280 results about "Open source" patented technology

The invention discloses a Linux container-based Android and open source gap dual-system collaborative operation method, relates to the technical field of operation system collaboration, and aims to reduce resource occupation and improve collaboration and switching coherence, and the method comprises the following steps: step 1, by taking an Android as a host, creating a container isolation running domain, starting a namespace and managing resources by a control group; the method comprises the following steps: presetting a binder virtualization and three-state template; 2, deploying an open source gap in a container, mounting a shared directory in a directory binding manner, configuring bridging or address translation, and establishing copy-on-write and snapshot identifiers; and step 3, establishing a cross-system binder channel, and setting a service registration agent in a service manager and completing mapping of a handle and an authority domain by combining a shared memory and a local socket. And step 4, executing system switching without restarting, enabling one foreground and the other background through a foreground interface and continuous quota assignment, freezing a background session, limiting the speed of background heartbeat, and returning according to a snapshot when an exception occurs.

The invention provides a shield tunneling parameter intelligent optimization method and system based on an AI big language model, and relates to the technical field of tunnel construction optimization. Comprising the following steps: training an open source large model to obtain a preliminary shield tunnel construction industry large model; an upstream task and a downstream task which are relatively independent are set, and the upstream task comprises a tunneling speed prediction module, a tool wear prediction module, a ground surface settlement prediction module and a tunneling attitude prediction module; a downstream task combines an RAG technology and an NSGA-III multi-objective optimization framework, four prediction modules and an energy consumption calculation formula serve as objective functions, the value range of constraint conditions is determined, a tunneling parameter optimization module is established, a professional shield tunnel construction industry large model is formed, and scientific and intelligent decision making of tunneling parameters is achieved. According to the method, information in multiple aspects can be comprehensively considered during decision making, the reasoning process is output, and scientificity, comprehensiveness and reliability of decision making are ensured.

The invention discloses an open source software supply chain security intelligent monitoring and risk assessment method, relates to the technical field of software supply chain security, and solves the problem that only existence of indirect dependence can be identified generally in the prior art, but whether a vulnerability code can be called on an actual execution path cannot be accurately judged. According to the method, through dependence locking and Hash fingerprint embedding during construction, cryptographic-level accurate traceability of a component version is realized, and version ambiguity is thoroughly eliminated; in combination with deep interception of a JVM probe for method calling and class loading events during operation, a loading source and a call stack context of each class in a real execution path can be captured, bidirectional association mapping is performed on dynamic behavior data and a static dependency tree, and whether a vulnerability component is located on an executable call chain or not is accurately identified. Compared with the defect that coarse-grained warning is carried out only through version matching in a traditional tool, the method has the advantage that by means of dynamic-static data fusion, it is avoided that a large number of unavailable indirect dependency vulnerabilities are misjudged to be high in risk.

The invention discloses a large and small model collaborative robot autonomous assembly method and system, and belongs to the field of advanced manufacturing technology intellectualization. The problems that traditional robot assembly depends on manual programming, adaptability is poor, and an algorithm cannot be optimized autonomously are solved. The method comprises the following steps: receiving an assembly project request submitted by a user in a natural language; the request is decoupled into a structured action primitive through an arrangement agent, and tasks are allocated; an algorithm design agent retrieves and adapts an algorithm from an open source library based on the action primitive, and completes training in a sandbox environment; the verification agent is responsible for automatic data acquisition and labeling, and carrying out overall performance test and iterative optimization on an integrated algorithm in a simulation environment; and finally generating an executable field control script. According to the method, the problems of algorithm autonomous design, simulation verification and closed-loop optimization when the robot faces a complex assembly task are solved, the development threshold and the deployment risk are reduced, and the intelligent level and the flexible adaptive capacity of an assembly system are remarkably improved.

The invention discloses a method and a device for generating a software vulnerability analysis report, and relates to the field of information security. The method comprises the following steps: acquiring auditing information of software vulnerabilities; a code feature matching rule for the software vulnerability is generated according to the auditing information through the large language model, and the code feature matching rule is used for matching a code calling mode related to the software vulnerability in the target software project; constructing a calling graph of the target software project; according to the code feature matching rule and the call graph, the correlation degree between each code snippet of the target software project and the software vulnerability is detected, and the correlation degree is used for evaluating the risk level of each code snippet of the target software project; and generating a software vulnerability analysis report of the target software project according to the association degree between each code snippet of the target software project and the software vulnerability. The technical problem that in the prior art, an open source software vulnerability detection tool cannot accurately evaluate the real influence of vulnerabilities in specific project contexts is solved.

The invention relates to a security event automatic handling method based on a large model, and belongs to the technical field of network security. The method comprises the steps of performing vectorization processing on collected historical security event data based on an embedded model, and constructing a security event processing knowledge base and an input enhancement knowledge base; finely adjusting the open source security field large model of the Transform architecture, dynamically updating the security event handling knowledge base and regularly updating the input enhancement knowledge base; carrying out vectorization and similarity matching on the input security event data to obtain matching information; matching information is input into the fine-tuned large model to generate a disposal scheme; and manually intervening a disposal scheme, linking the existing safety equipment to execute event disposal, evaluating a disposal result, and feeding back the disposal result to a safety event disposal knowledge base to realize continuous optimization. According to the method, the response speed and the disposal accuracy of the security event can be improved, the adaptability to novel and unknown threats is enhanced, and continuous optimization is realized.

The invention provides an attribute error binding attack and evaluation method for an identity preserving model, which comprises the following steps of: acquiring an open source unadapted content data set which comprises a plurality of cue words, labeling the cue words along four harmful dimensions, decomposing the cue words into three semantic components, constructing a sensitive word data set based on the plurality of cue words subjected to labeling and component decomposition; sensitive words are extracted to serve as input cue words, candidate cue words are generated by selecting an error binding strategy through an LLM model, and effective cue words are integrated into an error binding instruction evaluation set; obtaining an identity reference image, inputting the identity reference image into a diffusion model of the identity maintenance model, and generating a generated image which maintains character identity features and accords with cue word description; and performing attribute binding security evaluation on the generated image to obtain an attribute binding security score. The technical problem that the attack risk based on'attribute wrong binding 'cannot be effectively evaluated in the prior art is solved.

Techniques are disclosed for the implementation of machine learning model training utilities to generate models for advanced driving assistance system (ADAS), driving assistance, and / or automated vehicle (AV) systems. The techniques described herein may be implemented in conjunction with the utilization of open source and cloud-based machine learning training utilities to generate machine learning trained models. One example of such an open source solution includes TensorFlow, which is a free and open-source software library for dataflow and differentiable programming across a range of tasks. TensorFlow may be used in conjunction with many different types of machine learning utilities, such as Amazon's cloud-based SageMaker utility for instance, which is a fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale.

The invention discloses a code repository understanding enhancement method based on Monte Carlo tree search-driven agent reinforcement learning, which comprises the following steps: (1) collecting open source code repository data, preprocessing and filtering, and designing five special code repository exploration tools; (2) constructing a code repository question and answer agent based on the designed code repository exploration tool, and realizing a multi-round thinking-action-observation interaction mode; (3) using a Monte Carlo tree search algorithm to guide the intelligent agent to generate diversified exploration tracks in the code warehouse data, and calculating track rewards through process rewards and correctness rewards; (4) performing reinforcement learning training on the intelligent agent by adopting a GRPO algorithm to realize cold start learning; and (5) in the application process, inputting the question into the trained agent, and finding out codes or text fragments related to question answering in the warehouse. According to the method, the performance of the code warehouse question and answer task is improved, and the training efficiency is improved compared with general agent intensified training.

The invention discloses an open source environment software hidden vulnerability patch identification method, which is based on a multi-stage architecture and collaborative relationship modeling, and provides a new patch group identification scheme: firstly, obtaining candidate code submission from an open source warehouse, extracting correlation characteristics of vulnerabilities and candidate code submission, including rule-based characteristics and semantic characteristics, calculating a correlation score and screening high-correlation submission; pairwise pairing the high-correlation submissions, and fusing multi-dimensional features to predict a cooperative relationship between the submissions; and finally, constructing an undirected graph based on the correlation score, dividing a maximum connected sub-graph, fusing the features in the group through maximum pooling, calculating the correlation with the vulnerability, and outputting an optimal patch group. Meanwhile, an existing patch identification technology based on sorting learning is combined, an enhancement method based on a submission cooperative relation is provided, ranking logic submitted by candidate codes is updated through internal association between code submission and by means of correlation between group vectors and vulnerabilities, and the identification precision in a multi-patch scene is improved.

The invention discloses an industrial special system building method based on large model and agent collaborative optimization, which comprises two core steps of industrial large model generation and agent collaborative optimization. The method specifically comprises the following steps: S1, generation of an industry large model: completing construction of an industry adaptation model through a data set generation module, a model fine tuning module, a model format conversion and quantification module and a model reconstruction and loading module in sequence; and S11, the data set generation module adopts an open source general large model as an initial semantic generation engine, and the method constructs a full-link system covering automatic generation of a data set, efficient fine tuning of parameters, model format conversion and quantization, model reconstruction and rapid loading, and agent construction and collaborative optimization control. And rapid injection of industry knowledge and efficient migration of model capability are realized.

The invention discloses an open source component vulnerability availability judgment method and system based on dynamic taint analysis and related equipment.The method comprises the steps that when the system receives an external request or an input event, taint identifiers are automatically distributed to taint sources and marked as potential controllable sources; then, dynamically monitoring an application system through an instrumentation technology in a system operation process, and tracking a propagation path of the marked taint variable in a function calling process; and finally, according to the calling characteristics of the known vulnerability function, judging whether the taint variable is transmitted into the vulnerability point or not, and generating a vulnerability availability analysis result. According to the scheme, whether the vulnerability function is triggered by the external controllable input or not is identified by tracking the propagation path of the external input in the program in real time, so that whether the vulnerability can be utilized or not is accurately judged, and the vulnerability detection accuracy and practicability are improved.

The application provides an open source compliance efficient scanning method and system for an operating system, belongs to the field of information technology, splits open source compliance scanning into a plurality of scanning items, realizes configurable differentiated scanning, judges a main task type after triggering a scanning task, obtains a scanning object according to the main task type, and reads a scanning template corresponding to the main task type, extracts metadata information of the scanning object, generates a uniform resource locator PURL, creates a subtask for the scanning item by using a distributed task scheduling framework, performs distributed subtask distribution based on execution cost calculation, and manages the scheduling and execution of the subtask. The application meets strict requirements for open source compliance in the operating system development, maintenance and supply chain management processes.

Computer-implemented systems and methods provision a virtual machine sandbox for evaluating software. Firewall means are provisioned for a cloud network to permit access to an internet site from which source code is downloadable. A client computer device, via virtualization, controls a virtual machine. The client computer device is on an on-premises network that is different from, and in communication with, the cloud network. The virtual machine is controlled to: (a) download to the virtual machine, via the firewall means, the source code from the internet site; and (b) execute the source code for evaluation of the source code. The virtual machine is deleted after a predetermined time period. The source code is prohibited, after provisioning the virtual machine and through deletion of it, from being downloaded from the virtual machine to computer devices on the on-premises network.

The application relates to the computer technology field, in particular to a processing method and device of an open source component, electronic equipment and a storage medium. The method comprises the following steps: receiving an open source project to be processed; the open source project comprises a plurality of open source components; core developer determination processing is performed on the plurality of open source components, and a core developer corresponding to each open source component is determined; based on a preset webpage ranking Pagerank algorithm and the core developer corresponding to each open source component, analysis component centrality determination processing is performed on each open source component, and a target core open source component is obtained; the analysis component centrality determination processing is used for comprehensively scoring the core developer corresponding to the open source component and a dependency relationship, and the target core open source component meeting a condition in comprehensive scoring is screened out. In this way, through refined analysis processing on the core developer in each open source component and the dependency relationship, the target core open source component of the open source project can be accurately determined.

The invention discloses a version identification method and system for binary software, and belongs to the technical field of computer program detection. The method comprises the following steps: carrying out reverse analysis on a binary file, and extracting a character string and a constant serving as a function return value; performing layered filtering on the character string and the constant to screen out candidate version semantic features possibly containing version semantic information, and extracting a context environment of the candidate version semantic features in a binary file; performing semantic enhancement on the candidate version semantic features in combination with a context environment of the candidate version semantic features in a binary file; and performing version identification on the binary file according to the character string and the enhanced semantic features of the candidate versions to obtain a version identification result of the binary file. According to the method, the identification problem of the binary software multiplexing open source software version can be effectively solved, and the identification accuracy and the recall rate are improved.

The application provides an agent-based security alarm noise reduction and automatic disposal method, belonging to the technical field of network security. The method comprises the following steps: collecting and preprocessing security alarm data, constructing a noise reduction rule library, a noise reduction knowledge base and an alarm disposal knowledge base; using an open source large model, the noise reduction knowledge base and knowledge distillation technology to fine-tune a noise reduction small model, using the alarm disposal knowledge base to fine-tune a script generation large model based on a general reasoning large model; using the noise reduction rule library and the noise reduction small model to perform two-stage noise reduction on the security alarm to obtain effective alarms; generating corresponding disposal scripts by using the script generation large model; creating a task allocation agent and a disposal agent; after artificial judgment of the feasibility of the script, the task allocation agent delivers the script to the corresponding disposal agent for execution, and the similarity and success rate of historical cases are fused to assist in determining the subsequent disposal mode. The application effectively improves the efficiency and accuracy of security alarm processing.

The application relates to a basic input / output system customization method and device, and the method comprises the following steps: based on an open source computer operating system kernel and a basic input / output system shell environment, generating a flash read / write tool associated with a flash EPROM; based on the flash read / write tool, writing basic input / output system customization information into the flash EPROM; obtaining the basic input / output system customization information of the flash EPROM, and realizing basic input / output system customization based on the basic input / output system customization information. The method can realize the requirement of basic input / output system customization, improve the compatibility of basic input / output system code, effectively improve production efficiency, simplify operation process, and optimize the production mode of customized products.

The invention discloses an open source platform task matching method based on a developer behavior map and double-layer filtering, and the method comprises the following steps: S1, dividing the behavior characteristics of a developer into three dimensions, and obtaining a developer behavior characteristic data set; s2, identifying and screening developers which do not meet the basic requirements; s3, constructing a lightweight knowledge graph Gdevtask comprising developer nodes, task nodes and associated edges of the developer nodes, the task nodes and the associated edges of the developer nodes and the task nodes in a manner of combining a relational database with graph storage; s4, task demand texts Textreq of the historical open source tasks and the open source tasks to be matched are obtained, demand disassembly is carried out on the open source tasks to be matched to obtain a plurality of sub-tasks, and corresponding vectorization expressions are generated; s5, adopting a double-layer filtering strategy to construct a primary matching layer, and screening to obtain a primary candidate developer set; and constructing a fine screening scoring layer to obtain a recommendation result list.

The application provides an open source component vulnerability repair method and device, wherein the method comprises: analyzing a target software by using a software component analysis tool to obtain component information and dependency relationships of all open source components; obtaining global influence of each open source component based on the dependency relationships of all open source components, searching an open source component knowledge base based on the component information of all open source components, and determining at least one open source component with a vulnerability; sorting the at least one open source component with a vulnerability according to the respective global influence, and then performing a vulnerability repair operation in sequence according to the sorting result, including searching the open source component knowledge base based on the component information of the open source component with a vulnerability, obtaining the target open source component and its dependent components, and repairing the vulnerabilities of the open source component and its dependent components. Thus, the automatic recommendation of the open source component vulnerability repair scheme can be realized, the vulnerability repair efficiency is improved, and the system compatibility risk is reduced.

The application relates to the technical field of artificial intelligence, and discloses an interaction method and an interaction device for shopping guide information and an electronic device. The interaction method is applied to an electronic device provided with a digital person, the electronic device is locally deployed with an open source large model and a brand exclusive knowledge base, and the interaction method comprises the following steps: receiving interaction request information input by a user; analyzing the interaction request information through the open source large model to generate a user demand label; matching target product information conforming to the user demand label in the brand exclusive knowledge base, and generating a product recommendation scheme according to the target product information; and controlling the digital person to output the product recommendation scheme. The application can improve the accuracy and reliability of the interaction of shopping guide information.

This invention discloses a method for aligning fields based on structured parsing of overseas open-source information, relating to the field of data fusion and parsing. The method includes: acquiring raw data packets from overseas open-source platforms; performing structured parsing and field extraction on the raw data packets to generate a candidate field set; performing semantic recognition and field mapping on the fields in the candidate field set based on a dynamic cognitive network to generate a field mapping decision result; resolving and correcting the consistency of conflicting field values ​​mapped to the same standard field based on the field mapping decision result to obtain an aligned field set; and organizing the aligned field set into a unified structured record and outputting it according to the standard field model. This method achieves intelligent mapping and conflict resolution of cross-platform fields through an evolvable semantic network, possessing the ability to adaptively learn unknown fields, achieve deep semantic understanding, and output interpretable decisions, significantly improving the intelligence level and accuracy of multi-source information fusion.

The invention is suitable for the technical field of data processing, and provides an open-source building data cleaning method based on road data and conflict degree quantization, and the method comprises the steps: obtaining OSM road data and open-source building data of a research region; the OSM road data comprises a plurality of road lines, and the open source building data comprises a plurality of building surfaces; for each building surface, judging whether the building surface has a gland conflict based on the OSM road data, if yes, determining a conflict type of the gland conflict, and calculating a conflict distance of the building surface based on the conflict type; and cleaning the open source building data according to the calculated conflict distance. The reliability of open source building data can be improved.

The application discloses a kind of kubernetes cluster's Pod vertical capacity expansion method and device, it is related to cloud computing technical field, wherein the method comprises: when listening to Pod needs vertical capacity expansion, the first resource quantity and the second resource quantity of the pod to be expanded are obtained;First resource quantity is existing resource quantity, and second resource quantity is required resource quantity;Create the placeholder pod corresponding to each pod to be expanded;The resource difference value of the first resource quantity and the second resource quantity of each pod to be expanded is calculated;For each placeholder pod, the resource quantity corresponding to resource difference value is applied;In the case where the resource quantity corresponding to resource difference value is successfully applied for each placeholder pod corresponding to each pod to be expanded, according to the resource quantity applied for each placeholder pod corresponding to each pod to be expanded, the first resource quantity of each pod to be expanded is updated.The application can realize vertical capacity expansion without affecting business continuity, and is compatible with open source K8S.

The invention relates to the technical field of software security governance, in particular to an open source component governance method and system based on multi-dimensional measurement and feedback optimization, and the method comprises the steps: collecting multi-source heterogeneous data of an open source component, carrying out the feature extraction, and constructing a basic measurement matrix containing security, compliance, efficiency and collaborative dimensions; respectively calculating a security dimension index and a compliance dimension index which represent a risk defense boundary, and an efficiency dimension index and a cooperation dimension index which represent business delivery kinetic energy, and generating a multi-dimensional efficiency state vector; mapping to a governance efficiency evaluation space, and generating an efficiency deviation characteristic value by calculating the coupling collaboration degree and restriction loss among the dimension indexes; and reversely deducing the adjustment gradient of the control strategy parameter to generate a dynamic correction instruction for the strategy execution component, issuing the dynamic correction instruction to the strategy execution component to update the control rule in real time, and executing a treatment operation on the open source component. According to the method, the treatment effect of the software can be effectively quantified, and the treatment strategy is guided to carry out targeted adjustment and continuous optimization.

The invention discloses a code generation method and device, equipment, a medium and a program product in the technical field of computers. The code generation demand and the component calling information are input into the code generation model, the code generation model can call the target component corresponding to the component calling information according to the code generation demand, the corresponding target code is generated, and therefore the correctness and accuracy of the calling information of the target component in the target code can be guaranteed. The scheme also detects whether the calling permission of the target component in the target code exceeds the limit or not under the condition that the target component is determined to be a non-open source component; if it is confirmed that the calling permission does not exceed the limit, the target code is stored, and therefore the correctness and accuracy of the component calling information are guaranteed through double means, the generated target code can meet the actual code generation requirement, and the code generation efficiency and quality are also improved.

The invention discloses an open source big data system software reliability model with fault removal efficiency obeying Weibull distribution, and belongs to the technical field of software reliability analysis. Performance fitting and prediction experiments are carried out through eight fault data sets and nine software reliability models, 95% confidence interval analysis is carried out, and results show that the model provided by the invention has better fault fitting and fault prediction performance than other models. The model provided by the invention can effectively and accurately evaluate the reliability of the open source big data system software, and has certain guiding significance for actual software development and testing.

The invention provides a crowd simulation and spatial layout optimization method and system based on an open source engine and related equipment. The method comprises the following steps: receiving user input in an interactive interface constructed by a three-dimensional engine, creating and editing three-dimensional scene data, and mapping the three-dimensional scene data into a scene object set with an identification attribute; receiving crowd behavior parameters set by a user based on the scene object set, and associating the crowd behavior parameters to the corresponding scene objects to generate parameter binding information; a configuration generation module is called, a configuration file compatible with an open source crowd simulation framework is generated according to the scene object set and the parameter binding information, and the configuration file comprises structured data describing the relation between scene object space attributes and crowd behavior parameters; and inputting the configuration file into an open source crowd simulation framework, executing simulation calculation of crowd agency behaviors, and generating trajectory data corresponding to the configuration file.

The present disclosure relates to the technical field of computers, and discloses an open source protocol analysis method and device, electronic equipment and a storage medium. The method comprises the following steps: obtaining a preset analysis template and a source code package of an open source project, wherein the preset analysis template comprises at least one protocol attribute and an analysis object of the protocol attribute; analyzing a target open source protocol used by the source code package based on the preset analysis template to obtain a target analysis result of the analysis object of the at least one protocol attribute; and obtaining a protocol analysis result of the open source project based on the target analysis result of the analysis object. The present disclosure can solve the problem of analyzing the open source protocol used by the open source project.