39 results about "Random seed" patented technology

This application provides a method and apparatus for generating random instruction test cases, relating to the field of automated testing technology. First, target instructions or instruction sequences are encapsulated into C inline functions using inline assembly or macro definition, forming a unified function library. Next, a function parameter constraint system is constructed, defining parameter types, address ranges, instruction combination methods, and value range constraints for each encapsulated C inline function. Then, a multi-level nested structure is built based on the C inline functions to organize the instructions, where each level node is associated with a corresponding C inline function name and constraints. Finally, based on a YAML configuration file, the target C inline functions are determined from the multi-level nested structure and combined to generate random instruction test cases. The YAML configuration file includes at least the number of iterations, a random seed, a random strength factor, and test content configuration. The solution provided in this application has the advantages of improved verification efficiency and applicability to different scenarios.

The application discloses a large model watermarking method based on dynamic entropy, belonging to the field of large model watermarking. It includes: modifying the output token sampling process; dynamically adjusting the size of the sliding window and the size of the candidate token pool according to the probability distribution entropy value of the large model output; through pseudo-random scoring and multi-round competition; for each token in the sequence to be analyzed, the same watermark key and the context before the token are used to recalculate the pseudo-random seed, and based on the seed, the corresponding pseudo-random score of the token at all levels is regenerated; the average pseudo-random score of all tokens in the text is calculated as the aggregate score, and the statistical threshold is determined based on the preset false positive rate. If the statistical threshold is less than the aggregate score of the unknown text, it is determined as a generated text with watermark, otherwise it is a text without watermark. The application realizes high-precision source identification and tracing of large model output content through the dynamic entropy watermarking method while ensuring the original quality of the generated text.

The application provides a mixed supervision language model distillation method based on bridge domain-park domain decomposition, comprising the following steps: constructing a prefix state sequence, and saving context and task identification. The state information is used for subsequent partition discrimination and error statistics. The probability distribution, hard label, confidence and entropy statistics of the teacher model are obtained for each state. The state risk is calculated, and the bridge domain and the park domain are divided to form a partition label. The partition label can be reused for training weighting and slice analysis. Soft supervision and hard supervision are calculated at the state level, and are dynamically weighted. The joint optimization process keeps the single model parameter space solution, and reduces the process complexity. The final model is selected according to the accuracy, stability, time delay and cost, and an auditable evaluation report is formed. In the evaluation stage, unified benchmarks and fixed random seeds are recommended to improve comparability.

The application discloses a large code length private key amplification data access method suitable for a quantum key distribution system. Through the combination of DDR and on-chip memory BRAM, the reading of the error-corrected key and the random seed is no longer required to be synchronous, so that the requirement for the external memory can be reduced, the subsequent hardware integration processing is facilitated, the influence of the limitation of the IO speed of the external memory on the PA processing speed is reduced, and under the condition of resource permission, multi-path synchronous calculation can be performed, and the implementation performance of the PA is effectively improved.

This invention relates to a recommendation method based on verifiable local differential privacy, belonging to the field of privacy protection technology. The specific process of this method is as follows: the client generates a client-side random factor; the client uses a server-side random seed to generate a server-side random factor; the client-side random factor and the server-side random factor are combined to obtain a perturbation factor; an interaction rating vector is generated based on the client's interaction with the product; the perturbation factor is used to perform random perturbation on the interaction rating vector to obtain a perturbation rating vector that satisfies local differential privacy; the client constructs a zero-knowledge proof, which proves that the client strictly follows a predefined random perturbation mechanism; the server verifies the zero-knowledge proof and aggregates the perturbation rating vectors of all clients that pass the verification; a recommendation list is generated based on the aggregation result, and the recommendation list is returned to all clients.

This invention discloses a privacy-preserving method for federated learning based on adaptive quantization and sparse secret sharing: the server generates a globally random seed and broadcasts it to the clients. Each client locally generates a sparse neighbor set and negotiates a shared key, reducing communication complexity to logarithmic levels. After training gradients, the clients adaptively quantize to an integer ring, using their private seed and shared key to generate private masks and pairwise masks, which are then superimposed and uploaded. Simultaneously, the seed and key are split into secret shares and distributed to neighbors. The server directly sums these to obtain a preliminary aggregation result. After the window expires, it requests secret fragments to reconstruct the private seed and shared key, eliminating private masks and pairwise mask remnants caused by disconnected clients. After dequantization, the global model is updated. This invention reduces communication and computational overhead, eliminates the need for homomorphic encryption, has strong anti-disconnection capabilities, supports large-scale IoT devices, and achieves efficient and robust federated learning aggregation while ensuring information-theoretic security.

This invention provides an ensemble sampling method for a diffusion model used in content generation, comprising: at the beginning of sampling, selecting K random seeds for the same input condition, generating corresponding initial noise states for each random seed, resulting in K initial noise states; performing a first-stage diffusion reverse time step on each of the K initial noise states using a diffusion model, resulting in K intermediate state representations; performing an ensemble operation on the K intermediate state representations to fuse them into a single ensembled intermediate state; and using the single ensembled intermediate state as the starting state, continuing to perform a second-stage diffusion reverse time step under the same diffusion model to obtain the generated state. This invention not only requires less computation but also produces a higher quality generated image based on the generated state, with significantly fewer artifacts and blurring compared to fusion methods that integrate the final result after multiple complete sampling.

A method may include: receiving, by a smart contract, a request for a random number and a randomness seed from a user; deploying the request as a transaction that is written on a first block in the decentralized ledger; generating, by an oracle, a plurality of pseudorandom quantum circuits using the randomness seed; providing the plurality of pseudorandom quantum circuits to a quantum randomness source, wherein the quantum randomness source executes the quantum circuits and returns a sequence of random bits to the oracle; writing the sequence of random bits to a new block in the decentralized ledger; hashing the sequence of random bits and a block hash for the new block; and returning the hash of the sequence of random bits and the block hash to the user computer program, wherein the user consumes hash of the sequence of random bits and the block hash.

This invention discloses a secure access method for network interface card (NIC) firmware based on dynamic instruction mapping and transactional buffering. During session initialization, the driver and application construct an instruction opcode mapping table and data structure offset rules valid only for the current session based on a negotiated random seed, achieving dynamic obfuscation of communication protocol features. When processing write requests, the driver temporarily stores the data, reads the current hardware snapshot, performs semantic-level virtual assembly and logical conflict prediction, and intercepts dangerous operations with valid signatures but mutually exclusive configuration logic. Only after pre-verification passes and a commit instruction is received does the driver calculate the differential bitstream between the shadow buffer and the hardware data, lock the bus, and perform atomic incremental synchronization. This invention effectively resists reverse engineering and replay attacks through three mechanisms: dynamic protocol transformation, logical conflict immunity, and differential atomic commit, while also preventing firmware corruption caused by configuration errors or abnormal interruptions.

The application discloses a kind of pseudo-random number generation methods based on UDS 27 diagnostic authentication service, comprising: receiving diagnostic service 27 request;Read physical variable and mixed entropy source;Check whether the last random seed exists, if yes, enter S4, if not, enter S5;S4, load history seed, and enter S6;S5, use default initial seed, and enter S6;S6, seed is combined processing;Based on the seed value after mixed processing generates new random number;New seed is saved to nonvolatile memory;Format response data;Complete 27 authentication.The pseudo-random number generation method based on UDS 27 diagnostic authentication service of the application, improve the entropy value of random number by multi-factor combination, ensure high-entropy randomness;While superimposed history seed to ensure seed randomness, ensure random sequence continuity, to avoid being illegally simulated through 27 security access authentication service, attack ability is strong.

The application belongs to the field of bioinformatics and relates to a cell communication prediction method based on heterogeneous graph integration and dynamic fusion. First, ligand receptor features and labels are obtained and a heterogeneous graph is constructed, outer layer stratified cross-validation and training fold stratified validation are adopted, and only training feature standardization is based; second, a deep neural network branch outputting a prediction logarithm value is trained, and a first prediction probability is obtained through Sigmoid; third, a multi-random seed heterogeneous graph auto-encoding sub-model is trained, an AUC based on a current outer layer reserved evaluation set is monitored, and the optimal parameters are rolled back, the sub-model edge prediction probability is averaged to obtain a second prediction probability; then, the two branch results are ranked and normalized, and dynamic gating or weight search fusion is performed based on the AUC of the current evaluation set; finally, the final interaction prediction score or ranking result is output. The application can reduce the risk of information leakage, alleviate the output scale difference and weak branch interference, and significantly improve the model stability and generalization ability.

The application discloses an anticancer peptide generation and screening method and system based on a diffusion model and a seed synchronous autoencoder, and comprises the following steps: preprocessing original anticancer peptide and non-anticancer peptide sequences and extracting multi-dimensional physicochemical features; training a diffusion model in a continuous numerical space based on sequence mapping based on a global random seed, adding noise through forward diffusion and learning the potential distribution of anticancer peptide data features through reverse denoising; based on a reverse seed synchronization strategy, training an autoencoder using the same random seed and environment state, and establishing a mapping from continuous random noise to discrete biological sequences; using the diffusion model to sample and generate potential vectors in the latent space and mapping them into candidate anticancer peptide sequences through the decoded synchronously trained decoder; inputting an integrated learning classifier based on grouping features, selecting the optimal feature group and predicting the anticancer activity probability, and outputting the anticancer characteristic peptide chain; the application solves the mapping contradiction between continuous space and discrete sequences and can efficiently screen anticancer peptides with high activity sequences.

The application provides a blood vessel segmentation method for an infrared operation image based on an improved U-Net, comprising the following steps: step 1, converting an input original picture into standardized data with a high signal-to-noise ratio and meeting the input requirements of a model tensor; step 2, simultaneously calling pre-trained models with different random seeds, the pre-trained models performing parallel prediction and independently generating prediction results; step 3, performing a mean aggregation operation to generate an uncertainty measurement map; step 4, scaling the segmentation result back to the resolution of the original picture through interpolation, converting the continuous probability into a conclusion of whether it is a blood vessel, and finally labeling the input infrared operation image based on the conclusion. Under the premise of not increasing the model parameter quantity, the method realizes physical superposition of weak features. It utilizes the redundancy between feature map channels, forcibly fuses the information of the encoder and the decoder through addition, and significantly improves the detection rate and continuity of small blood vessels in the infrared operation image.

The application discloses an AES-based random value generation method, system, device and storage medium, and the method comprises the following steps: obtaining an original true random bit stream, and performing bias correction and interception on the original true random bit stream to obtain a true random seed; based on the true random seed and an individualized string, a current round key and a current round counter value are obtained through an AES encryption algorithm, and the current round key and the current round counter value are combined into a current round state of CTR_DRBG; a current round random bit string is generated through the AES encryption algorithm according to the current round state; it is judged whether a preset target length is less than or equal to the length of the current round random bit string; if yes, random bits corresponding to the preset target length are intercepted from the current round random bit string as pseudo-random values. The application guarantees security through a true random seed, guarantees high efficiency through AES-128 encryption, and finally realizes transparent compatibility and safe use of true and pseudo random numbers.

The application is a kind of closed-loop dynamic optimization-based generation method of fixed porosity heterogeneous honeycomb structure. It includes: setting the macroscopic design parameters of the target plate; taking the total number of random seed points as the only variable to initialize the binary search interval; in the optimization iteration, based on the current point number, boundary mirror image anti-distortion and Voronoi partition are performed, effective common edges are extracted and equally offset to generate continuous entities without broken walls; finally, the actual porosity is calculated, and the seed point interval is updated by using the bisection method in a closed loop until the error converges. The application realizes the precise control of macroscopic porosity and the high disorder of microscopic force transmission path under the premise of complying with the wall thickness limit of additive manufacturing, and provides a high-quality geometric model for impact-resistant protection design.

The application relates to a software runtime memory fingerprint watermark protection method and system, and belongs to the field of computer software security protection.The method comprises the following steps: collecting various hardware characteristic information of a target device to generate a device fingerprint, selecting a predetermined position segment as a deterministic random seed, driving a pseudo-random number generator by the seed, constructing a hierarchical object tree, recursively traversing the object tree to calculate final hash values of each node, collecting node identification, the number of child nodes, the final hash value of the node and the address difference between the parent node and the child node, and obtaining a comprehensive topology hash value through a cryptographic hash operation, repeatedly executing comparison of the comprehensive topology hash value at random time intervals during operation, and identifying debugging behavior in multiple dimensions by using different detection methods, and executing a hierarchical threat response according to the comparison result and the anti-debugging detection result.The application closely binds the device fingerprint and the runtime memory layout, realizes strong association protection of a software running environment and a memory topology, and effectively resists copying, tampering and dynamic debugging attacks.

A method and system to increase security in VPN services are provided. The method comprises receiving, at a VPN terminator, a message sent by a first computer device at a first site intended for a second computer device at a second site; encrypting the received message, at the VPN terminator, using a first shared session key, the first shared session key being updated using a first renegotiated session key; and routing, by the VPN terminator, the encrypted message to the second computer device. The method further comprises periodically combining the first renegotiated session key with a first LLB shared secret to generate a first hash function, which is used to create the first shared session key. The first LLB shared secret is computed by hashing a value of at least one selected random seed with another LLB shared secret.

The present disclosure relates to the field of semiconductor circuit testing, and particularly relates to a memory simulation method, comprising: providing a first refresh command and a second refresh command to a memory, and providing a plurality of word line opening commands to the memory between the first refresh command and the second refresh command; wherein the number of word line opening commands is generated based on a random seed, the word line address corresponding to each word line opening command is generated by the corresponding random seed, and the opening time corresponding to each word line opening command is generated by the corresponding random seed; obtaining a preset address required to be refreshed by the memory after different word line addresses are opened based on the plurality of word line opening commands; obtaining a refresh word line address refreshed by the memory based on the second refresh command; and judging whether the preset address+1 and the preset address-1 are located in the refresh word line address or not, so as to test whether the supplementary refresh function of the refresh circuit is normal, thereby ensuring the accuracy of the stored data in each storage area.

The application relates to the technical field of processor verification, and provides a RISC-V branch predictor closed-loop verification method and system, which comprises the following steps: providing a plurality of test modes facing a branch predictor micro-architecture, each test mode corresponds to a branch behavior feature and has a parameterized configuration; receiving a random seed, selecting a target test mode from the plurality of test modes based on the random seed, and determining parameters for the target test mode; generating a corresponding RISC-V assembly test program according to the target test mode and the parameters, so as to perform closed-loop verification on the RISC-V branch predictor. Through the parameterized test mode facing the micro-architecture and the random seed driving mechanism, efficient closed-loop verification is realized, the problem that test excitation randomness is too high or simulation time is too long in the prior art is solved, and the verification efficiency is effectively improved.

The present application provides a steganographic embedding and image recovery method and device based on remote sensing image sensitive targets, which relates to the technical field of remote sensing image processing. The present application obtains an original remote sensing image and extracts a sensitive target bounding box, initializes a single-channel all-zero matrix, generates a global binary union mask and a carrier image; then performs non-scaling mapping and packaging on the sensitive target to generate a secret map and a metadata file; a fixed decoder is initialized using a random seed key; texture block selection based on local binary pattern is performed, a secret-containing image is generated through joint loss optimization, and a segmented linear warming schedule is introduced to balance performance; residual disturbance is extracted at the decryption end and analyzed by the decoder, and the target is seamlessly pasted back in place in combination with the metadata file. The present application can avoid scaling distortion, maintain the visual quality of the carrier, realize high-fidelity hiding of multi-scale sensitive targets, pixel-level accurate recovery, and scene-level in-place restoration, and has high security and strong robustness.

The application provides a hydrate and gas occurrence form reconstruction and voxel number control method, and belongs to the field of digital rock physics and pore-scale medium reconstruction. The application reconstructs different material occurrence forms in a three-dimensional voxel pore candidate domain, and realizes accurate, stable and repeatable control of saturation in the sense of discrete voxel counting. Specifically, a three-dimensional voxel digital core is taken as input, a pore voxel set or a subset thereof is determined as a candidate domain based on identification of a solid skeleton voxel set and a pore voxel set, a continuous scalar priority field is constructed in the candidate domain, a target saturation is mapped to a target voxel number, and then a target voxel number selection process of "a small amount of pseudo-random disturbance breaking an isovalued platform, a threshold determined by partial order statistics, accurate repair of supplementing / removing, and random seed and rule recording" is performed in the candidate domain to obtain a target phase voxel set.

The application provides a verifiable resale attribution and dispute resolution method and system for fine-grained structured data transactions. In the sales stage, a unified data processing specification is established through public universe and three-state normalization processing, different buyers are allocated different column views and bit map bindings are generated, the normalized data is embedded, locally sensitive hash is discretized and minimum hash digest is generated, the buyer binding receipt leaf is organized into an authentication data structure, and the root digest is anchored to the alliance chain smart contract. In the resale stage, the sampling position is determined by the on-chain unpredictable random seed, the authentication path verification and normalization recalculation are executed by the independent committee node to confirm the authenticity of the resale object. In the dispute stage, the suspicious sample is extracted and the disclosure digest is confirmed by the committee threshold, and the dispute object is locked. The proving party generates zero-knowledge proof to compare the coincidence count between the candidate buyer digest and the disclosure digest, and outputs the accusation, exclusion or retention judgment three-state ruling result according to the preset accusation threshold and exclusion threshold. Without disclosing the plaintext delivery data, the application provides a verifiable object authenticity verification channel for legal resale, and a privacy protection attribution mechanism based on similarity detection and double threshold ruling for illegal resale or data leakage.

This invention discloses an ECU diagnostic access system, method, device, and storage medium. The system includes a diagnostic instrument and an ECU. The diagnostic instrument sends a RequestSeed sub-function command to the ECU. The ECU parses the RequestSeed sub-function command, identifies the level identifier, and generates a random seed based on the current timestamp using a deterministic random number generator. The ECU then sends the level identifier and the random seed to the diagnostic instrument. The diagnostic instrument matches the corresponding scenario-based Label security level and master key according to the level identifier, generates a Send key using a preset seed key algorithm, and sends the Send key to the ECU. The ECU verifies and compares the Send key and the authentication key. If they match, the ECU unlocks the access permission for the scenario-based Label security level and allows service access. This invention combines scenario-based identifiers to achieve differentiated key derivation, thereby achieving both practicality and high security for secure access.