202 results about "Android application" patented technology

The invention discloses an android container rendering optimization method based on cross-domain hard real-time Fen synchronization, which comprises the following steps: by taking a swan-mong system as a host and an android system as a container, creating a hash table, a synchronous thread and a shared memory corresponding to a GPU core when the host is started, acquiring VSync cycle registration callback, transmitting shared memory FD to the container, and finishing shared memory mapping and alignment by the container. Registering a GPU queue to complete callback; when the Android application is started, a container obtains a queue and a physical address of a rendering buffer area, creates a Fen and binds the Fen to the queue, after the queue is submitted, metadata is written into a shared memory to inform a host, after the host receives the metadata, nodes are created and stored in a hash table, and an overtime timer is registered; after the GPU completes the command queue, the container calls back an update state and a verification value to notify the host, and after the host is verified to be valid, the corresponding hash table is updated, the timer is reset, and asynchronous screen loading is triggered; and the host executes buffer area synthesis and submission of the display equipment to finish on-screen, so that the stability of the rendering frame rate is improved, and the reliability of cross-domain synchronization is ensured.

The invention discloses a container application on-screen method based on texture full-process optimization, which comprises the following steps: taking a swan-gap system as a host and an Android system as a container, distributing a plurality of first buffers by the host, screening out a first texture format by the container, writing original textures of the format generated by rendering into frame buffers, identifying a dirty area of the rendered textures, and displaying the original textures in the frame buffers; packaging the texture data of the region, storing the packaged texture data into a shared memory, transmitting a file descriptor FD to a host, binding an idle first buffer setting priority, a state, a generation timestamp and a texture data pointer at the same time, and obtaining the texture data by the host through the FD; the host establishes a fixed thread task pool, executes multiple tasks in parallel to obtain on-screen texture data, and then updates the state of the first buffer and a texture data pointer; and finally, the host queries the first buffer with the processed state, reads the texture data after sorting according to the priorities and the generation timestamps to finish on-screen, and resets the state of the first buffer to be idle, so that the on-screen delay is effectively reduced, and the actual frame rate of the Android application is improved.

The invention relates to a cooperative control system and method based on heterogeneous unmanned aerial vehicles. The control system comprises a ground station control system and a mobile terminal control system. The ground station control system is a desktop application supporting task issuing to a plurality of mobile terminals; the mobile terminal is an Android application and can directly control the flight of the single unmanned aerial vehicle through the unmanned aerial vehicle controller; the method comprises the following steps: establishing a relation among the ground station, the mobile terminal and the heterogeneous unmanned aerial vehicle to carry out image return. The heterogeneous unmanned aerial vehicle cooperative control system and method relate to technologies and systems in multiple aspects such as task analysis, communication protocols, data fusion, state monitoring and autonomous cooperation, effective cooperation among heterogeneous unmanned aerial vehicles is achieved through system design and application, and the application potential of the unmanned aerial vehicles in the military and civil fields is expanded.

The invention belongs to the technical field of information security, and relates to an Android malicious software detection method based on API semantic enhancement, and the method comprises the steps: obtaining a to-be-detected Android application; performing static analysis on the to-be-detected Android application, and constructing a function call graph of the to-be-detected Android application; optimizing the function call graph of the Android application; extracting a complete API context sequence of a corresponding function from the optimized function call graph by adopting a recursive algorithm; adopting Skpi-Gram to map the complete API context sequence into feature vectors, and adopting a clustering algorithm to divide the feature vectors with close distances into the same class; inputting the clustered feature vectors into a trained graph convolutional neural network model to obtain a detection result of the to-be-detected Android application; according to the method, the extracted function call graph nodes are optimized by adopting the graph convolutional neural network, so that information loss caused by feature structure conversion is avoided, and the efficiency of model training and the accuracy of a detection result are improved.

The invention provides an Android application task automation method based on a user interaction description diagram, and belongs to the technical field of automation. Comprising the steps that a first stage comprises user interaction description graph generation and aims at obtaining a user interaction description graph of an application; and outputting the user interaction description diagram of the application by taking the Android project as input. And the second stage comprises task execution path planning and adaptive interactive operation generation. According to the method, static program analysis is combined with the semantic reasoning ability of the LLM, the structured user interaction description graph is automatically constructed from the source code of the target application, the user interface elements, the interaction logic and the state jump relation are covered, and the problems of operation blindness and the like caused by lack of application prior knowledge before task execution of the LLM are solved. An initial operation instruction sequence can be generated in combination with user task requirements; through an adaptive instruction re-planning mechanism, state fault tolerance and path optimization in a task execution process are realized, and the task completion rate in a complex scene is remarkably improved.

The invention discloses a setting-related interface display defect positioning method and system in an Android application, and the method comprises the steps: storing a defect report through an initialized null set BUGS, and injecting a test Activity to obtain all UI pages; traversing each pair of UI components in each UI page, and comparing visual feature relationships of the UI components after default setting and system setting change, including color, alignment mode, distance and inclusion relationship consistency; if any inconsistency is detected, generating a defect report and adding the defect report to a BUGS set; and finally, returning a report set containing all detected style-related and semantic-related defects. According to the method, the UI page is obtained by injecting the test Activity, and the visual feature relationships of the components under different settings are traversed and compared, so that the automatic detection and report generation of the interface display defects related to the settings are realized.

The invention provides a reinforcement learning-based distributed Android application automatic test method, which is executed by a plurality of agents in parallel: a) an independent test stage: each agent interacts with a tested application within a preset round duration, and executes the following operations: generating a state representation according to a current interface structure; selecting and executing actions based on a reinforcement learning strategy, and recording state transition and reward values; maintaining a global state set to track states found by all agents; b) an experience aggregation stage: at the end of a preset round duration, aggregating learning experiences of all agents to generate a global strategy, the learning experiences at least comprising a Q table and an action execution frequency; c) a strategy synchronization stage: distributing a global strategy to all agents as an initial strategy of a next time period; and repeating the steps a)-c) until the test is ended. Through distributed architecture design, a state similarity driven reward function and a regular experience aggregation mechanism, efficient exploration and test case generation are realized.

The invention discloses an Android application notification synchronization system, method, device, medium and product, and relates to the technical field of computer operating systems, the system comprises an Android system and an OpenHarmony system; the android application issues a notification message to a first notification subsystem; the first notification subsystem sends the notification message to the first Android compatible subsystem; the first Android compatible subsystem sends the notification message to a second Android compatible subsystem; the second Android compatible subsystem sends the notification message to the shell application; the shell application analyzes the notification message to obtain a first notification message, and sends the first notification message to a second notification subsystem; the second notification subsystem sends the first notification message to a system user interface; the system user interface displays the first notification message, and the function that the notification of the Android application is normally published and displayed on the OpenHarmony system is achieved.

The invention discloses an Android Service plug-in implementation method, an Android Service plug-in implementation system, Android Service plug-in implementation equipment and a medium. The Android Service plug-in implementation method specifically comprises the following steps: deploying proxy service in a host application, creating a standard interface IServiceInterface, and fusing host and plug-in resources by rewriting a context loading method of Android Service; constructing a service life cycle prediction model through a federated learning framework based on multi-device service behavior data collected during proxy service operation; generating a dynamic scheduling strategy based on an output result of the service life cycle prediction model in combination with the equipment electric quantity, the network type and the CPU load; and based on a dynamic scheduling strategy, writing the plug-in metadata hash, the federated model fingerprint and the device state snapshot into a block chain smart contract, and verifying the integrity of the plug-in through a light node on the chain to obtain a block chain verification result. According to the method, the stability and the reliability of the Service plug-in are improved, and powerful support is provided for the hot update function of the Android application.

The invention discloses a multi-window display optimization method for android applications of a swan-Monte platform, which comprises the following steps: after an android container is started, creating a first shared memory containing a plurality of partitions on the swan side, distributing and binding a component ID when an android application component is started, configuring GLES resources, creating a double-buffering queue and a GLES context, and displaying the GLES resources in the double-buffering queue. A shared image resource handle is generated, a mapping table of a component ID, a window ID and a texture identifier is established, context and the component ID are verified during component rendering, a difference region is calculated and processed to generate first data and a checksum after pixel data are rendered, a data head and the first data are written into a shared memory partition, and a gap side is notified; after the gap side verification is passed, information is extracted to generate a texture identifier, a Surface buffer area is associated, and finally Android and gap window data are synthesized and submitted to display hardware to be displayed on a screen.

The invention provides a cabin integration method of whole vehicle self-adaption platform service based on SOA and a vehicle, and relates to the technical field of vehicle SOA service, the method comprises the following steps: deeply integrating functional components of a whole vehicle self-adaption platform into an Android operating system, and embedding a communication module into an Android hardware abstraction layer; the original biochemical deployment of the SOA service in the cabin domain is realized; meanwhile, an efficient and low-delay service calling interface is constructed by expanding a communication mechanism between Android native processes, so that the Android application can directly call the whole vehicle level SOA service, and the dependence of traditional cross-domain communication on a vehicle-mounted Ethernet and a central gateway is avoided; besides, processor core resources are dynamically allocated in combination with the function security level of the SOA service, so that the real-time performance and execution reliability of high-security-level tasks are guaranteed, and the overall resource utilization efficiency of the system is improved.

A method includes: When detecting preview requests for a plurality of cameras, a first device creates views and buffers that correspond to the plurality of cameras in a camera Android application package APK, delivers the buffers corresponding to the views to a framework FWK layer, and obtains camera data streams corresponding to the plurality of cameras from a hardware abstraction layer HAL through the FWK layer; and the first device renders the plurality of camera data streams to the corresponding buffers respectively through a layer transferring module of the FWK layer. The camera data streams of the plurality of cameras are carried and displayed by using the plurality of views, and the plurality of camera data streams are rendered to the buffers of the corresponding views through the layer transferring module, so as to implement quick preview.

The invention discloses an Android malicious software dynamic detection method fusing API sequence semantics and graph structure features. The method comprises the following steps that an Android application program runs in a simulator environment, a runtime log is monitored and collected, an API method name sequence is extracted from the log, and calling sequence semantic information is reserved; constructing a global API dependency relationship graph based on a point-by-point mutual information PMI theory; generating joint feature representation by combining semantic embedding and graph structure embedding, including semantic embedding, graph structure embedding and joint embedding; inputting the fusion embedding into a pre-training BERT encoder, extracting features through a self-attention mechanism, and outputting a detection result through a classifier by using [CLS] flag bit vectors; according to the method, the detection performance is remarkably improved, and the method has high practical application value.

Systems and methods are disclosed to develop and use a tool to enable an application package to be instrumented with automatic real user monitoring (RUM) without accessing the original source code. A package, such as Android application bundle (AAB) or Android package kit (APK), is imported and decoded and a generated source code file and / or manifest is obtained. Instrumentation is then added at a location corresponding to a code signature in the generated source code file (e.g., an operation to be instrumented before and / or after the operation). The generated source code file is then compiled and packaged into an APK and / or AAB file. The resulting application package is available for downloading, installation, and use on user devices with the instrumentation having been automatically added and without access to the original source code.

The invention relates to an intelligent depression detection system based on physiological behavior multi-modal information. The system comprises an Android application program and a wearable device capable of collecting electrocardio, electroencephalogram and PPG signals (photoplethysmography), and voice and video signals are collected through a camera and a microphone. The system is provided with a user information input module, a sensor detection module, a resting state signal acquisition module, a picture video emotion induction experiment module, a multi-mode signal fusion analysis module, an evaluation report generation module and other functional modules. The system combines resting state signals and induced state experiment data, through intelligent analysis and fusion of physiological and behavioral two-dimensional signals, depression identification and detection can be carried out based on comprehensive characteristics of the five signals, the accuracy and reliability of depression detection are effectively improved, and therefore the psychological state of a user is evaluated more comprehensively. The system has the characteristics of noninvasiveness, convenience, real-time acquisition, multi-mode fusion and the like, and can provide a powerful auxiliary tool for clinical depression diagnosis.

The invention provides a multi-application camera sharing method and device for a Linux-compatible Android system, and the method comprises the steps: transplanting a virtual video device driver to an environment with the Linux-compatible Android system, creating a camera server program at a Linux system side, creating a Linux side system service configuration file, carrying out the self-starting along with the startup, transforming an Android Framework layer camera frame, and carrying out the self-starting of the camera frame. A plurality of Android applications can call the same camera device at the same time; and transforming an Android side camera hal layer, so that the Android side camera hal layer can read camera data from camera virtual equipment and send the camera data to an application layer. According to the method and the device, a plurality of Linux applications and a plurality of Android applications can share the same camera, so that the user experience is greatly improved.

The present disclosure provides a method, apparatus, and device for operating an Android application in a Linux system, relating to the field of computer technologies. The method includes: detecting a request to operate an Android application in the Linux system, where the Android system service has been started in the Linux system; obtaining the file package information of the Android application according to the request; and sending the file package information to the Android system service to trigger the Android system service to perform an operation on the Android application according to the file package information. The technical solution of the present disclosure can realize operating an Android application in the Linux system without the need for the dual systems of Linux and Android to run synchronously, without cross-system data interaction, saving the memory consumption of the Linux system, improving the running performance, and enhancing the efficiency of operating the Android application.

The present invention discloses an Android application vulnerability detection method and system based on multi-agent collaboration, which relates to the field of cyberspace security. The method comprises: S1, vulnerability information sorting step; S2, APK decompression and decompilation step, S3, APK intelligent scanning step; S4, vulnerability mining step; S5, vulnerability verification step. The present invention discloses an Android application vulnerability detection method and system based on multi-agent collaboration, which can effectively identify and verify security vulnerabilities in Android applications, and can more accurately verify vulnerabilities by using the semantic analysis ability of the agent, reduce the false alarm rate and missed alarm rate of vulnerability scanning, and improve the reliability of vulnerability detection.

The invention discloses an Android cross-process stain detection method based on transaction graph reconstruction, and relates to the technical field of mobile terminal information security, and the method comprises the following steps: a deployment monitoring module intercepts Binder communication between Android applications; adding a stain mark for the sensitive data source, and attaching the mark during inter-process transmission; recording information of communication transactions between each process, constructing a transaction graph, and restoring paths for transmitting sensitive data between different processes in the graph; performing traversal analysis on the transaction graph, and searching for a path of spreading the data carrying the taint marks from the source application to the target application; and if the target application does not authorize to acquire the sensitive data or send the sensitive data out of the equipment, judging that the sensitive data is leaked and outputting an alarm. According to the method, flowing of privacy data can be tracked across application boundaries, automatic detection of cross-process leakage of user sensitive information caused by application collusion is achieved, and the accuracy and comprehensiveness of privacy leakage detection of the Android platform are remarkably improved.

The invention provides a method and a device for realizing log file output / far-end output of an Android log and electronic equipment, in the method, a service program LogColletor can convert the Android log into an AP log and further write the AP log into an AUTOSAR AP log module, and finally, the AP log is stored as a log file or sent to a far end through a network by virtue of the function of the AUTOSAR AP log module, so that the Android log can be output or output from the far end through the AUTOSAR AP log module. According to the method, log file output / remote output of the Android log can be realized through a service program LogColletor transformed by an AUTOSAR AP log module, a developer of the Android application does not need to perform secondary development, a technical threshold does not exist, the process is non-perceived for the developer of the Android application, the user experience is good, and in addition, the method can be applied to the development of the Android application. According to the method, the Android Log and the AP log are stored or sent to the far end in the form of the AP log, the data format is uniform, the method is convenient to use, a user can check and analyze the Android Log and the AP log in a unified mode and check vehicle faults, the log analysis efficiency is greatly improved, and the overall vehicle problem checking efficiency is improved.

The invention discloses an APK package volume optimization method and device, a storage medium and electronic equipment, and relates to the technical field of Android application development.The method comprises the steps that unpacking processing is conducted on different versions of APKs of a target application, and package volume parameters corresponding to the different versions of APKs are obtained; detecting the packet volume parameters among different versions of APK packets by adopting detection rules corresponding to different detection indexes to obtain to-be-optimized packet volume parameters corresponding to different detection indexes; performing optimization priority ranking on each packet volume parameter to be optimized to obtain a packet volume parameter queue to be optimized; and optimizing each to-be-optimized packet volume parameter one by one by adopting a parameter optimization mode corresponding to each to-be-optimized packet volume parameter in the to-be-optimized packet volume parameter queue to obtain an APK packet volume optimization result. According to the method, the APK package volume optimization efficiency and accuracy can be improved.

The invention provides an Android APK reinforcement method and system oriented to high-strength code protection, and belongs to the technical field of computer software, and the method comprises the steps: obtaining a resource call chain during the operation of an Android application through a reflection heat loading technology, and generating a dynamic encryption key stream; performing segmented encryption on the key resource according to the dynamic encryption key stream to obtain encrypted resource data; analyzing a bottom-layer instruction sequence of the encrypted resource data by adopting an instruction-level semantic analysis technology, and generating a semantic conversion template; performing dynamic re-signature on the package body according to the verification result to obtain a re-signed application package body; monitoring the re-signed application package body through a runtime reverse protection mechanism, and obtaining an abnormal behavior log; if the dynamic injection attack is detected in the abnormal behavior log, protection logic encryption is activated, and an irreversible protection module is generated; and updating an encryption strategy of the data stream during operation according to the irreversible protection module to obtain an optimized resource protection scheme. According to the method and the device, the resource security during Android application running is remarkably improved.

The application discloses a kind of API sequence semantics and graph structure feature fusion Android malware dynamic detection method, including the following steps: running Android application in simulator environment, monitoring and collecting runtime log, extracting API method name sequence from log, retaining call order semantic information;Based on point mutual information PMI theory, global API dependency graph is constructed;Combined with semantic embedding and graph structure embedding, joint feature representation is generated, including semantic embedding, graph structure embedding and joint embedding;The fusion embedding is input into pre-training BERT encoder, and the feature is extracted through self-attention mechanism, and the detection result is output by the classifier with [CLS] flag bit vector;The application significantly improves the detection performance, and has strong practical application value.

The invention relates to an external display screen driving method and system based on an Android system, an external display screen is connected with Android equipment through a low-speed serial interface, and the method comprises the steps that S1, a Native layer initialization function is called through a JNI interface on an Android application layer; s2, an LVGL graphic library is loaded on a Native layer; s3, registering and adapting external display screen hardware of the low-speed serial interface through a display driving interface of the LVGL graphics library; s4, executing a color space conversion algorithm on the Native layer, and converting color graphic data output by the LVGL graphic library into color format data suitable for the target external display screen; and S5, transmitting the converted display data to an external display screen through a device driving interface of the Linux kernel. According to the method, the lightweight LVGL graphics library is integrated into the Android application through the JNI technology, and the display screen connected through the low-speed serial interface is directly driven in the user space, so that the efficient and flexible display driving is realized under the condition that the source code of the Android system is not modified, and the multi-screen different display function is supported.

The present invention discloses a method for identifying and classifying Android shelled malicious applications, comprising the following steps: (1) constructing a fingerprint feature library of Android shelled malicious application shells; (2) constructing a fingerprint classification mapping library of Android shelled malicious application shells; (3) collecting different categories of unpacking tools for Android shelled malicious applications; (4) collecting an Android malicious application data set, unpacking it using an unpacking tool, and then extracting features and matching them using rules to identify the shelled Android malicious applications; (5) using the fingerprint classification mapping library constructed in (2) and processing the results in (4) to classify the shelled Android malicious applications; and (6) using the unpacking tools collected in (3) and processing the results in (5) to provide a suitable unpacking solution for the Android shelled malicious applications. The present invention can be used to effectively realize the identification and classification of Android shelled malicious applications.

Embodiments of the present specification provide a method, device and storage medium for detecting invocation of a trusted execution environment (TEE) by an Android application. The method comprises: obtaining a data packet of a software to be detected; obtaining an identifiable file from the data packet based on a reverse engineering algorithm; identifying whether the software to be detected invokes a TEE function based on a preset TEE function vector set and the identifiable file, the TEE function vector set containing vectors representing general functions / interfaces, indirect invocation functions / interfaces or specific TEE functions / interfaces; obtaining a function vector of the invoked TEE function, text data and logical structure data of a module in the software to be detected that invokes the TEE function from the identifiable file when the software to be detected invokes the TEE function; and determining a functional module to which the invoked TEE function belongs based on the function vector of the invoked TEE function, the text data and the logical structure data. The technical solution provided by the present application solves the problem of insufficient precision in detecting TEE in the prior art.

The present invention discloses a third-party countersignature method based on a V2 or V3 signature mechanism. In an Android application signature data block, a V2 or V3 signature data block is found, an Android native signer data block sequence is found, an additional attribute data block is found in each signer data block, an ID is inserted into the additional attribute data block, and the value of the ID inserted into the additional attribute data block is the countersignature data; in the V2 signature data block, the ID is not 0x7109871a; in the V3 signature data block, the ID is not 0x7109871a or 0xf05368c0 or 0x3ba06f8c. The present invention also discloses a third-party countersignature verification method based on a V2 or V3 signature mechanism. The present invention is applicable to a third-party countersignature method under an Android system mobile application V2 or V3 signature mechanism, and realizes the signature tracing of various countersignature roles (application developers, testing agencies, application stores, etc.) under an Android system mobile application V2 or V3 signature mechanism, while not changing the original Android V2 or V3 signature verification mechanism.

The application discloses an Android application logic bomb semantic detection method and device based on LLM, and belongs to the technical field of intelligent terminal security; the device comprises an APK reverse analysis graph extraction module, a sensitive API knowledge base construction and suspicious CFG generation module, a cross-function semantic correlation and structured representation module, an LLM semantic reverse reasoning identification and explainability analysis module; through converting a target Android APK into an LLM understandable semantic expression form, LLM understandable APK program semantic information is generated; a logic bomb sensitive API knowledge base is constructed and a suspicious CFG is generated; cross-function call context semantic information of the suspicious CFG is constructed and is subjected to serialization and structured processing; a reverse reasoning identification logic bomb based on factual evidence semantic features and an evidence report are generated; the application can convert an APK file into an LLM easily understandable semantic expression form, and then effectively identify a logic bomb hidden in an intelligent terminal application, and has good explainability.

Disclosed herein is an apparatus for automatically removing anti-dynamic analysis code from an Android application. The apparatus includes an execution control module for performing control to install and execute an application in multiple devices based on an Android Package Kit (APK) file, an execution record reception module for receiving an execution record in which the content of code executed by the application is converted into a string format from the device, and an execution evaluation instrumentation module for searching for a branch point of anti-dynamic analysis code based on the execution record in a string format.

The invention relates to the technical field of computer software, in particular to a method for automatically generating an Android system Binder communication SDK (Software Development Kit), which comprises the following steps: defining an AIDL interface source file and compiling to generate a JAR packet; defining an interface configuration JSON file; executing a pre-generation program, and creating an annotation mark Java file; integrating the annotation processor and compiling to generate a final SDK file, wherein the generation process of the final SDK file comprises the following steps: registering and triggering the annotation processor, analyzing the annotation, analyzing an AIDL interface method, constructing a code model and generating the SDK file; and using the generated SDK file. The technical problems that in existing Android application development, due to the fact that Binder communication bottom layer template codes are manually written, the development efficiency is low, the codes are redundant and prone to errors, and unified maintenance is difficult are solved, and normalization and consistency of communication codes among multiple services are fundamentally guaranteed.