601 results about "Bytecode" patented technology

The invention discloses a cross-chain smart contract vulnerability detection method and system based on multi-feature fusion learning. The method comprises the following steps: collecting a cross-chain smart contract vulnerability data set for cleaning and labeling; feature extraction is carried out from the source code and the byte code, an abstract syntax tree (AST) is extracted from the cleaned source code, a basic control flow graph (CFG) is extracted from the byte code, and a cross-chain control flow graph (xCFG) is constructed; carrying out feature representation on AST and xCFG, generating a graph vector through a graph neural network (GNN), generating a semantic vector through CodeBert, and fusing the semantic vector into a feature fusion vector; performing model training and detection, taking the generated vectors as training data and test data, obtaining a cross-chain smart contract vulnerability detection model by adopting Transform-FC model training data, and finally evaluating model performance through accuracy, recall rate, precision rate and F1 value. According to the method, the structural features and semantic features of the codes can be effectively fused, potential vulnerability information in the codes can be fully mined, the recognition capability of the model for cross-chain vulnerabilities can be enhanced, and the accuracy and reliability of the cross-chain vulnerability detection model can be improved, so that the security of a block chain system can be more efficiently guaranteed.

The invention relates to the field of byte code unshelling storage, in particular to a byte code storage method and device of an Android unshelling machine and computer equipment. The method comprises the following steps: monitoring all application programs in a system in real time, and carrying out pseudo-call dynamic class loading to generate byte code structure feature information; performing service module identification on the byte code structure feature information, and performing module security sensitivity quantification so as to obtain a security sensitivity quantized value of each service module; based on the security sensitive quantized value of each service module, performing byte code symmetric encryption and confusion encryption on the multiple application program service modules so as to obtain a normalized module encryption code and a confusion encryption compression code; and carrying out code-by-code independent packaging processing on the normalized module encryption code and the confusion encryption compression code, and carrying out distributed storage so as to construct a distributed encryption unit storage structure. According to the invention, complete and efficient shelling preservation is realized.

The invention provides an intrusion prevention method, a management unit, a system and a storage medium, and relates to the field of network security, and the method comprises the steps: collecting context operation data corresponding to a to-be-tracked asset object in a kernel, and carrying out the security management of the context operation data, and obtaining a first target security control strategy corresponding to the to-be-tracked asset object; and mounting a first target BPF byte code corresponding to the first target security control strategy in a Linux security module so as to monitor and defend the target asset object through the Linux security module. Or in response to the security policy configuration request, extracting a second target security control policy from the security policy configuration request; and when the second target security control strategy is activated, mounting a second target BPF byte code corresponding to the second target security control strategy in the Linux security module. Therefore, through the above intrusion prevention method, the embodiment of the invention can immediately block attacks and improve the convenience of maintenance and deployment.

The embodiment of the invention provides a byte code generation method and device and a machine code generation method and device, and the byte code generation method comprises the steps that a target source code is obtained, first processing is applied to the target source code, and the first processing comprises the steps that a target statement used for integer operation in the target source code is replaced with a preset target function; according to the first processed target source code, a target byte code is generated, the target byte code comprises a byte code instruction generated according to a preset function, and the byte code instruction indicates that integer operation corresponding to the target statement is executed through a preset machine instruction sequence and overflow check for the integer operation is executed.

An adaptive dependency replay control system for use in a latency-sensitive ad serving backend, comprising: a microcontroller-based replay control engine configured to receive ad serving requests and interface with a variety of downstream microservices; a latency monitoring unit operatively coupled to the microcontroller, the latency monitoring unit continuously sampling and maintaining real-time latency histograms for each downstream microservice over sliding time windows; a health status aggregator communicatively coupled to the retry control engine, the aggregator configured to receive service-level health indicators, including, but not limited to, HTTP status codes, circuit breaker states, request timeout counters, and error rate thresholds; a retry decision processing unit stored in a memory accessible to the microcontroller, wherein the matrix can generate a retry action vector based on one or more of the following factors: dependency health, request priority, estimated ad impression value, and system resource metrics; a policy execution engine configured to evaluate retry policies expressed in a domain-specific retry policy language, wherein the execution engine resolves the policies into bytecode rules that are executed by the retry control engine in real time on a per-request basis; and at least one fallback path generator capable of returning an approximate or synthetic response instead of retrying a degraded dependency, where the fallback path is selected based on runtime evaluation of the policy conditions and a calculated retry confidence value.

The invention relates to the field of risk data visual tracing, and provides a visual track tracing method and system for a risk checking task, and the method comprises the steps: analyzing a heterogeneous data stream, separating a source metadata set, calculating an original structure entropy fingerprint, intercepting an end feature, embedding a global tracking identifier, and generating a packaging data package; generating transformed service data by using dynamic byte code instrumentation, constructing a runtime execution context and a differential snapshot, and transmitting an instantiated track node object according to a shunt delivery strategy; mapping and instantiating the logical topology execution graph based on the Hash fragments, and marking a pollution state and generating a total element execution link graph when the logic topology execution graph is abnormal; the method comprises the steps of generating a topology summary data packet, rendering a real-time state view, responding to physical interaction operation to construct a retrieval request data packet, reconstructing a full-amount service load through topology backtracking and reverse data evolution, and generating an attribution view in combination with static codes and rule description. According to the method, a dynamic trajectory tracing and full-link risk visualization mechanism of massive heterogeneous data is constructed.

The invention discloses a code obfuscation method, device and equipment and a storage medium, and belongs to the field of financial science and technology, and the method comprises the steps: obtaining an original byte code file corresponding to an application program source code; identifying to-be-confused data in the original byte code file, and confusing and renaming the to-be-confused data according to a mapping name of the to-be-confused data in the naming mapping table to obtain a first confused file corresponding to the original byte code file; identifying a control flow in the first confusion file, and performing confusion recombination on the identified control flow to obtain a second confusion file; and performing confusion processing on methods contained in various types in the second confusion file to obtain a target confusion file. According to the method, the maintainability and the resistance of the application program source code are enhanced, the risk that the application program source code is decompiled is reduced, the safety of the application program source code is improved, and then the safety of the application program is improved.

The invention discloses a cross-language application program vulnerability mining method based on static analysis, which adopts a nested cross-programming language pointer analysis method and a micro-service cross-programming language taint tracking method to effectively solve the limitation of processing nested cross-language control flow and micro-service cross-language data flow. A nested language semantic boundary is accurately positioned by constructing a nested byte code, and a data stream is completely tracked by utilizing an interface relay technology, so that the detection precision is improved. According to the method, part of multi-end data streams and complex control streams of cross-programming language applications can be uniformly processed, and the analysis process in a cross-programming language environment is simplified; by nesting cross-programming language control flow diagram construction and double-end / multi-end data flow diagram construction, a unified analysis framework is constructed, seamless cooperation of static analysis among different languages is achieved, the analysis cost is reduced, the analysis efficiency is improved, efficient and accurate vulnerability mining is achieved in a complex cross-programming language application program, and the method is suitable for application and popularization. And the reliability of cross-language vulnerability detection is improved.

The invention provides a server-free dynamic management and control method based on an extended Burkley packet filter, and the method comprises the steps: mounting an eBPF program to a kernel cgroup subsystem, monitoring a function instance creation / destruction event in real time, extracting metadata, dynamically generating a fine-grained network strategy, compiling the fine-grained network strategy into an eBPF byte code, and injecting the eBPF byte code into a Map format strategy table, realizing data packet level allowing / discarding control by using a flow control hook; and when the instance is destroyed, the strategy table rule is automatically cleared through a cgroprease event. Through kernel-level dynamic management and control, precise security protection, zero-trust micro-isolation and kernel layer malicious behavior interception of the function instance in the full life cycle are realized, and the security efficiency and the resource utilization rate of the cloud native environment are remarkably improved.

The invention relates to the technical field of electrical digital data processing, in particular to an intelligent contract vulnerability detection method based on multi-modal selection state space fusion, and aims to solve the technical problem of low vulnerability detection accuracy in the prior art. The method comprises the following steps: firstly, fusing global and local features of a contract graph to obtain graph modal embedding features; performing feature alignment on the text context information of the intermediate representation text and the byte code text to obtain text modal embedding features; extracting spatial layout features from the color image and the grayscale image, and splicing the spatial layout features to obtain visual modal embedding features; thirdly, performing multiple rounds of feature cross processing on the graph modal embedding features, the text modal embedding features and the visual modal embedding features based on a selection state space to realize intra-modal and inter-modal information interaction, and then performing fusion to obtain multi-modal fusion features; and finally, performing feature normalization and regularization processing on the multi-modal fusion features, and performing classification processing to obtain a vulnerability detection result.

The invention relates to a data operation method of a model, which is applied to the operation of an artificial intelligence (AI) model. In the method, based on an input tensor of an operation in an AI model during actual operation, a calculation graph corresponding to the operation in the AI model is compiled into a byte code instruction, and then the byte code instruction is interpreted and operated through a virtual machine which is pre-configured with a corresponding processing function, so that the operation in the AI model is executed. The execution of a traditional tedious compiling process is effectively avoided, and the running time of the AI model is shortened.

The invention relates to the technical field of data acquisition, in particular to an AOP-based user behavior data acquisition method. The method comprises the following steps: firstly, identifying user behavior related code features by statically analyzing Java source codes of an application program, and constructing a feature template library; during a compiling period, according to a template library identification target method, embedding a point burying instruction by utilizing a byte code enhancement technology, and constructing a monitoring section framework; and during running, dynamically adjusting an execution strategy according to the running state of the application program by virtue of a dynamic rule engine. Meanwhile, an annular buffer area is adopted to asynchronously process user behavior data streams, cache data are managed in a sub-generation mode, and asynchronous processing is triggered when a threshold value is exceeded. The method also constructs an adaptive thread pool model based on a hierarchical thread pool architecture, distributes tasks according to data value weights, monitors the task backlog rate of a high-priority sub-pool, adjusts the sampling frequency or acquisition dimension when the task backlog rate exceeds a threshold value, forms adaptive closed-loop control, and effectively acquires and processes user behavior data.

Disclosed are systems, apparatuses, methods, and computer-readable media for heterogenous network services using platform agnostic extensions. A method includes: instantiating a first service having a first data plane control point; instantiating a second service configured to access the first control point in a data plane; receiving a first packet at the first service in a network path; providing at least one of the first packet and first metadata associated with the first packet to the second service to analyze or process the first packet and the first metadata in conjunction with the first service; processing at least one of the first packet or the first metadata in the second service based on external bytecode and generating at least second metadata based on the processing; receiving second metadata to the first service; and processing the first packet or a second packet.

The invention provides a mock platform construction method oriented to a travel saas platform. The mock platform construction method comprises the following steps: demand analysis: determining a target and a demand of a Mock platform; environment preparation: ensuring that the Java environment of the target SaaS platform meets the operation of the java byte code instrumentation technology; integration of a java byte code instrumentation technology: the java byte code instrumentation technology is integrated into an SaaS platform; according to the invention, a Java byte code instrumentation technology is utilized to construct a software as a service (SaaS) platform interface Mock platform which is powerful in function, flexible and easy to use, and the Mock platform can dynamically perform Mock on the interface of the SaaS platform without restarting an application, so that the development and test efficiency is greatly improved, and the development cost is reduced. And the Mock platform also has the characteristics of non-invasiveness, dynamic plugging, class isolation, flexible AOP support, self-definition, real-time monitoring and fault simulation, easiness in integration and use, safety, fault positioning and performance optimization.

The invention provides an intelligent solitary policy processing method based on a neural network and machine learning, and relates to the field of data processing. According to the method, strategy byte codes and execution contexts are generated by extracting business rules, supervision calibers and field dependency relationships of the single insurance policy, discovery, repair and arbitration of field abnormity are achieved in combination with a dynamic data governance model, an account-falling confirmation receipt is output through a voting game and a compensation transaction, and a replayable trace and a rare mode index are generated. And a high-confidence label and an error correction prior increment are obtained in combination with triggering verification, and finally, full-link evidence is solidified through continuous distillation, chain type evidence storage and an auditable snapshot library, so that a traceable record of the single insurance policy is formed. By implementing the technical scheme provided by the invention, full-link data processing can be conveniently carried out on the single insurance policy, so that the processing efficiency is effectively improved.

A container mirror image generation system based on an agency-free service grid framework comprises a multi-dimensional rule configuration module, a full-link gray level isolation module, a micro-service strategy injection module, a byte enhancement module and a link unvarnished transmission implementation module. The advantages of a software toolkit (core tools and libraries required for developing, compiling, debugging and running application programs) and a service grid are combined, and non-invasive treatment logic injection, flexible expansibility and efficient performance optimization are provided. The service management in the micro-service architecture is simplified, the observability and safety of the system are improved, and the method has important significance for the modern micro-service environment.

The invention provides a software monitoring method, system and device based on byte code replacement and risk awareness and a medium, and belongs to the technical field of software security. The method comprises the steps that a special annotation mark in a source code is scanned, a test code entry point is recognized, and metadata information is extracted; performing encryption processing on the metadata and generating a registry file with a digital signature; environment safety data are collected through four monitoring dimensions, and a comprehensive risk score is calculated; generating a grading fusing instruction according to the score; and finally executing the fusing operation of byte code replacement or thread sandbox isolation. According to the invention, accurate identification and real-time protection of the leakage risk of the test code are realized; through a multi-dimensional monitoring and hierarchical fusing mechanism, the system security is ensured, and the influence on the service performance is minimized; and byte code replacement and thread isolation technologies are adopted, so that security protection can be realized without restarting the application, and the availability and the operation and maintenance efficiency of the system are improved.

The invention provides a game resource optimization method and device based on a predictive algorithm and a storage medium. The method comprises the following steps: compiling a source code of a game voice tool into a bytecode file and generating an executable game voice tool main body; dividing the loading process of the non-core resources into a plurality of stages, and pre-loading the non-core resources through at least one background thread; generating a target resource list for a subsequent game scene by using a predictive algorithm; executing a loading operation on the target resource which is not loaded by utilizing a background thread, and executing a releasing operation on the loaded resource which is judged to be lower than a preset threshold value in the subsequent game scene by the predictive algorithm, wherein the use probability of the loaded resource is lower than the preset threshold value; a high execution priority is set for a voice communication module, and the loading priority of non-core resources and the task allocation order of background threads are dynamically adjusted according to the real-time condition of voice communication. According to the method and the device, memory resource utilization can be improved, CPU (Central Processing Unit) occupation is reduced, and game jamming caused by resource competition is reduced.

The invention discloses a JavaScript language security reinforcement method based on a virtual machine technology, and belongs to the field of JavaScript languages. The method comprises the following steps: firstly, building a test system comprising a compiler, an assembler, a virtual machine and a packer; then, a developer submits the JavaScript program or the function requirement to be tested to the test system; a test system constructs a to-be-tested program by using a Yarn environment, and a compiler compiles a JavaScript source code and analyzes and converts the JavaScript source code into an intermediate representation IR; the assembler converts the IR into byte codes, and converts the relative reference address into an absolute address by generating a character string table and a lookup table; and the generated byte code is optimized. The test system submits the optimized byte code to the virtual machine, the virtual machine runs a byte code program, and after execution is completed, the test system collects an execution result of the virtual machine and compares the execution result with an expected result; and finally generating a test report and delivering the test report to developers for confirmation. According to the method, the security of the JavaScript code is enhanced through a virtualization technology, and malicious access and analysis are prevented.

The invention discloses a link tracking monitoring method, system and device and a computer readable storage medium, and relates to the technical field of communication, the method tracks a link needing to be tracked through a preset link tracking model, unnecessary byte code injection, interception and excessive tracking data are prevented from being generated, and the link tracking monitoring efficiency is improved. The influence on a network, a CPU (Central Processing Unit), a memory and the like caused by transmission, analysis and storage of the tracking data is avoided, the relation among the invasion degree of the existing code, the link tracking granularity and the performance overhead is balanced, and the influence on the existing service performance and the concurrent processing capability is avoided; a byte code enhancement technology is adopted to enhance original service processing logic, enforcement coding and decoding byte codes are injected, execution calling information of a specified link (function / method) is intercepted, enhanced, recorded and sent, zero invasion and zero development are carried out on existing service codes, and tracking of the full-link calling process of an application layer data protocol HTTP / RPC and a transmission layer protocol UDP is achieved.

The invention provides a multi-player voice game performance optimization method and device based on dynamic resource management. The method comprises the following steps: acquiring a core source code of a game voice tool and pre-compiling the core source code to generate a byte code file; analyzing a target scene demand and pre-loading a related resource file; performing real-time acquisition and analysis on memory occupation and CPU load to obtain performance state data of the current system; based on the performance state data, when it is detected that memory occupation and / or CPU load exceed a preset threshold value, a pre-compiling mode and a resource loading strategy are automatically adjusted; when it is detected that the multi-person voice function is started, resources and byte codes needed by voice processing are placed in a high-priority queue, and cooperative scheduling is carried out on memory occupation and / or CPU loads. According to the method, the loading delay can be reduced, the frame rate can be improved, the communication delay can be reduced, and real-time voice processing and high-load requirements of games can be dynamically considered.

The invention discloses a real-time anti-fraud transaction intelligent analysis system and method based on multi-chain collaboration, and the system comprises a dynamic federated learning module which is used for dynamically loading and updating a global model during the operation of a JVM (Java Virtual Machine) by adopting a Java Agent bytecode enhancement technology; the multi-chain collaborative verification engine comprises an alliance chain and a private chain, the alliance chain is formed by taking a plurality of banks as organization nodes and is used for distributed evidence storage of transaction characteristics among financial institutions, and the private chain is maintained by a supervision mechanism and is used for auditing and compliance verification; and the real-time stream processing pipeline processes the transaction request in a stream processing mode to obtain feature data, and makes a decision based on the feature data and the global model output by the dynamic federation learning module. The intelligent risk control system which supports cross-mechanism collaboration, privacy protection, high throughput and low delay is constructed, and the problems that in the prior art, model updating is lagged, a verification mechanism is not transparent, and processing delay is high are solved.

The invention discloses an incremental code coverage rate acquisition device based on a Java bytecode dynamic instrumentation technology, and relates to the technical field of software testing and quality control. Comprising a code difference analysis module, a byte code instrumentation module, a coverage rate data acquisition module, a coverage rate data integration module, a coverage rate report generation module and a test trigger and threshold control module, and a syntax tree structure of incremental codes is generated based on a Java syntax analysis tool, so that line level analysis of code differences is realized. According to the method, incremental codes are accurately analyzed through Git and JavaParser, coverage rate data are collected through dynamic instrumentation, a unified report is generated in combination with path analysis, missing scenes are marked in a highlighted mode, and the test efficiency and the code quality control capacity are improved.

The invention relates to the technical field of mobile application continuous integration automation, and discloses a multi-channel APP automatic packaging system which comprises the steps that byte code files in a released mobile terminal APP installation package are acquired, and an occupied symbol space set is generated; generating an available confusion namespace by using set complementary operation; extracting method-level code change by using an abstract syntax tree difference algorithm, and generating a change method set; generating a patch special confusion rule for the change method set by using a namespace allocation algorithm; compiling and obfuscating the change method set by applying a patch special obfuscating rule to generate a safe obfuscating patch byte code; performing packaging and signature operation on the safe obfuscation patch byte code, and outputting a minimized obfuscation safe hot repair patch pack; according to the method, the technical problems that class definition conflicts or method calling errors occur after the hot repair patch is loaded, and the downloading success rate of a user is affected due to the overlarge size of the hot repair patch are solved.

The invention provides a game performance optimization method and device based on dynamic scheduling and a storage medium. The method comprises the following steps: dynamically adjusting a byte code compiling strategy based on operation data, and reducing the execution priority of a byte code compiling task when monitoring that a multi-person voice team function is started and a CPU load reaches a preset condition; performing dynamic scheduling on allocation of the CPU cores based on the operation data, allocating high-priority tasks to the CPU cores with loads lower than a preset load threshold for execution, and allocating other tasks to the remaining CPU cores; carrying out scheduling and intelligent cache management on the resource file according to the operation data; and when monitoring that the network bandwidth or the network delay reaches a preset condition, adjusting a multi-person voice data transmission strategy based on the operation data. According to the method and the device, dynamic scheduling can be performed according to the real-time state during game running, tasks and resources are flexibly allocated, CPU occupation is reduced, and game running lagging is avoided.

The invention provides a software supply chain risk component calling identification method, and belongs to the technical field of basic safety. The method comprises the following steps: loading components in a Java Web application, and dynamically capturing a loaded component list; storing the component list locally and sending the component list to an external intelligence system, acquiring risk component information, and generating a risk calling interface signature according to the risk component information; a preset instrumentation rule file is loaded based on the risk calling interface signature, and accurate monitoring of the risk interface is realized through dynamic method matching and byte code enhancement; screening risk interfaces triggered during operation according to cross comparison of static data and dynamic calling data, and marking high-risk components which must be repaired and risk components which can be postponed to be repaired; the risk report generation module generates repair suggestions and priority reports. According to the method, the accuracy of risk assessment is fundamentally improved, meanwhile, the unnecessary repair cost is remarkably reduced, and an efficient and innovative technical solution is provided for supply chain risk management.

The invention discloses a Flash animation media playing system and method based on WASM, belongs to the technical field of webpage playing, and aims to solve the technical problem of how to realize compatible playing of an original Flash file on the premise of not modifying the original Flash file so as to guarantee sustainable use of original educational resources. The analyzer module is used for analyzing the format content of the Flash file and sending the analyzed data to the ActionScript virtual machine and the rendering engine module; the ActionScript virtual machine is used for explaining and executing the ActionScript byte codes, interacting with the JavaScript environment of the browser through the API bridging module, and sending a rendering command to the rendering engine module; and the rendering engine module is used for interacting with a Javascript execution environment to complete display of a rendering result.

The invention belongs to the technical field of information security, and particularly relates to a reinforcing method and device for a swan application. The method comprises the steps of obtaining a to-be-reinforced swan gap application, wherein the swan gap application comprises at least one first byte code file; decompiling the first byte code file into an editable first file, and modifying and reinforcing the first file to generate a second file; and compiling the second file into a second byte code file, and generating the reinforced swan application based on the second byte code file. The invention provides an application reinforcement scheme which is available for a swan-gap system and has better performance.

The invention relates to the technical field of block chains, in particular to a smart contract vulnerability detection method and system based on a multi-modal large language model.The detection method comprises the steps that S1, the system receives source code input of a smart contract; s2, executing semantic branches and graph structure branches in parallel; executing semantic branch processing, calling an annotation agent, and generating an annotation from the source code of the smart contract; calling a vectorization agent, coding the annotation and the source code, and converting the annotation and the source code into a high-dimensional vector; executing graph structure branch processing, compiling a source code into a byte code by the system, and generating a control flow graph; the vectorization agent generates high-dimensional embedded representation of the nodes based on the control flow graph; and S3, integrating features extracted from the semantic branches and the graph structure branches through a multi-modal feature fusion strategy, and inputting the integrated features into a classifier to detect vulnerabilities. The method is based on a multi-modal large language model agent, and potential vulnerabilities in the smart contract are comprehensively analyzed by integrating high-level semantic information and low-level structured data.