8 results about "Avalanche effect" patented technology

The invention provides an anti-fraud early warning system based on multi-source cross-platform fusion, belongs to the field of network security and privacy computing, and aims to solve the problems of privacy set intersection matching failure and early warning missing report caused by data noise. According to the scheme, data are cleaned through a multi-modal normalization engine, and the cleaning distortion degree is calculated; generating a fuzzy feature vector containing a plurality of variants through a fuzzy feature mapper to avoid the Hash avalanche effect; performing privacy set intersection in a ciphertext domain through an encryption calculation unit; and finally, a risk decision-making module combines the variant weight and the time decay factor to carry out weighted scoring and generate an early warning. According to the method, accurate matching is upgraded into fuzzy query, so that the early warning robustness and accuracy are remarkably improved, and risk quantification and privacy security are realized at the same time.

The application provides a reversible desensitization method for a visual rough visible sensitive image, and the method comprises the following steps: constructing a pixel matrix and dividing the matrix into blocks according to original image channel data and desensitization parameters; performing summation and encryption on the first two adjacent pixels of a first image block to obtain a ciphertext pixel group; then, the second pixel of the ciphertext pixel group and the next unencrypted pixel are combined into a new group, and the new group is iteratively encrypted by using a pseudo-random function and an encryption key until the pixels in the block are processed; a random number sequence is generated to rearrange the positions of the ciphertext block elements and complete permutation encryption; the current ciphertext block and the key are spliced and then hashed to derive the encryption key of the next image block, and all the blocks in the block and among the channels are processed in sequence; finally, the ciphertext blocks are reorganized according to the original channel order to obtain a desensitized image. The application forms a three-level encryption chain architecture which is mutually related and layer by layer transmitted; the architecture makes the pixels, image blocks and color channels of the image form strong encryption dependence at each level, and realizes the avalanche effect of the desensitization process.

The invention discloses a multimodal transport one-order system waybill sensitive data hierarchical encryption and dynamic evaluation method, and relates to the technical field of logistics information. According to the method, waybill data is divided into high-sensitivity data, medium-sensitivity data and low-sensitivity data according to sensitivity degrees, and differential encryption is performed on different levels of data by adopting an AES-256 algorithm in combination with a dynamic timestamp key, adopting a Blowfish algorithm in combination with a random byte sequence key and adopting an SHA-3 algorithm in combination with a unique salt value; and the encryption strength is quantitatively evaluated through thermodynamic diagram distribution, spectrum uniformity, avalanche effect and other indexes, and the encryption performance is analyzed in combination with an information entropy value and total time consumption. By monitoring the data deviation degree in real time, fine tuning optimization, parameter reset or safety alarm strategies are dynamically triggered, and a lagging interval mechanism is introduced to prevent parameter oscillation. According to the invention, a quantifiable and adaptive integrated solution is provided for privacy protection and system performance balance of multimodal transport one-order system waybills.

The present invention relates to a method for implementing hashing with high preimage resistance, collision resistance, and avalanche effect using a neural network model. A message hashing method according to an embodiment of the present invention comprises the steps of: generating a first random number dataset by setting each element of a vector having a first length as a random number, and generating a second random number dataset by setting each element of a vector having a second length shorter than the first length as a random number; supervised learning of a merge block using a first training dataset in which input / output data is composed of the first random number dataset; supervised learning of a hash block using a second training dataset in which input / output data is composed of the first and second random number datasets, respectively; generating a plurality of units by dividing a target message by the first length and sequentially inputting the plurality of units into the merge block serially connected by the number of units; and determining a digest having the second length by inputting the output of the serially connected merge block into the hash block.

The invention discloses a dynamic spiral and bidirectional diffusion image encryption method based on four-dimensional chaos, and relates to the technical field of information security. Comprising the following steps: generating a high-entropy key stream related to a plaintext image based on SHA-512 Hash and a four-dimensional chaotic system; dynamically controlling the direction, the starting point and the step length of spiral traversal by using the key stream, and carrying out layered spiral scrambling on image pixels so as to damage spatial correlation; and performing forward and backward bidirectional diffusion on the scrambled image by using two independent chaotic key sequences in combination with a nonlinear feedback mechanism so as to realize confusion and diffusion of global pixel values. Through the synergistic effect of the chaotic system, the dynamic scrambling and the bidirectional diffusion, the problems that the randomness of a low-dimensional chaotic system is insufficient and the residual correlation of static scrambling and the avalanche effect of unidirectional diffusion are weak are solved, and the security, the randomness and the anti-attack capability of image encryption are remarkably improved.

The invention discloses a data storage method and a related device, and the data storage method comprises the steps: receiving a data change request for a database, the data change request pointing to at least one piece of data; executing a data change operation corresponding to the data change request on at least one piece of data in a database; and synchronously executing a data change operation on the at least one piece of data in the cache. According to the scheme, the dirty reading or expired data problem of data query can be avoided, and meanwhile, the cache avalanche effect cannot occur in a high-concurrency scene.

The application relates to the technical field of image encryption, and discloses a plaintext-related image encryption method based on a bidirectional dynamic window, which comprises the following steps: calculating the hash value of a plaintext image, combining the hash value with a master key to generate a session key, using the session key to disturb a chaotic system to generate first to fourth chaotic sequences; using the first chaotic sequence to perform pixel position replacement on the plaintext image to obtain a scrambled image; performing high-low bit exchange of pixel values on the scrambled image to output an intermediate image; using the second and third chaotic sequences to construct a forward dynamic window scheduling table and a reverse dynamic window scheduling table respectively, and sequentially performing forward window-by-window diffusion calculation and reverse traversal diffusion calculation on the intermediate image; and using a two-dimensional matrix remodeled by the fourth chaotic sequence to perform feedback superposition calculation to output a ciphertext image. The application establishes the correlation between plaintext and encryption parameters, and introduces a bidirectional dynamic window diffusion mechanism, thereby avoiding the regularity of fixed diffusion step length, and improving the ability of the algorithm to resist selective plaintext attacks and the avalanche effect.

The application provides an anti-fraud early warning system based on multi-source cross-platform fusion, belongs to the field of network security and privacy computing, and aims to solve the problems of privacy set intersection matching failure and early warning false alarm caused by data noise. The scheme cleanses data and calculates cleansing distortion degree through a multi-modal normalization engine; generates a fuzzy feature vector containing multiple variants through a fuzzy feature mapper to avoid hash avalanche effect; performs privacy set intersection in the ciphertext domain through an encryption calculation unit; and finally generates an early warning by a risk decision module in combination with variant weight and time decay factor for weighted scoring. The application upgrades the precise matching to fuzzy query, significantly improves the early warning robustness and accuracy, and realizes risk quantification and privacy security.