9 results about "Initial Seed" patented technology

The application discloses a mirror structure topology optimization method and device based on thermal coupling and a mirror, and relates to the technical field of metal mirror research and development. The application provides a mirror structure optimization method driven by thermal coupling simulation, which can self-adaptively control seed density and complete constrained Voronoi partition in a mirror body design domain. The method comprises the following steps: creating an initial model of a mirror to be optimized by using a three-dimensional modeling software; assigning initial Voronoi seed points; matching a corresponding stress value closest to each initial Voronoi seed point; dividing the Voronoi seed data into a high-stress-area seed point set and a low-stress-area seed point set; merging after increasing the seed point density in the high-stress-area and decreasing the seed point density in the low-stress-area; and performing 3D Voronoi partition between a front mirror surface of the mirror and a support frame body. The optimization method is suitable for optimizing the structural parameters of an existing mirror.

The application discloses a protocol fuzzing method based on state machine constraints, and relates to the technical field of network security.The method comprises the following steps: performing static analysis on the source code of a target protocol implementation, and extracting state machine constraint relations; based on the state transition paths in the state machine constraint relations, performing state expansion on a preset initial seed pool in an initial stage of fuzzing; based on the client request constraints and the server state constraints in the state machine constraint relations, performing mutation on the expanded seed pool in a cycle stage of fuzzing, and generating test cases; and performing fuzzing on the target protocol by using the generated test cases.The method can accurately extract the state machine of the protocol implementation and guide the fuzzing process accordingly, and effectively improves the pertinence and efficiency of the protocol fuzzing.

This invention provides a rapid analysis method for large-scale land space compliance review, comprising the following steps: receiving a compliance review task submitted by a user, the review task including the review scope geometry, target planning layer, and review rules; calculating the area of ​​the bounding rectangle (AreaEnvelope) and the area of ​​the geometric shape (Area) within the review scope geometry; if both AreaEnvelope and Area are present, it is determined to be a small-scale review, and the traditional single-step compliance analysis process is executed; otherwise, it is determined to be a large-scale review, triggering a parallel optimization process; performing balanced region division for large-scale reviews, including initial seed point generation, Voronoi diagram construction and pruning, and iterative optimization steps; performing parallel compliance analysis and generating a review report. This invention transforms a single long-duration calculation into multiple short-duration parallel calculations, reducing the review time from minutes / hours to seconds, meeting the needs of real-time review.

The application discloses a kind of real BOM construction methods and systems for complex equipment, it is related to product life cycle management technical field, including: EBOM structure tree and PBOM structure tree are mapped matrix is constructed;With EBOM structure tree as basic skeleton, traverse EBOM node, to each EBOM node, if there is corresponding PBOM node in mapping matrix, then the attribute of corresponding PBOM node is attached to current EBOM node;If it does not exist, then keep current EBOM node, and obtain initial seed tree;According to the process assembly sequence and node type of PBOM structure tree, the initial seed tree is adjusted in structure, conflict resolution and deduplication are executed, and the real BOM structure tree skeleton is obtained;Real BOM structure tree skeleton is filled with real object data, and the real BOM structure tree is obtained, and tree structure difference comparison method is used for updating.It realizes the mapping conversion and dynamic synchronization from digital BOM to real BOM.

The application provides a self-development method and system based on a morphogenetic field, the self-development method comprising: receiving a user intention and converting it into a structured intention message; generating a functional semantic manifold, constructing a mixed manifold space and a morphogenetic field, and generating an initial seed of the morphogenetic field; determining an implementation mode of a task target in the structured intention message; assigning the task target to a plurality of morphogenetic engines; assigning the initial seed to the plurality of morphogenetic engines for solving, and broadcasting field slice data on a shared physical interaction interface; adjusting a solving strategy of the morphogenetic engines; when the plurality of morphogenetic engines reach a cooperative stable state, collecting achievement data and generating a standardized delivery package. Through intention analysis, construction of a morphogenetic field and an initial seed, objective judgment of an implementation mode of a task target and real-time adjustment of a solving strategy, a delivery process from an abstract intention to a standardized engineering product is realized.

This invention proposes a fuzzing method and system for WebAssembly engines, relating to the field of software testing. It involves acquiring a large number of WebAssembly binary samples as initial seed samples; parsing the initial seed samples into an attribute abstract syntax tree (API) with node position and type information; applying a mutation method to the API using a type-aware mutation strategy and a structure-aware instruction mutation method to generate a new API with valid structure and type; pre-validating the mutated API and quickly correcting invalid node positions; and generating WebAssembly binary samples from the pre-validated API, which are then input into the target engine for fuzzing. This invention, by using an API based on attribute abstract syntax trees and a WebAssembly mutation method with pre-validation and rapid correction, more effectively generates WebAssembly module mutations with correct binary format, legality, and compliance with security constraints, enabling efficient fuzzing of the WebAssembly engine.

The application belongs to the technical field of software security and automatic test, and provides a library fuzzy cooperative test method and system based on static analysis and large language model, performs static analysis on a target software library, extracts metadata information of the library, constructs a cross-file function call graph, and performs code slicing on a target function in the library; based on the extracted metadata information and the sliced code, a prompt word containing a calling context is constructed, an initial template of a driver program is generated; the validity of the driver program is verified through compilation until a compilable driver program is generated; input parameter types and path constraints are identified; script code for constructing seeds is generated, the script code is executed to generate an initial seed corpus; the generated seeds are verified for validity, and cooperative seeds are screened out; the generated driver program and the cooperative seeds are continuously subjected to fuzzy test, and crash information is collected to identify potential security vulnerabilities. The accuracy and efficiency of the software library fuzzy test are significantly improved.

A method and apparatus for assessing privacy leakage risk of a large model. In this method, several prompt templates are generated as initial seed prompt templates, and the following iterative process is performed: the current seed prompt templates are diversified and expanded; the prompt words corresponding to the multiple prompt templates are input into the target large model to obtain corresponding inference information; the fitness score of the corresponding prompt template is determined accordingly; and several prompt templates with higher fitness scores are selected as updated seed prompt templates. Based on the seed prompt templates after multiple iterations, the target prompt template and corresponding target prompt words are determined; the target inference information of the target large model for the target prompt words is obtained; and the assessment result regarding the privacy leakage risk of the target large model is determined accordingly. The prompt template includes: a first placeholder for representing known user information, a second placeholder for representing target user information, and a task description indicating how to infer target user information based on the known user information. User information is private data.

The application discloses a random data generation method, system and platform based on a white-box algorithm. The application obtains a replay seed signal through a method, generates first seed data in real time according to the replay seed signal, processes the first seed data through encoding mapping to generate second seed data, and transmits the second seed data in real time. The second seed data is processed through encoding inverse mapping to generate initial seed data and device identity sequence data respectively. The internal state is initialized according to the initial seed data, and self-equivalent affine transformation is generated in real time. Random data is generated in real time through the generated self-equivalent affine transformation and in combination with the white-box algorithm, and the corresponding system and platform can guarantee the forward and backward security of a software random number generator and the seed security.