11 results about "Pseudo random number generation" patented technology

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).

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 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.

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.