23 results about "Pseudo random number generation" patented technology

The invention relates to the technical field of security calculation and privacy protection, in particular to a large model privacy reasoning method and device based on trusted hardware and electronic device.The method comprises the steps that before a large model reasoning task is executed, a client and a server initialize respective pseudo-random number generators based on information interaction so as to synchronize initial seeds, and the pseudo-random number generators are initialized; generating a random number based on the seed; in the reasoning execution process, homomorphic encryption is used for completing word embedding of large model reasoning, a reasoning instruction set is used for converting all operators into instruction combinations, privacy reasoning is carried out based on a privacy reasoning protocol and a random number generated by a pseudo-random number, and the random number is used for masking privacy data; and after the task is completed, obtaining an execution result and proof information provided by the server, performing verification, and refusing to receive the result if verification fails. Therefore, the problems of data leakage risk, difficulty in considering safety and efficiency and the like existing in related technologies are solved.

A method of generating at least one encryption key (130) for encrypting data (142), a method of data transmission between at least two communication systems (136, 138), a method of encrypting data (142) and a method of decrypting encrypted data (144) are disclosed. Further disclosed are an encryption key generating device (110), a system (134), a data encryption system (148) and a data decryption system (150). The method of generating at least one encryption key (130) for encrypting data (142), specifically for data transmission over an insecure channel, comprises:blending at least two materials (114) according to at least one item of blending information by using a blending device (112), thereby generating at least one blend (120);ii. detecting at least one material property (124) of the blend (120) by using at least one detector (126); andiii. transforming the material property (124) into the encryption key (130) by using at least one data processing device (132) configured for applying at least one transformation algorithm to the material property (124).

The invention relates to a shuffling machine control method, device and equipment and a storage medium, and belongs to the field of shuffling machines, and the shuffling machine control method comprises the following steps: obtaining entropy sources, and mixing the entropy sources to obtain randomized seeds; generating a control parameter by using a pseudo-random number generation module based on the randomized seed; and controlling the shuffling machine to operate based on the generated control parameters. According to the shuffling machine control method and device, the equipment and the storage medium, by introducing a randomization control algorithm and a real-time feedback mechanism, high randomization and self-adaptive control in the shuffling process are achieved, the shuffling quality is improved, card collision is avoided, and the failure rate of card sticking and one-time rubbing of multiple cards is reduced.

The present disclosure relates to systems and methods for pseudo-random batch code printing and product authentication via two-dimensional (2D) codes using dot matrix codes. Systems and methods are disclosed for authenticating a product using two-dimensional (2D) codes and dot matrix codes that involve generating an authentication sequence of pseudo-random numbers via a cryptographic algorithm. The initial seed value corresponds to a particular product within a batch, and each subsequent number is generated directly or indirectly from the previous number. And the 2D code printing application program generates two dot matrix codes based on different groups of pseudo-random numbers in the sequence, and prints the dot matrix codes on corresponding products in the batch. The first lattice code is printed onto the 2D code of the first product and the second lattice code is printed onto the 2D code of the second product, allowing each product to have a unique combination of codes that can be verified to confirm its authenticity. These systems and methods use one or more processors and printers to perform these steps, allowing for efficient and secure authentication of products within batches.

A pseudo random number generator includes a first generator configured to generate a random first bit sequence having a bit length with floating-point representation, and a second generator configured to generate a second bit sequence having the bit length, using a predetermined sign bit, a bit sequence of a predetermined exponent part, and a bit sequence of a mantissa part included in the first bit sequence.

This specification provides a pseudo-random number generation method and apparatus. The method includes: multiple iterations corresponding to the count value of a counter, wherein any t-th iteration includes: obtaining the seed output from the previous round as the current seed; processing the current seed and a first value using a symmetric encryption algorithm to obtain a random number for the current round, wherein the first value is determined based on the current count value of the counter and a preset first constant; processing the current seed and a second value using the symmetric encryption algorithm to obtain the seed for the next round of iteration, wherein the second value is determined based on the current count value and a preset second constant. It features high performance and side-channel security.

A method of generating at least one encryption key (130) for encrypting data (142), a method of 5 data transmission between at least two communication systems (136, 138), a method of encrypting data (142) and a method of decrypting encrypted data (144) are disclosed. Further disclosed are an encryption key generating device (110), a system (134), a data encryption system (148) and a data decryption system (150). The method of generating at least one encryption key (130) for encrypting data (142), specifically for data transmission over an insecure channel, comprises: i. blending at least two materials (114) according to at least one item of blending in-formation by using a blending device (112), thereby generating at least one blend (120); ii. detecting at least one material property (124) of the blend (120) by using at least one detector (126); and iii. transforming the material property (124) into the encryption key (130) by using at least one data processing device (132) configured for applying at least one trans-formation algorithm to the material property (124).

The invention relates to the technical field of chip-level network security, and discloses a pseudo-random number hardware acceleration and true random seed collaborative generation method and system, and the method comprises the steps: generating a load through monitoring a pseudo-random number, dynamically regulating and controlling the working mode of a true random seed generation unit with a multi-entropy source fusion and weight compensation mechanism, and generating a true random seed; according to the method, a closed-loop self-adaptive supply and demand response mechanism is established between the high-speed consumption demand of the pseudo-random number and the physical supply capability of the true random seed, so that the inherent contradiction between the resource efficiency and the operation safety of a traditional separated architecture is avoided; the multi-entropy source dynamic compensation design enhances the environmental stability and reliability of seed generation.

The application relates to a chip security mechanism self-checking system, method, computer device and storage medium. The system comprises a self-checking control module, a pseudo-random number generation module, a security mechanism unit and a cyclic redundancy check module. The self-checking control module is used for sending a control signal to the security mechanism unit needing self-checking according to configuration, enabling the self-checking function of the security mechanism unit, sending a pseudo-random number seed to the pseudo-random number generation module, comparing a check code sent by the cyclic redundancy check module with a check value, and outputting a self-checking result according to a comparison result. The pseudo-random number generation module is used for generating a plurality of pseudo-random numbers according to the pseudo-random number seed. The security mechanism unit is used for starting self-checking according to the control signal, receiving the pseudo-random number excitation and generating output data. The cyclic redundancy check module is used for performing cyclic redundancy check operation on the output data of each security mechanism unit, generating a corresponding check code, and sending the current check code to the self-checking control module when the pseudo-random number is traversed. The system can improve the self-checking coverage, reduce the test time and power consumption.

Various examples relate to systems and methods for generating a set of pseudo-random numbers in a computing system that includes a computing element and a memory device. A memory controller of the memory device may receive an indication from the computing element to generate a set of pseudo-random numbers. The memory controller may generate the set of pseudo-random numbers and write the set of pseudo-random numbers to a memory array of the memory device for access by the computing element.

The application relates to the technical field of chip-level network security, and discloses a pseudo-random number hardware acceleration and true random seed cooperative generation method and system, which comprises the following steps: monitoring a pseudo-random number generation load, dynamically regulating and controlling the working mode of a true random seed generation unit with a multi-entropy source fusion and weight compensation mechanism, and establishing traceable association from the seed to the pseudo-random number. A closed-loop adaptive supply-demand response mechanism is established between the high-speed consumption demand of the pseudo-random number and the physical supply capacity of the true random seed, so that the contradiction between the inherent resource efficiency and operation safety of the traditional separate architecture is avoided, and the multi-entropy source dynamic compensation design enhances the environmental stability and reliability of seed generation.

The invention discloses a chaotic key generation method and system based on discrete sine memristor cascade chaotic mapping, an image encryption method and a pseudo-random number generation method. The chaotic key generation method comprises the following steps: firstly, generating a chaotic mapping system consisting of a first-stage discrete sine memristor, a first-stage linear controller, a second-stage discrete sine memristor and a second-stage linear controller, performing multi-period iterative mapping through the chaotic mapping system, and sampling to obtain multiple groups of three-dimensional chaotic data; and forming a chaos matrix or a pseudo-random number based on the three-dimensional chaos data as a chaos key. The system is a circuit for realizing the chaotic mapping system. In the image encryption method, a chaotic matrix is constructed by utilizing chaotic data generated by a chaotic mapping system to serve as a secret key to realize image encryption, and in the pseudo-random number generation method, a pseudo-random number is formed by utilizing the chaotic data generated by the chaotic mapping system. The chaotic mapping system is rich in dynamic behavior, hardware is easy to implement, and the generated secret key is high in application value.

The present disclosure provides a pseudo-random number generator and a pseudo-random number generation method. The pseudo-random number generator comprises: a signal mapping circuit configured to map a plurality of input signals using a chaotic model to obtain a plurality of chaotic signals having a four-wing chaotic state; a signal sampling circuit electrically connected to the signal mapping circuit and configured to sample the plurality of chaotic signals to obtain a plurality of state variables corresponding to each chaotic signal in the plurality of chaotic signals; and a signal operation circuit electrically connected to the signal sampling circuit and configured to perform an integer operation on the plurality of state variables corresponding to each chaotic signal to obtain a plurality of groups of random numbers corresponding to the plurality of chaotic signals respectively, each group of random numbers in the plurality of groups of random numbers comprising a plurality of random numbers.

The application relates to the technical field of secure computation and privacy protection, in particular to a large model privacy inference method and device based on trusted hardware and electronic equipment, wherein the method comprises the following steps: before performing a large model inference task, a client and a server initialize respective pseudo-random number generators based on information interaction, so as to synchronize initial seeds and generate random numbers based on the seeds; in the inference process, homomorphic encryption is used to complete word embedding of the large model inference, all operators are converted into instruction combinations by using an inference instruction set, privacy inference is performed based on a privacy inference protocol and the random numbers generated by the pseudo-random number generator, and privacy data is masked by using the random numbers; after the task is completed, execution results and proof information provided by the server are acquired, verification is performed, and the results are rejected if the verification fails. Thus, the problems that related technologies have data leakage risks and are difficult to balance security and efficiency are solved.

The present disclosure relates to a block cipher-based variable-output-length pseudo-random number generation method, apparatus, system, and computer program, and more specifically, in the present disclosure, a method for generating a variable-output-length pseudo-random number using a computing device may include the steps of: generating a plurality of intermediate values, based on a given input value; producing a plurality of intermediate random values by performing block cipher-based encoding on the plurality of intermediate values; and deriving a final random value for the input value, based on a combination of the plurality of intermediate random values.

Embodiments of the present application provide a ransomware prevention method and device, a terminal and a computer readable storage medium. The method generates a first pseudo-random number based on a pseudo-random number generation module in response to the target software obtaining a random number, so that the target software encrypts the target file based on a key generated by the first pseudo-random number. Then, the second pseudo-random number identical to the first pseudo-random number is generated again based on the pseudo-random number generation module, and the target file is decrypted by using the second pseudo-random number. Embodiments of the present application change the way of obtaining the random number by the target software, and generate the first pseudo-random number and the second pseudo-random number based on the pseudo-random number generation module, which are both generated within a preset range. Therefore, the target file encrypted based on the key generated by the first pseudo-random number can be easily cracked, thereby solving the technical problem that the ransomware encrypts the file of the user, so that the encrypted file cannot be technically cracked.

The invention relates to the technical field of anti-packet-loss methods, in particular to a self-adaptive anti-packet-loss method based on deep learning, and the method comprises the steps: a sending end and a receiving end, 1) the sending end carries out the anti-packet-loss, 2) the receiving end carries out the anti-packet-loss, an automatic feedback algorithm is adopted to optimize a packet loss probability model P (n), an adversarial generation algorithm is adopted to process a feature vector, and a packet loss probability model P (n) is obtained; and on this basis, the audio feature vector of the receiving end generated by the output of the generator tends to be consistent with the audio feature vector of the sending end. At a sending end, the time-space information of audio features is extracted through a graph neural network, and packet loss is simulated by using a pseudo-random number generation algorithm. At a receiving end, an adversarial generative network is adopted to train a potential audio feature model, and an automatic feedback algorithm is used to dynamically optimize a packet loss probability model. Through the comprehensive design, the method can effectively adapt to various network environments, and the packet loss resistance is greatly improved.

Systems and techniques for providing pseudorandom number generation include generating a pseudorandom number based on a bitwise exclusive-OR, or XOR, function that compares a shifted version of an input seed with one of a plurality of values, where one of the values is selected based on whether a first bit of the input seed is set or unset. An initial seed value is stored in hardware or generated based on an unknown value stored in memory, and successive outputs of the pseudorandom number generation are used as seeds in subsequent pseudorandom number generation operations.

A data set integrity verification method, a model training method and a computing device relate to a to-be-tested model obtained through training according to a real data set, the real data set comprises a training sample, and the training sample comprises a target sample. The sample number of the target sample in the real data set is generated by using a preset pseudo-random number generation algorithm and taking a first identifier as a random number seed, and the first identifier is determined by using a preset Hash algorithm according to the training sample in the real data set; the prediction result distribution of the to-be-tested model for the target sample and the real data set is different; acquiring a nominal data set; selecting training samples in the nominal data set according to a Hash algorithm and a pseudo-random number generation algorithm to obtain a probe set; determining the prediction accuracy of the to-be-tested model for the probe set; whether the nominal data set is the real data set is determined according to the prediction accuracy corresponding to the probe set, and tiny tampering of the real data set used in the training process can be recognized with low calculation cost.

This invention relates to the field of switching power supply control technology, and discloses a method and circuit for dual random frequency dithering and adaptive slope compensation in switching power supplies. The method generates a dual-layer independent random sequence based on pseudo-random numbers, and generates a slow random triangular wave frequency dithering signal and a fast random jump frequency dithering signal through layered mapping. The switching cycle duration is obtained through cycle counting and numerical conversion, and the target duty cycle is calculated by combining the input voltage and output voltage reference values. Using the target duty cycle, switching cycle, and system parameters, an adaptive compensation slope value is calculated through a lookup table combined with interpolation or formulas. A digital compensation slope is generated based on the smoothed compensation slope and the cycle synchronization signal. This slope is digitally added to and compared with the inductor current sampling signal to achieve stable LED drive current output. This invention maintains stable output current while effectively suppressing broadband electromagnetic interference, and is suitable for high-reliability applications such as automotive LED drives.

The invention discloses a pseudo-random number generation method and a pseudo-random number generation system based on training-free multi-scale autoregressive Transform and 3D-Lu chaotic collaboration. The method comprises the following steps: firstly, decoupling a master key into an original submerged space seed of a visual autoregression model by using an SHA-384 algorithm, and sampling a temperature parameter and an original state vector; then, generating a high-dimensional nonlinear original sequence by using a multi-scale autoregressive network of a frozen weight, and performing dynamic masking and large-scale quantization enhancement in combination with a trajectory of a 3D-Lu chaotic system; and finally, updating the input seed in real time through a Hash chain type feedback loop based on SHA-256. According to the method, the dynamic degradation problem of the digital chaotic system is effectively suppressed through a heterogeneous cooperation mechanism, the pseudo-random sequence with an ultra-large key space and excellent statistical characteristics can be obtained without data training, and the method is suitable for high-security requirements such as image encryption and the like.

The invention relates to a method and a system for generating a pseudo-random number based on a mixed entropy source, which can ensure the unpredictability of a seed even if the system is just started and an external entropy source is insufficient by introducing a persistent RSA private key as a static entropy source. Meanwhile, in combination with an SHA-512 Hash algorithm, full mixing of entropy sources is ensured, and safety risks caused by the fact that a single entropy source is broken through are prevented. According to the method, a plurality of non-blocking system state information (PID, load and temperature) is mixed, and the dependence on a single blocking entropy source (such as / dev / random) is reduced, so that the generation efficiency is improved on the premise of ensuring the safety. The method can be applied to the fields of token generation in large-scale network communication, digital currency wallet private key generation or end-to-end encrypted private key generation in instant message communication and the like, can also be used for other similar token generation services, and has a wide application prospect.

The invention relates to an encryption processing method and device for credit card information, equipment and a storage medium. The method comprises the following steps: generating a target password according to credit card information to be encrypted and a pseudo-random number, encrypting the credit card information to be encrypted by using the target password to obtain an encrypted ciphertext, performing fusion operation on the encrypted ciphertext and a first preset image to obtain a first image containing the credit card information, according to the target password and a preset image generation rule, a second image containing the target password is generated, and the target password is used for decrypting the encrypted ciphertext in the first image. According to the invention, user experience can be taken into account while credit card information security is guaranteed.