control plane VCN 816 through the Internet gateway 834. This request can be received by the LB subnet 822 included in the control plane DMZ tier 820. The LB subnet 822 can determine that this request is valid, and in response to this determination, the LB subnet 822 can send the request to the app subnet 826 included in the control plane app tier 824. If the request is determined to be valid and requires a call to the public Internet 854, the call to the public Internet 854 can be sent to the NAT gateway 838 that can make a call to the public Internet 854. The metadata that may be desired to be stored by the request can be provided in the DB subnet 830.

[0087] In some examples, the data plane mirror app tier 840 can facilitate direct communication between the control plane VCN 816 and the data plane VCN 818. For example, changes, updates, or other suitable modifications to the configuration may be desired to be applied to the resources included in the data plane VCN 818. Through the VNIC 842, the control plane VCN 816 can communicate directly with the resources included in the data plane VCN 818, thereby performing changes, updates, or other suitable modifications to the configuration.

[0088] In some embodiments, the control plane VCN 816 and the data plane VCN 818 may be included in the service tenancy 819. In this case, a user or customer of the system may not own or operate either the control plane VCN 816 or the data plane VCN 818. Instead, an IaaS provider may own or operate both the control plane VCN 816 and the data plane VCN 818, which may both be included in the service tenancy 819. This embodiment may enable a separation of the network that may prevent a user or customer from interacting with the resources of other users or other customers. Also, this embodiment may enable a database to be privately stored without the need for a user or customer of the system to rely on the public Internet 854, which may not have the desired level of threat defense for storage.

[0089] In other embodiments, the LB subnet 822 included in the control plane VCN 816 may be configured to receive signals from the service gateway 836. In this embodiment, the control plane VCN 816 and the data plane VCN 818 may be configured to be called by a customer of the IaaS provider without calling the public Internet 854. Since the database used by the customer may be controllable by the IaaS provider and may be stored on the service tenancy 819 that may be separated from the public Internet 854, a customer of the IaaS provider may desire this embodiment.

[0090] FIG. 9 is a block diagram 900 showing another exemplary pattern of an IaaS architecture according to at least one embodiment. A service operator 902 (e.g., the service operator 802 of FIG. 8) can be communicatively coupled to a secure host tenancy 904 (e.g., the secure host tenancy 804 of FIG. 8) that can include a virtual cloud network (VCN) 906 (e.g., the VCN 806 of FIG. 8) and a secure host subnet 908 (e.g., the secure host subnet 808 of FIG. 8). The VCN 906 can include a local peering gateway (LPG) 910 (e.g., the LPG 810 of FIG. 8) communicatively coupled to an SSH VCN 912 (e.g., the SSH VCN 812 of FIG. 8) via the LPG 910 included in the secure shell (SSH) VCN 912. The SSH VCN 912 can include an SSH subnet 914 (e.g., the SSH subnet 814 of FIG. 8), and the SSH VCN 912 can be communicatively coupled to a control plane VCN 916 (e.g., the control plane VCN 816 of FIG. 8) via the LPG 910 included in the control plane VCN 916. The control plane VCN 916 can be included in a service tenancy 919 (e.g., the service tenancy 819 of FIG. 8), and the data plane VCN 918 (e.g., the data plane VCN 818 of FIG. 8) can be included in a customer tenancy 921 that can be owned or operated by a user or customer of the system.

[0091] The control plane VCN 916 may include a control plane DMZ tier 920 (e.g., the control plane DMZ tier 820 of FIG. 8) that may include an LB subnet 922 (e.g., the LB subnet 822 of FIG. 8), a control plane app tier 924 (e.g., the control plane app tier 824 of FIG. 8) that may include an app subnet 926 (e.g., the app subnet 826 of FIG. 8), and a control plane data tier 928 (e.g., the control plane data tier 828 of FIG. 8) that may include a database (DB) subnet 930 (similar to the DB subnet 830 of FIG. 8). The LB subnet 922 included in the control plane DMZ tier 920 may be communicatively coupled to the app subnet 926 included in the control plane app tier 924 and an Internet gateway 934 (e.g., the Internet gateway 834 of FIG. 8) that may be included in the control plane VCN 916. The app subnet 926 may be communicatively coupled to the DB subnet 930 included in the control plane data tier 928, as well as a service gateway 936 (e.g., the service gateway 836 of FIG. 8) and a network address translation (NAT) gateway 938 (e.g., the NAT gateway 838 of FIG. 8). The control plane VCN 916 may include the service gateway 936 and the NAT gateway 938.

[0092] The control plane VCN 916 may include a data plane mirror application affinity 940 (e.g., the data plane mirror application affinity 840 of FIG. 8) that may include an application subnet 926. The application subnet 926 included in the data plane mirror application affinity 940 may include a virtual network interface controller (VNIC) 942 (e.g., the VNIC 842) capable of executing a compute instance 944 (e.g., similar to the compute instance 844 of FIG. 8). The compute instance 944 may facilitate communication between the application subnet 926 of the data plane mirror application affinity 940 and an application subnet 926 that may be included in a data plane application affinity 946 (e.g., the data plane application affinity 846 of FIG. 8) via the VNIC 942 included in the data plane mirror application affinity 940 and the VNIC 942 included in the data plane application affinity 946.

[0093] The internet gateway 934 included in the control plane VCN 916 may be communicatively coupled to a metadata management service 952 (e.g., the metadata management service 852 of FIG. 8) that may be communicatively coupled to the public internet 954 (e.g., the public internet 854 of FIG. 8). The public internet 954 may be communicatively coupled to a NAT gateway 938 included in the control plane VCN 916. The service gateway 936 included in the control plane VCN 916 may be communicatively coupled to a cloud service 956 (e.g., the cloud service 856 of FIG. 8).

[0094] In some examples, the data plane VCN 918 can be included in the customer tenancy 921. In this case, the IaaS provider may provide a control plane VCN 916 for each customer, and the IaaS provider may set up a unique compute instance 944 included in the service tenancy 919 for each customer. Each compute instance 944 can enable communication between the control plane VCN 916 included in the service tenancy 919 and the data plane VCN 918 included in the customer tenancy 921. The compute instance 944 can enable resources preconfigured in the control plane VCN 916 included in the service tenancy 919 to be deployed or otherwise used in the data plane VCN 918 included in the customer tenancy 921.

[0095] In other examples, a customer of the IaaS provider may have a database that persists in the customer tenancy 921. In this example, the control plane VCN 916 can include a data plane mirror application entity 940 that can include an app subnet 926. The data plane mirror application entity 940 can reside in the data plane VCN 918, but the data plane mirror application entity 940 may not persist in the data plane VCN 918. That is, the data plane mirror application entity 940 can access the customer tenancy 921, but the data plane mirror application entity 940 may not exist in the data plane VCN 918 or may not be owned or operated by the customer of the IaaS provider. The data plane mirror application entity 940 can be configured to call the data plane VCN 918, but may not be configured to call any entity included in the control plane VCN 916. The customer may desire to deploy or otherwise use resources in the data plane VCN 918 preconfigured in the control plane VCN 916, and the data plane mirror application entity 940 can facilitate the desired deployment or other use of the customer's resources.

[0096] In some embodiments, customers of an IaaS provider can apply filters to the data plane VCN 918. In this embodiment, the customer can determine what the data plane VCN 918 can access, and the customer can restrict access from the data plane VCN 918 to the public Internet 954. The IaaS provider may not be able to apply or otherwise control filters on the access of the data plane VCN 918 to any external network or database. Applying customer filters and controls to the data plane VCN 918 included in the customer tenancy 921 can help separate the data plane VCN 918 from other customers and from the public Internet 954.

[0097] In some embodiments, the cloud service 956 may be called by the service gateway 936 to access services that may not be present on the public Internet 954, on the control plane VCN 916, or on the data plane VCN 918. The connection between the cloud service 956 and the control plane VCN 916 or the data plane VCN 918 may not be persistent or may not be continuous. The cloud service 956 may be present on a different network owned or operated by an IaaS provider. The cloud service 956 may be configured to receive calls from the service gateway 936 and may be configured not to receive calls from the public Internet 954. Some cloud services 956 may be isolated from other cloud services 956, and the control plane VCN 916 may be isolated from cloud services 956 that may not be in the same region as the control plane VCN 916. For example, the control plane VCN 916 may be located in "Region 1", and the cloud service "Deployment 8" may be located in Region 1 and "Region 2". If a call to Deployment 8 is made by the service gateway 936 included in the control plane VCN 916 located in Region 1, the call may be sent to Deployment 8 in Region 1. In this example, the control plane VCN 916, or Deployment 8 in Region 1, may not be communicatively coupled to or may not communicate with Deployment 8 in Region 2.

[0098] FIG. 10 is a block diagram 1000 showing another exemplary pattern of an IaaS architecture according to at least one embodiment. A service operator 1002 (e.g., the service operator 802 of FIG. 8) can be communicatively coupled to a secure host tenancy 1004 (e.g., the secure host tenancy 804 of FIG. 8) that can include a virtual cloud network (VCN) 1006 (e.g., the VCN 806 of FIG. 8) and a secure host subnet 1008 (e.g., the secure host subnet 808 of FIG. 8). The VCN 1006 can include an LPG 1010 that can be communicatively coupled to an SSH VCN 1012 (e.g., the SSH VCN 812 of FIG. 8) via an LPG 1010 included in the SSH VCN 1012. The SSH VCN 1012 can include an SSH subnet 1014 (e.g., the SSH subnet 814 of FIG. 8), and the SSH VCN 1012 can be communicatively coupled to a control plane VCN 1016 (e.g., the control plane VCN 816 of FIG. 8) via an LPG 1010 included in the control plane VCN 1016 and to a data plane VCN 1018 (e.g., the data plane 818 of FIG. 8) via an LPG 1010 included in the data plane VCN 1018. The control plane VCN 1016 and the data plane VCN 1018 can be included in a service tenancy 1019 (e.g., the service tenancy 819 of FIG. 8).

[0099] The control plane VCN 1016 may include a control plane DMZ tier 1020 (e.g., control plane DMZ tier 820 of FIG. 8) that may include a load balancer (LB) subnet 1022 (e.g., LB subnet 822 of FIG. 8), a control plane app tier 1024 (e.g., similar to control plane app tier 824 of FIG. 8) that may include an app subnet 1026 (e.g., similar to app subnet 826 of FIG. 8), and a control plane data tier 1028 (e.g., control plane data tier 828 of FIG. 8) that may include a DB subnet 1030. The LB subnet 1022 included in the control plane DMZ tier 1020 may be communicatively coupled to the app subnet 1026 included in the control plane app tier 1024 and an Internet gateway 1034 (e.g., Internet gateway 834 of FIG. 8) that may be included in the control plane VCN 1016. The app subnet 1026 may be communicatively coupled to the DB subnet 1030 included in the control plane data tier 1028, as well as a service gateway 1036 (e.g., service gateway of FIG. 8) and a network address translation (NAT) gateway 1038 (e.g., NAT gateway 838 of FIG. 8). The control plane VCN 1016 may include the service gateway 1036 and the NAT gateway 1038.

[0100] The data plane VCN 1018 may include a data plane app tier 1046 (e.g., the data plane app tier 846 of FIG. 8), a data plane DMZ tier 1048 (e.g., the data plane DMZ tier 848 of FIG. 8), and a data plane data tier 1050 (e.g., the data plane data tier 850 of FIG. 8). The data plane DMZ tier 1048 may include an LB subnet 1022 communicatively coupled to a trusted app subnet 1060 and an untrusted app subnet 1062 of the data plane app tier 1046 and to an Internet gateway 1034 included in the data plane VCN 1018. The trusted app subnet 1060 may be communicatively coupled to a service gateway 1036 included in the data plane VCN 1018, a NAT gateway 1038 included in the data plane VCN 1018, and a DB subnet 1030 included in the data plane data tier 1050. The untrusted app subnet 1062 may be communicatively coupled to a service gateway 1036 included in the data plane VCN 1018 and a DB subnet 1030 included in the data plane data tier 1050. The data plane data tier 1050 may include a DB subnet 1030 communicatively coupled to a service gateway 1036 included in the data plane VCN 1018.

[0101] The untrusted application subnet 1062 may include one or more primary VNICs 1064(1) to (N) communicatively coupled to tenant virtual machines (VMs) 1066(1) to (N). Each tenant VM 1066(1) to (N) may be communicatively coupled to respective application subnets 1067(1) to (N) that may be included in respective container egress VCNs 1068(1) to (N) that may be included in respective customer tenancies 1070(1) to (N). Each secondary VNIC 1072(1) to (N) may facilitate communication between the untrusted application subnet 1062 included in the data plane VCN 1018 and the application subnets included in the container egress VCNs 1068(1) to (N). Each container egress VCN 1068(1) to (N) may include a NAT gateway 1038 communicatively coupled to the public internet 1054 (e.g., the public internet 854 of FIG. 8).

[0102] The internet gateway 1034 included in the control plane VCN 1016 and in the data plane VCN 1018 may be communicatively coupled to a metadata management service 1052 (e.g., the metadata management system 852 of FIG. 8) communicatively coupled to the public internet 1054. The public internet 1054 may be communicatively coupled to a NAT gateway 1038 included in the control plane VCN 1016 and in the data plane VCN 1018. The service gateway 1036 included in the control plane VCN 1016 and in the data plane VCN 1018 may be communicatively coupled to a cloud service 1056.

[0103] In some embodiments, the data plane VCN 1018 can be integrated with the customer tenancy 1070. This integration can be useful or desirable for customers of the IaaS provider in some cases, such as when the code may require support when being executed. The customer may provide code that can be disruptive, communicate with other customer resources, or otherwise cause undesirable effects. In response, the IaaS provider can determine whether to execute the code provided by the customer to the IaaS provider.

[0104] In some examples, a customer of the IaaS provider can grant the IaaS provider temporary network access and request functions attached to the data plane app tier 1046. The code that executes that function can be executed in the VMs 1066(1)-(N), and the code cannot be configured to execute elsewhere on the data plane VCN 1018. Each of the VMs 1066(1)-(N) can be connected to one customer tenancy 1070. Each of the containers 1071(1)-(N) included in the VMs 1066(1)-(N) can be configured to execute code. In this case, double separation can exist (e.g., the containers 1071(1)-(N) can be included in at least the VMs 1066(1)-(N) included in the untrusted app subnet 1062), which can help prevent inaccurate or otherwise undesirable code from damaging the IaaS provider's network or the networks of different customers. The containers 1071(1)-(N) can be communicatively coupled to the customer tenancy 1070 and configured to send or receive data from the customer tenancy 1070. The containers 1071(1)-(N) may not be configured to send or receive data from any other entity in the data plane VCN 1018. Upon completion of the code execution, the IaaS provider can forcibly stop (kill) or otherwise dispose of the containers 1071(1)-(N).

[0105] In some embodiments, the trusted application subnet 1060 may execute code that can be owned or operated by an IaaS provider. In this embodiment, the trusted application subnet 1060 may be communicatively coupled to the DB subnet 1030 and may be configured to perform CRUD operations in the DB subnet 1030. The untrusted application subnet 1062 may be communicatively coupled to the DB subnet 1030, but in this embodiment, the untrusted application subnet may be configured to perform read operations in the DB subnet 1030. The containers 1071(1)-(N) that may be included in each customer's VMs 1066(1)-(N) and may execute code from that customer cannot be communicatively coupled to the DB subnet 1030.

[0106] In other embodiments, the control plane VCN 1016 and the data plane VCN 1018 may not be directly communicatively coupled. In this embodiment, there may be no direct communication between the control plane VCN 1016 and the data plane VCN 1018. However, communication may occur indirectly through at least one method. The LPG 1010 may be established by the IaaS provider and may facilitate communication between the control plane VCN 1016 and the data plane VCN 1018. In another example, the control plane VCN 1016 or the data plane VCN 1018 may call the cloud service 1056 via the service gateway 1036. For example, a call from the control plane VCN 1016 to the cloud service 1056 may include a request for a service that can communicate with the data plane VCN 1018.

[0107] FIG. 11 is a block diagram 1100 showing another exemplary pattern of an IaaS architecture according to at least one embodiment. A service operator 1102 (e.g., service operator 802 of FIG. 8) can be communicatively coupled to a secure host tenancy 1104 (e.g., secure host tenancy 804 of FIG. 8) that can include a virtual cloud network (VCN) 1106 (e.g., VCN 806 of FIG. 8) and a secure host subnet 1108 (e.g., secure host subnet 808 of FIG. 8). The VCN 1106 can include an LPG 1110 that can be communicatively coupled to an SSH VCN 1112 (e.g., SSH VCN 812 of FIG. 8) via an LPG 1110 included in the SSH VCN 1112. The SSH VCN 1112 can include an SSH subnet 1114 (e.g., SSH subnet 814 of FIG. 8), and the SSH VCN 1112 can be communicatively coupled to a control plane VCN 1116 (e.g., control plane VCN 816 of FIG. 8) via an LPG 1110 included in the control plane VCN 1116 and to a data plane VCN 1118 (e.g., data plane 818 of FIG. 8) via an LPG 1110 included in the data plane VCN 1118. The control plane VCN 1116 and the data plane VCN 1118 can be included in a service tenancy 1119 (e.g., service tenancy 819 of FIG. 8).

[0108] The control plane VCN 1116 may include a control plane DMZ tier 1120 (e.g., the control plane DMZ tier 820 of FIG. 8) that may include an LB subnet 1122 (e.g., the LB subnet 822 of FIG. 8), a control plane app tier 1124 (e.g., the control plane app tier 824 of FIG. 8) that may include an app subnet 1126 (e.g., the app subnet 826 of FIG. 8), and a control plane data tier 1128 (e.g., the control plane data tier 828 of FIG. 8) that may include a DB subnet 1130 (e.g., the DB subnet 1030 of FIG. 10). The LB subnet 1122 included in the control plane DMZ tier 1120 may be communicatively coupled to the app subnet 1126 included in the control plane app tier 1124 and an Internet gateway 1134 (e.g., the Internet gateway 834 of FIG. 8) that may be included in the control plane VCN 1116. The app subnet 1126 may be communicatively coupled to the DB subnet 1130 included in the control plane data tier 1128, as well as a service gateway 1136 (e.g., the service gateway of FIG. 8) and a network address translation (NAT) gateway 1138 (e.g., the NAT gateway 838 of FIG. 8). The control plane VCN 1116 may include the service gateway 1136 and the NAT gateway 1138.

[0109] The data plane VCN 1118 may include a data plane app tier 1146 (e.g., the data plane app tier 846 in FIG. 8), a data plane DMZ tier 1148 (e.g., the data plane DMZ tier 848 in FIG. 8), and a data plane data tier 1150 (e.g., the data plane data tier 850 in FIG. 8). The data plane DMZ tier 1148 may include an LB subnet 1122 communicatively coupled to a trusted app subnet 1160 (e.g., the trusted app subnet 1060 in FIG. 10) and an untrusted app subnet 1162 of the data plane app tier 1146 (e.g., the untrusted app subnet 1062 in FIG. 10), and an Internet gateway 1134 included in the data plane VCN 1118. The trusted app subnet 1160 may be communicatively coupled to a service gateway 1136 included in the data plane VCN 1118, a NAT gateway 1138 included in the data plane VCN 1118, and a DB subnet 1130 included in the data plane data tier 1150. The untrusted app subnet 1162 may be communicatively coupled to the service gateway 1136 included in the data plane VCN 1118 and the DB subnet 1130 included in the data plane data tier 1150. The data plane data tier 1150 may include a DB subnet 1130 communicatively coupled to the service gateway 1136 included in the data plane VCN 1118.

[0110] The untrusted application subnet 1162 may include primary VNICs 1164(1) to (N) communicatively coupled to tenant virtual machines (VMs) 1166(1) to (N) resident within the untrusted application subnet 1162. Each tenant VM 1166(1) to (N) can execute code in respective containers 1167(1) to (N) and can be communicatively coupled to an application subnet 1126 that may be included in a data plane application tier 1146 that may be included in a container egress VCN 1168. Each secondary VNIC 1172(1) to (N) can facilitate communication between the untrusted application subnet 1162 included in the data plane VCN 1118 and the application subnet included in the container egress VCN 1168. The container egress VCN may include a NAT gateway 1138 communicatively coupled to a public internet 1154 (e.g., the public internet 854 of FIG. 8).

[0111] The internet gateway 1134 included in the control plane VCN 1116 and included in the data plane VCN 1118 can be communicatively coupled to a metadata management service 1152 (e.g., the metadata management system 852 of FIG. 8) communicatively coupled to the public internet 1154. The public internet 1154 can be communicatively coupled to a NAT gateway 1138 included in the control plane VCN 1116 and included in the data plane VCN 1118. The service gateway 1136 included in the control plane VCN 1116 and included in the data plane VCN 1118 can be communicatively coupled to a cloud service 1156.

[0112] In some examples, the pattern exemplified by the architecture of block diagram 1100 of FIG. 11 may be considered an exception to the pattern exemplified by the architecture of block diagram 1000 of FIG. 10 and may be desirable for customers of an IaaS provider when the IaaS provider cannot communicate directly with the customer (e.g., a disconnected region). Each of the containers 1167(1) to (N) included in the VMs 1166(1) to (N) for each customer can be accessed in real time by the customer. The containers 1167(1) to (N) can be configured to make calls to respective secondary VNICs 1172(1) to (N) included in the application subnet 1126 of the data plane application tier 1146 that can be included in the container egress VCN 1168. The secondary VNICs 1172(1) to (N) can send calls to a NAT gateway 1138 that can send calls to the public internet 1154. In this example, the containers 1167(1) to (N) that can be accessed in real time by the customer can be separated from the control plane VCN 1116 and can be separated from other entities included in the data plane VCN 1118. The containers 1167(1) to (N) can also be separated from resources from other customers.

[0113] In other examples, a customer can call the cloud service 1156 using the containers 1167(1) through (N). In this example, the customer may execute code in the containers 1167(1) through (N) that requests services from the cloud service 1156. The containers 1167(1) through (N) may send this request to the secondary VNICs 1172(1) through (N), which may send the request to the NAT gateway, which may send the request to the public Internet 1154. The public Internet 1154 may send the request to the LB subnet 1122 included in the control plane VCN 1116 via the Internet gateway 1134. In response to a determination that the request is valid, the LB subnet may send the request to the app subnet 1126, which may send the request to the cloud service 1156 via the service gateway 1136.

[0114] It should be understood that the IaaS architectures 800, 900, 1000, 1100 shown in the figures may have other components in addition to those illustrated. Further, the embodiments shown in the figures are merely examples of cloud infrastructure systems that may incorporate embodiments of the present disclosure. In some other embodiments, the IaaS system may have more or fewer components than those shown in the figures, may combine two or more components, or may have different configurations or arrangements of components.

[0115] In one embodiment, the IaaS system described herein may include the delivery of a suite of applications, middleware, and database services to customers in a self-service, subscription-based, elastically scalable, highly reliable, highly available, and secure manner. An example of such an IaaS system is the Oracle Cloud Infrastructure (OCI) provided by the assignee hereof.

[0116] FIG. 12 shows an exemplary computer system 1200 in which various embodiments may be implemented. System 1200 may be used to implement any of the computer systems described above. As shown in the figure, computer system 1200 includes a processing unit 1204 that communicates with a number of peripheral subsystems via a bus subsystem 1202. These peripheral subsystems may include a processing acceleration unit 1206, an I / O subsystem 1208, a storage subsystem 1218, and a communication subsystem 1224. Storage subsystem 1218 includes a tangible computer-readable storage medium 1222 and system memory 1210.

[0117] Bus subsystem 1202 provides a mechanism for enabling the various components and subsystems of computer system 1200 to communicate with each other as intended. Bus subsystem 1202 is shown schematically as a single bus, although alternative embodiments of the bus subsystem may utilize multiple buses. Bus subsystem 1202 may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus, using any of a variety of bus architectures. For example, such architectures may include an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MCA) bus, an Enhanced ISA (EISA) bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus, which may be implemented as a Mezzanine bus manufactured in accordance with the IEEE P1386.1 standard.

[0118] A processing unit 1204, which can be implemented as one or more integrated circuits (e.g., a conventional microprocessor or microcontroller), controls the operation of computer system 1200. One or more processors can be included in processing unit 1204. These processors can include single-core or multi-core processors. In some embodiments, processing unit 1204 can be implemented as one or more independent processing units 1232 and / or 1234, each including a single-core or multi-core processor included in each processing unit. In other embodiments, processing unit 1204 can also be implemented as a quad-core processing unit formed by integrating two dual-core processors on a single chip.

[0119] In various embodiments, processing unit 1204 can execute a wide variety of programs in response to program code and can maintain multiple simultaneously executing programs or processes. At any given time, some or all of the program code being executed can reside in processor 1204 and / or storage subsystem 1218. Through suitable programming, processor 1204 can provide the various functions described above. Computer system 1200 can additionally include a processing acceleration unit 1206, which can include a digital signal processor (DSP), an application-specific processor, and / or the like.

[0120] The I / O subsystem 1208 may include user interface input devices and user interface output devices. User interface input devices can include a keyboard, a pointing device such as a mouse or trackball, a touchpad or touch screen incorporated into a display, a scroll wheel, a click wheel, a dial, buttons, switches, a keypad, a voice input device having a voice command recognition system, a microphone, and other types of input devices. User interface input devices can include motion sensing and / or gesture recognition devices such as a Microsoft Kinect (registered trademark) motion sensor that enables a user to control an input device, such as an input device like a Microsoft Xbox (registered trademark) 360 game controller, and interact with the input device through a natural user interface using gestures and spoken commands. User interface input devices can also include eye gesture recognition devices such as a Google Glass (registered trademark) blink detector that detects eye activity from a user (e.g., a "blink" during photo taking and / or menu selection) and converts the eye gesture into an input to the input device (e.g., Google Glass (registered trademark)). Additionally, user interface input devices can include voice recognition sensing devices that enable a user to interact with a voice recognition system (e.g., a Siri (registered trademark) navigator) through voice commands.

[0121] The user interface input device may also include, but is not limited to, a three-dimensional (3D) mouse, joystick or pointing stick, game pad and graphic tablet, and audio / visual devices such as speakers, digital cameras, digital camcorders, portable media players, webcams, image scanners, fingerprint scanners, barcode readers, 3D scanners, 3D printers, laser distance meters, and eye gaze tracking devices. In addition, the user interface input device may include, for example, medical image input devices such as computed tomography, magnetic resonance imaging, positron emission tomography, and medical ultrasound examination devices. The user interface input device may also include, for example, audio input devices such as MIDI keyboards, digital musical instruments, and the like.

[0122] The user interface output device may include a non-visual display such as a display subsystem, indicator lights, or an audio output device. The display subsystem may be a cathode ray tube (CRT), a flat panel device using, for example, a liquid crystal display (LCD) or a plasma display, a projection device, a touch screen, and the like. Generally, the use of the term "output device" is intended to include all possible types of devices and mechanisms for outputting information from the computer system 1200 to the user or another computer. For example, the user interface output device may include, without limitation, a variety of display devices for visually conveying text, graphics, and audio / video information such as monitors, printers, speakers, headphones, automotive navigation systems, plotters, voice output devices, and modems.

[0123] The computer system 1200 may include a storage subsystem 1218 that includes software elements shown as currently located within the system memory 1210. The system memory 1210 may store program instructions loadable and executable by the processing unit 1204, as well as data generated during the execution of those programs.

[0124] Depending on the configuration and type of computer system 1200, system memory 1210 may be volatile (such as random access memory (RAM)) and / or non-volatile (such as read-only memory (ROM), flash memory, etc.). RAM is typically immediately accessible to processing unit 1204 and / or includes data and / or program services that are currently being operated on and executed by processing unit 1204. In some embodiments, system memory 1210 may include multiple different types of memory such as static random access memory (SRAM) or dynamic random access memory (DRAM). In some embodiments, a basic input / output system (BIOS) including basic routines that assist in the transmission of information between elements within computer system 1200, such as during startup, may typically be stored in ROM. By way of example and without limitation, system memory 1210 may also include application programs 1212, program data 1214, and operating system 1216 that may include, for example, client applications, web browsers, middleware applications, relational database management systems (RDBMS), etc. By way of example, operating system 1216 may include various versions of Microsoft Windows®, Apple Macintosh®, and / or Linux® operating systems, a wide variety of commercially available UNIX® or UNIX-like operating systems (including but not limited to various GNU / Linux® operating systems, Google Chrome® OS, etc.), and / or mobile operating systems such as iOS, Windows® Phone, Android®, BlackBerry®, and Palm® OS.

[0125] The storage subsystem 1218 may also provide a tangible computer-readable storage medium for storing the basic programming and data structures that provide the functionality of some embodiments. When executed by a processor, software (programs, code services, instructions) that provides the functionality described above may be stored in the storage subsystem 1218. These software services or instructions may be executed by the processing unit 1204. The storage subsystem 1218 may also provide a repository for storing data used in accordance with the present disclosure.

[0126] The storage subsystem 1200 may also include a computer-readable storage medium reader 1220 that may be further connected to a computer-readable storage medium 1222. Together, and optionally in combination with the system memory 1210, the computer-readable storage medium 1222 may comprehensively represent remote, local, fixed, and / or removable storage devices and storage media for temporarily and / or more permanently containing, storing, transmitting, and receiving computer-readable information.

[0127] The computer-readable storage medium 1222 that includes code or a portion of the code may also include any suitable media known in or used in the art, including but not limited to storage media and communication media such as volatile and non-volatile removable and non-removable media implemented in any method or technology for storing and / or transmitting information. This may include tangible computer-readable storage media such as RAM, ROM, electrically erasable programmable ROM (EEPROM), flash memory, or other memory technologies, CD-ROM, digital versatile disk (DVD), or other optical storage devices, magnetic cassettes, magnetic tapes, magnetic disk storage devices, or other magnetic storage devices, or other tangible computer-readable media. This may also include intangible computer-readable media such as data signals, data transmissions, or any other medium that can be used to transmit the desired information and is accessible by the computing system 1200.

[0128] As an example, computer-readable storage medium 1222 can include a hard disk drive that reads from or writes to a non-removable, non-volatile magnetic medium, a magnetic disk drive that reads from or writes to a removable, non-volatile magnetic disk, and an optical disk drive that reads from or writes to a removable, non-volatile optical disk such as a CD-ROM, DVD, and Blu-Ray (registered trademark) disk, or other optical media. Computer-readable storage medium 1222 can include, but is not limited to, a Zip (registered trademark) drive, a flash memory card, a Universal Serial Bus (USB) flash drive, a Secure Digital (SD) card, a DVD disk, a digital video tape, etc. Computer-readable storage medium 1222 can also include a solid state drive (SSD) based on non-volatile memory such as a flash memory-based SSD, an enterprise flash drive, a solid state ROM, an SSD based on volatile memory such as solid state RAM, dynamic RAM, static RAM, a DRAM-based SSD, a magnetoresistive RAM (MRAM) SSD, and a hybrid SSD that uses a combination of DRAM and flash memory-based SSDs. Disk drives and their associated computer-readable media can provide non-volatile storage of computer-readable instructions, data structures, program services, and other data for computer system 1200.

[0129] The communication subsystem 1224 provides an interface to other computer systems and networks. The communication subsystem 1224 functions as an interface for receiving data from other systems and transmitting data from the computer system 1200 to other systems. For example, the communication subsystem 1224 may enable the computer system 1200 to connect to one or more devices via the Internet. In some embodiments, the communication subsystem 1224 may include radio frequency (RF) transceiver components, global positioning system (GPS) receiver components, and / or other components for accessing wireless voice and / or data networks using advanced data network technologies such as, for example, cellular phone technology, 3G, 4G, or EDGE (enhanced data rates for global evolution), WiFi (registered trademark) (IEEE 802.11 family standards or other mobile communication technologies, or any combination thereof). In some embodiments, the communication subsystem 1224 may provide wired network connectivity (e.g., Ethernet (registered trademark)) in addition to, or instead of, a wireless interface.

[0130] In some embodiments, the communication subsystem 1224 may also receive input communications on behalf of one or more users of the computer system 1200 in the form of structured and / or unstructured data feeds 1226, event streams 1228, event updates 1230, and the like.

[0131] As an example, the communication subsystem 1224 may be configured to receive in real time data feeds 1226 from one or more third-party information sources, such as Twitter (registered trademark) feeds, Facebook (registered trademark) updates, web feeds such as Rich Site Summary (RSS) feeds, and / or data feeds from users of social networks and / or other communication services such as real-time updates.

[0132] In addition, the communication subsystem 1224 can also be configured to receive data in the form of a continuous data stream, which can include an event stream 1228 of real-time events and / or event updates 1230 that can be virtually continuous or infinite without a clear end. Examples of applications that generate continuous data can include, for example, sensor data applications, financial tickers, network performance measurement tools (e.g., network monitoring and traffic management applications), clickstream analysis tools, automotive traffic monitoring, and the like.

[0133] The communication subsystem 1224 can be configured to output structured and / or unstructured data feeds 1226, event streams 1228, event updates 1230, etc. to one or more databases that can communicate with one or more streaming data source computers coupled to the computer system 1200.

[0134] The computer system 1200 can be of various types, including handheld portable devices (e.g., iPhone (registered trademark) mobile phone, iPad (registered trademark) computing tablet, PDA), wearable devices (e.g., Google Glass (registered trademark) head-mounted display), PCs, workstations, mainframes, kiosks, server racks, or any other data processing system.

[0135] Due to the ever-changing nature of computers and networks, the description of computer system 1200 shown in the figures is intended as a specific example only. Many other configurations are possible with more or fewer components than the system shown in the figures. For example, customized hardware may also be used, and / or certain elements may be implemented in hardware, firmware, software (including applets), or combinations thereof. Additionally, connections to other computing devices such as network input / output devices may also be used. Based on the disclosure and teachings provided herein, those skilled in the art will understand other ways and / or methods for implementing various embodiments.

[0136] Embodiments may be implemented using a computer program product comprising computer program / instructions that, when executed by a processor, cause the processor to execute any of the methods described in this disclosure.

[0137] Although specific embodiments have been described, various modifications, alterations, alternative structures, and equivalents are also included within the scope of this disclosure. Embodiments are not limited to operating within a particular data processing environment and are free to operate within multiple data processing environments. Additionally, although embodiments have been described using a specific series of transactions and steps, it will be apparent to those skilled in the art that the scope of this disclosure is not limited to the series of transactions and steps described. The various features and aspects of the embodiments described above may be used individually or in combination.

[0138] Furthermore, although embodiments have been described using specific combinations of hardware and software, it will be appreciated that other combinations of hardware and software are also within the scope of the present disclosure. Embodiments may be implemented using hardware only, software only, or combinations thereof. The various processes described herein may be implemented on the same processor or different processors in any combination. Accordingly, when a component or service is described as being configured to perform an operation, such a configuration may be realized, for example, by designing an electronic circuit to perform the operation, by programming a programmable electronic circuit (such as a microprocessor) to perform the operation, or by any combination thereof. Processes can communicate using a variety of techniques including, but not limited to, conventional techniques for inter-process communication, different pairs of processes can use different techniques, or the same pair of processes can use different techniques at different times.

[0139] Accordingly, the specification and drawings are to be regarded in an illustrative rather than a limiting sense. However, it will be apparent that additions, deletions, omissions, as well as other modifications and changes may be made without departing from the broader spirit and scope as set forth in the claims. Thus, while specific embodiments of the disclosure have been described, they are not intended to be limiting. Various modifications and equivalents are within the scope of the appended claims.

[0140] In the context of describing the disclosed embodiments (in particular, in the context of the appended claims), the terms "a", "an", and "the", as well as similar referents, should be construed to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by the context. The terms "comprising", "having", "including", and "containing" should be construed as open-ended terms (i.e., meaning "including, but not limited to") unless otherwise specified. The term "connected" should be construed to mean included, attached, or joined together, either partially or wholly, even if there is something intervening. References to ranges of values herein are intended only to serve as a shorthand way of referring individually to each separate value falling within the range, and each separate value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order, unless otherwise indicated herein or clearly contradicted by the context. The use of any examples and all examples provided herein, or exemplary language (e.g., "such as") is intended merely to clarify the embodiments and does not impose a limitation on the scope of the disclosure unless otherwise claimed. No expression herein should be construed as indicating that any non-claimed element is essential for carrying out the disclosure.

[0141] Disjunctive expressions such as the phrase "at least one of X, Y, or Z" are generally understood in context to be used to indicate that items, terms, etc. can be any one of X, Y, or Z, or any combination thereof (e.g., X, Y, and / or Z), unless otherwise specified. Thus, such disjunctive expressions are not generally intended, and should not be construed, to imply that an embodiment requires the presence of each of at least one X, at least one Y, or at least one Z.

[0142] Preferred embodiments of the present disclosure, including the best mode known to the applicant for carrying out the present disclosure, are described herein. Variations of those preferred embodiments will be apparent to those skilled in the art upon reading the above description. Those skilled in the art should be able to appropriately use such variations, and the present disclosure may be practiced without departing from the spirit and scope of the present disclosure as set forth in the claims appended hereto as permitted by applicable law. Accordingly, the present disclosure includes all modifications and equivalents of the subject matter recited in the claims appended hereto as permitted by applicable law. In addition, any combination of the above-described elements in all possible variations thereof is included in the present disclosure unless otherwise specifically stated herein.

[0143] All references, including publications, patent applications, and patents, cited herein are hereby incorporated by reference in their entirety, as if each reference were individually and specifically indicated to be incorporated by reference and set forth in its entirety herein.

[0144] In the foregoing specification, embodiments of the present disclosure have been described with reference to specific embodiments thereof, but those skilled in the art will recognize that the present disclosure is not limited thereto. The various features and aspects of the above-described disclosure can be used individually or in combination. Further, embodiments can be utilized in any number of environments and applications beyond those described herein without departing from the broader spirit and scope of the present disclosure. Accordingly, the specification and drawings are to be regarded as illustrative rather than restrictive.

Claims

1. A method performed by a computer, To detect a modification of the mapping from a first memory location to a cache location within the instruction cache accessible by the hardware processor, Based on detecting at least the modification of the mapping, a verification operation is triggered to verify one or more instructions in the instruction cache, The process includes performing the verification operation for verifying one or more instructions in the instruction cache, and performing the verification operation is Collecting metrics associated with one or more instructions in the instruction cache, The possibility of a ransomware attack is determined based on the aforementioned metrics, A method performed by a computer, including sending a notification based on the aforementioned possibility of a ransomware attack.

2. To detect the instruction class of the instruction stored in the instruction cache, Determining the frequency of instances of the instruction in the instruction cache, Assigning weights to the instruction based at least partially on the instruction class, A method performed by a computer according to claim 1, further comprising determining the likelihood of the ransomware attack based at least in part on the weights.

3. The above method further, The method includes generating a first cryptographic bitmap containing a first row of encryption-related data associated with the instruction cache, and generating a second cryptographic bitmap containing a second row of encryption-related data associated with the instruction cache, wherein the first row is associated with a first instruction among the one or more instructions, and the method further includes: In order to derive the delta value, a mathematical exclusive operation is performed on the first row and the second row, The derived delta value is compared with the threshold delta value, A method performed by a computer according to claim 1, comprising determining whether the aforementioned possibility of a ransomware attack is a false positive based on the comparison.

4. The method described above, further comprising registering a callback function, wherein the notification is transmitted using the callback function, is performed by a computer according to claim 1.

5. A method performed by a computer according to claim 1, further comprising receiving a notification that an instance has been repaved, at least in part based on the determination of the likelihood of the ransomware attack.

6. The computer-operated method according to claim 1, further comprising determining whether the modification to the mapping exceeds a threshold number of modifications, and performing the verification operation is in response to determining whether the modification to the mapping exceeds a threshold number of modifications.

7. The one or more instructions include an assembly instruction related to encryption, A method performed by a computer according to claim 1, wherein determining the likelihood of the ransomware attack based on the metric includes determining that one or more of the assembly instructions exceed a threshold.

8. Determining the likelihood of a ransomware attack based on the aforementioned metrics is: Assigning each of the one or more instructions to one of a plurality of instruction classes, based on the instruction type of each of the one or more instructions, Using the weights associated with each of the aforementioned instruction classes, the weighted frequency of each instruction class is determined. A method performed by a computer according to claim 1, comprising determining the likelihood of the ransomware attack based on the sum of the weighted frequencies that exceed a threshold.

9. The method performed by the computer according to claim 1, wherein the modification of the mapping from the instruction cache location to the first memory location within the instruction cache is performed before executing the operation stored in the first memory location.

10. It is a cloud infrastructure node, Processor and A computer-readable medium containing instructions, wherein when the instructions are executed by the processor, the processor receives To detect a modification of the mapping from a first memory location to a cache location within the instruction cache accessible by the hardware processor, Based on detecting at least the modification of the mapping, a verification operation is triggered to verify one or more instructions in the instruction cache, Performing the verification operation to verify one or more instructions in the instruction cache, and performing the verification operation, Collecting metrics associated with one or more instructions in the instruction cache, The possibility of a ransomware attack is determined based at least partially on the aforementioned comparison, A cloud infrastructure node that includes sending a notification of the possibility of the aforementioned ransomware attack.

11. The aforementioned instruction further instructs the processor, To detect the instruction class of the instruction stored in the instruction cache, Determining the frequency of instances of the instruction in the instruction cache, Assigning weights to the instruction based at least partially on the aforementioned class, A cloud infrastructure node according to claim 10 or 11, which determines the likelihood of a ransomware attack based at least in part on the weights.

12. The aforementioned instruction further instructs the processor, The system generates a first cryptographic bitmap containing a first row of encryption-related data associated with the instruction cache, and generates a second cryptographic bitmap containing a second row of encryption-related data associated with the instruction cache, wherein the first row is associated with a first instruction among the one or more instructions, and the instruction further causes the processor to: In order to derive the delta value, a mathematical exclusive operation is performed on the first row and the second row, The derived delta value is compared with the threshold delta value, A cloud infrastructure node according to claim 10 or 11, which determines whether the aforementioned possibility of a ransomware attack is a false positive based on the comparison described above.

13. The cloud infrastructure node according to claim 10 or 11, wherein the instruction further causes the processor to register a callback function, and the notification is transmitted using the callback function.

14. The cloud infrastructure node according to claim 10 or 11, wherein the instruction further causes the processor to receive a notification that the instance has been repaved, at least in part based on the determination of the likelihood of the ransomware attack.

15. The cloud infrastructure node according to claim 10 or 11, wherein the instruction further causes the processor to determine that the modification to the mapping exceeds a threshold number of modifications, and the execution of the verification operation is in response to the determination that the modification to the mapping exceeds a threshold number of modifications.

16. The one or more instructions include an assembly instruction related to encryption, The cloud infrastructure node according to claim 10 or 11, wherein determining the likelihood of the ransomware attack based on the metric includes determining that one or more of the assembly instructions exceed a threshold.

17. Determining the likelihood of a ransomware attack based on the aforementioned metrics is: Assigning each of the one or more instructions to one of a plurality of instruction classes, based on the instruction type of each of the one or more instructions, Using the weights associated with each of the aforementioned instruction classes, the weighted frequency of each instruction class is determined. A cloud infrastructure node according to claim 10 or 11, comprising determining the likelihood of the ransomware attack based on the sum of the weighted frequencies that exceed a threshold.

18. The cloud infrastructure node according to claim 10 or 11, wherein the modification of the mapping from the instruction cache location to the first memory location within the instruction cache is performed before executing the operation stored in the first memory location.

19. A program for causing a computer to perform the method described in any one of claims 1 to 9.

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