132 results about "Brute force" patented technology

The invention provides a molecular identity authentication system and method based on DNA origami framework layered assembly. The molecular identity authentication system comprises a disclosed skeleton chain and a plurality of shared staple chains, the shared staple chain comprises staple chains shared by three groups of single bodies and staple chains shared in pairs, and the staple chains are used as secret keys to be distributed to three participants so as to prepare the three groups of single bodies respectively, and then the three groups of single bodies are combined and spliced into a tripolymer with a dot matrix pattern, so that multi-user collaborative layered chain type assembly is realized. According to the molecular identity authentication system based on DNA origami framework layered assembly, the system combination complexity is improved to the information theory security level, so that the biological information security protection capability is improved, and brute force cracking is prevented.

A system includes an originating client platform, a first intermediate client platform, and a bridge platform. A first electronic processor of the originating client platform is configured to generate an authorization request and transmit the authorization request. A second electronic processor of the first intermediate client platform is configured to receive the authorization request and determine whether the authorization request is malicious or not malicious. In response to determining that the authorization request is malicious, the second electronic processor is configured to store the authorization request in a data store, transmit an authorization request denial, and transmit an incident payload including details of the authorization request. A third electronic processor of the bridge platform is configured to receive the incident payload, generate a security profile based on the incident payload, and transmit the security profile to a second intermediate client platform.

The invention discloses a dynamic authentication method for communication equipment and an optical module. The method comprises the following steps: the communication equipment judges whether the optical module is accessed or not; when the communication equipment judges that an optical module is accessed, first information of the optical module is read, and dynamic encryption data is generated according to the first information; the communication equipment writes the dynamic encryption data into the optical module according to a preset format; the communication equipment reads backup verification data generated by the optical module after the dynamic encryption data is written in; the communication equipment checks according to the backup check data, and judges whether the optical module is a legal optical module or not; and the communication equipment records and stores the first information of the legal optical module to complete dynamic authentication. According to the method, a dynamic authentication mode is adopted, the authentication data is dynamically generated while the authentication data is closely connected with key information of the equipment and the optical module, the authentication data is difficult to crack through modes of illegal clone reading, dictionary brute force cracking and the like, the safety is improved, and more guarantee is provided for the network quality.

Example embodiments provide systems and methods for increasing the cryptographic strength of an encryption or message-authentication-code-(MAC) generation technique. According to some embodiments, a MAC may be constructed around a shared secret (such as a random initialization number), thereby increasing strength of the MAC against brute force attacks based on the size of the shared secret. The MAC may be combined with randomized data, and may also be encrypted to further bolster the strength of the code. These elements (shared secret, MAC algorithm, and encryption algorithm) may be employed in various combinations and to varying degrees, depending on the application and desired level of security. At each stage, the cryptographic construct operates on the cyptographically modified data from the previous stage. This layering of cryptographic constructs may increase the strength of the group of contrasts more efficiently than applying any one construct with a larger key size or similar increase in complexity.

To provide an abnormality detection method, an abnormality detection program, and an abnormality detection system that are capable of easily and highly accurately detecting an abnormality in an object to be detected.SOLUTION: A plurality of vector analysis models VM is created by calculating α normal state feature amounts for each divided data BD obtained by dividing normal state record data SRD, extracting two feature amounts from the calculated α normal state feature amounts in a round-robin method, and performing machine learning using as input a plurality of normal state feature amount vectors STV consisting of combinations of the two extracted feature amounts. α detection feature amounts are calculated for each divided data BD obtained by dividing detection record data KRD. Two of the calculated α detection feature amounts are extracted using a round-robin method and a plurality of detection feature amount vectors KTV consisting of combinations of the extracted two is input into the vector analysis model VM, so as to calculate an abnormality score IS for the detection feature amount vectors KTV. A determination whether detection record data KRD is "abnormal" or "normal" is made based on the abnormality score IS.SELECTED DRAWING: Figure 2

Embodiments of the invention describe a computer-implemented method of analyzing an electronic version of a document. The computer-implemented method can include an architecture of machine learning sub-models that performs the global task of translating unstructured and semi-structured inputs into numerical representations that can be recognized and manipulated by a content-analysis (CA) sub-model without relying on brute force analysis. Embodiments of the invention achieve these results by separating the global task into auxiliary tasks and assigning each sub-model to at least one of the auxiliary tasks. The auxiliary tasks can include parsing the unstructured or semi-structured inputs into format types (e.g., lists, tables, figures, text, etc. of a PDF document), extracting features of the parsed document, and performing a computer-based CA on the extracted features. The sub-models are trained in stages and in groups, wherein both the stages and the groupings are based on the complexity of the sub-model's assigned task.

The invention discloses a multi-factor login authentication method and system based on a dynamic authentication chain, and belongs to the technical field of information security, and the method comprises the steps: defining a plurality of authentication factors and an associated authentication chain sequence through extensible configuration data; recording the current authentication step and the completion state of each step through a state machine object; realizing cross-request state synchronization based on a distributed cache storage session state; and intercepting a login request through a section controller, and dynamically driving a multi-factor authentication process according to an authentication chain sequence. According to the invention, flexible and safe identity verification is realized through configurable authentication process and state machine management, the code coupling degree can be reduced, the user experience can be improved, and the brute force cracking risk can be reduced.

The invention discloses an abnormal login detection method and device, equipment and a storage medium, and relates to the technical field of network security, and the method comprises the steps: judging whether the current login time of a current login target user is within a normal login time range corresponding to the target user or not; and / or whether the current login failure times exceed an abnormal login threshold value corresponding to the target user is determined; the normal login time range is a normal login time period obtained by performing density clustering analysis on login time data in historical login data of different users by using a DBSCAN algorithm; the abnormal login threshold value is a threshold value determined by a distribution parameter obtained by performing statistical analysis on login failure times of different users in a preset time window based on historical login data; and if not, determining that the target user has an abnormal login behavior. According to the method and the device, abnormal login behaviors such as login at abnormal time by brute force cracking can be effectively identified and prevented, and meanwhile, the accuracy and the efficiency of abnormal login detection are improved.

The present invention provides an end-to-end panoramic image stitching method, an electronic device, and a storage medium. The panoramic image stitching method comprises the following steps: acquiring pictures captured by multiple cameras of a vehicle; processing the multiple pictures to obtain camera data; and inputting the camera data, preset parameter data and weight data into a trained panoramic image stitching model to generate a panoramic image, wherein the parameter data is a coordinate mapping relationship between the pictures and the panoramic image, and the weight data is weights of the pictures in the panoramic image. The method can obtain a panoramic stitched view in an end-to-end manner by directly inputting camera data, parameter data and weight data into a stitching model, without intermediate transformations and brute-force matching. The method involves few model parameters, requires less inference time and less GPU computing power, achieves relatively high real-time performance, and is suitable for embedded platforms.

The invention provides an SSH brute force attack detection method and device. The method comprises the following steps: constructing a sample array; screening samples in the sample array by using a preset screening strategy to obtain reserved samples; extracting target statistical data of each reserved sample, and performing threshold judgment according to the target statistical data; and judging an SSH brute force cracking result according to a threshold judgment result. According to the method, a plurality of statistical characteristics, calculation characteristics and threshold value judgment methods are combined and used for detection, detection depending on single frequency or port characteristics is avoided, false alarms are reduced, and the detection accuracy is improved.

The invention discloses a network information security encryption method and system. The method comprises the following steps: converting network information data into a decimal sequence and constructing a matrix to be encrypted; based on uniformity parameters of elements in the matrix to be encrypted and feature difference values of adjacent rows, generating a reconstructed combined row set, and determining a basic unit row sequence and a basic unit column sequence through neighborhood complexity analysis; and performing multi-round replacement encryption on the basic unit rows and columns in combination with a dynamic random number generation algorithm. According to the network information security encryption method and system, dynamic matrix recombination is adopted, based on data uniformity parameter and neighborhood complexity analysis, self-adaptive adjustment of encryption granularity is achieved, compared with traditional fixed matrix encryption, brute force cracking resistance is improved, asymmetric fusion encryption is achieved, each round of replacement parameter is dynamically generated by an RSA public key, and the security of the network information security encryption system is improved. The AES-CBC mode is combined to form multi-layer protection, and the success rate of resisting man-in-the-middle attack is reduced.

The invention discloses a power grid upgrading mirror image data transmission method and system, and the method comprises the steps that a transmitting end generates a first key sequence and a second key sequence based on a preset iteration algorithm and two different pieces of initial iteration information; the sending end encrypts the power grid upgrading mirror image data based on the first key sequence and a first encryption algorithm to generate a first layer of encrypted data sequence; the sending end encrypts the first-layer encrypted data sequence based on a second key sequence and a second encryption algorithm to generate a second-layer encrypted data sequence; and the receiving end performs hierarchical decryption on the second-layer encrypted data sequence based on the first key sequence, the second key sequence, the first encryption algorithm and the second encryption algorithm to obtain the power grid upgrading mirror image data. Through the technical scheme of the embodiment of the invention, safe transmission of the power grid upgrading mirror image data is realized, the possibility that an encryption algorithm is cracked by brute force can be reduced, the transmission safety of the power grid upgrading mirror image data is improved, and the operation safety of a power grid is ensured.

Systems, computer program products, and methods are described herein for identification and verification of brute force attacks using hash signature segmentation and behavior clustering analysis. The present invention is configured to receive a plurality of access attempts and an associated plurality of hash values; determine a failure request load based on the plurality of access attempts; determine whether the failure request load meets a failure threshold, wherein, in an instance where the failure request load meets the failure threshold, separating the plurality of access attempts associated with the failure request load into a plurality of hash clusters; generate a behavior cluster for each hash cluster based on shared behavior data of the plurality of access attempts; and determine, based on the behavior cluster for each hash cluster, a likelihood of misappropriation for each access attempt of the plurality of access attempts.

A method is provided for detecting proximity between objects using threshold based clustering. The method includes receiving object data of a plurality of objects in a space to be monitored, from one or more data capturing devices disposed in a space, clustering the object data into one or more clusters, based on a predetermined threshold distance, thereby reducing the search space, and processing the one or more clusters using brute force to identify the plurality of objects which lie within the predetermined threshold distance of each other, thereby identifying the plurality of objects that are at risk of collision.

The invention relates to the technical field of network intrusion detection, and discloses an RDP brute force cracking detection method and device, and the method comprises the steps: obtaining transmission data, and determining whether the transmission data is an RDP data flow or not through a preset method; when the transmission data is the RDP data stream, determining an RDP protocol version corresponding to the RDP data stream; when the RDP protocol version of the RDP data stream is a first version, detecting whether brute force cracking exists between an RDP server and a client by adopting a first detection method; and when the RDP protocol version of the RDP data stream is a second version, detecting whether brute force cracking exists between the RDP server and the client by adopting a second detection method. According to the method provided by the embodiment of the invention, the corresponding detection method is determined according to the version of the RDP protocol, and whether brute force cracking exists between the RDP server and the client can be more easily detected, so that the accuracy of RDP brute force cracking detection is improved.

The invention discloses an identity verification method and system, and the method comprises the steps: generating a verification result through a verification algorithm after an identity verification server receives an identity verification request; when the verification result is successful, generating a legal identity certificate; and when the verification result is failure, generating a counterfeit identity certificate, and generating at least one of counterfeit reasonable data, counterfeit reasonable authority and counterfeit reasonable abnormity. The method has the core advantages that fake reasonable information is returned when verification fails, so that illegal visitors cannot deduce correct identity information by using failure feedback and cannot distinguish the authenticity of acquired data, authority or abnormal prompts, illegal behaviors such as library collision attacks and brute force cracking are effectively avoided, and the safety of the visitors is improved. The defect that key information is leaked due to failure feedback in the traditional identity verification technology is overcome, and the security of system data and functions is remarkably improved.

The present invention provides a web application protection method, system, and computer-readable storage medium. The method comprises: a front-end sending a data request to a back-end, the data request carrying a uniform resource locator (URL) and parameter information; upon receiving the data request, the back-end parsing the parameter information to obtain corresponding parameter values; and the back-end generating corresponding parameter images based on the parameter values, and saving the parameter images to a preset database. By graphically representing parameter values, the present invention can avoid web application risks caused by inserting malicious code into parameters, effectively defend against attacks such as cross-site scripting, SQL injection, file uploads, and brute force attacks, thereby improving the security of web applications and achieving comprehensive protection for web applications. This addresses the problem that existing web application protection methods lack comprehensive protection for web applications.

The invention discloses a router Wi-Fi anti-brute force cracking function test method and device and a computer readable storage medium, and the method comprises the steps: carrying out the first simulation access and the second simulation access of a to-be-tested router Wi-Fi according to a preset first parameter and a preset second parameter, the Wi-Fi connection password in the first parameter is different from the Wi-Fi password of the router, and the Wi-Fi connection password in the second parameter is the same as the Wi-Fi password of the router; and generating an anti-brute force cracking function test result of the router Wi-Fi according to the first access state of the first simulation access and / or the second access state of the second simulation access. According to the invention, a self-adaptive testing scheme for the anti-brute force cracking function of the router Wi-Fi is realized, the testing efficiency and the testing precision are improved, the security and protection requirements of the router Wi-Fi are met, the testing steps are simplified, and the cost of manpower and material resources is reduced.

Methods, systems, and devices for access management are described. A software platform may identify devices of a botnet based on a cluster score associated with a device characteristic. For example, the software platform may receive a request from a device to access an application. The software platform may determine a cluster score for the characteristic of the device. The cluster score may be based on a link between the device and a list of devices (e.g., devices of a botnet). If the cluster score satisfies (e.g., exceeds) a cluster score threshold, the software platform may deny the access request. In some examples, the cluster score may be determined using machine learning techniques. Based on determining the cluster score, the software platform may efficiently identify devices of the botnet and prevent brute force attacks, which may improve reliability of access for users of the application.

The application discloses a kind of mobile terminal operating system information protection methods based on hardware certificate, comprising the following steps: one, in boot partition and recovery partition using asymmetric encryption algorithm write mutual certificate system of confirmation;Two, whether through boot partition or recovery partition start is needed to ensure the integrity of another partition.Current mobile terminal operating system can be read by the system partition file in the way of writing the third party system that can be started in recovery partition, there are mobile terminal operating system files directly read, brute force cracking user password authentication and other security problems, all the startable partitions of the system are introduced into the certificate using asymmetric encryption algorithm in the application, only the certificate and the partition are complete, the system can normally run, thereby preventing the system from being maliciously tampered with, ensuring that the user cannot obtain system root permissions and cannot modify system files, with higher security and convenience.

The invention relates to the technical field of image processing, in particular to an MLCC metallographic microscopic image splicing method and system for repeated textures, and the method comprises the following steps: S1, obtaining a first image and a second image; s2, carrying out exhaustion matching by adopting a violent matcher to obtain an initial matching point pair set; s3, performing mismatching elimination processing on the initial matching point pair set to obtain a final inner point matching set; s4, calculating an affine transformation matrix between the first image and the second image; s5, aligning images in the image sequence in the affine transformation matrix by adopting a chain accumulation transformation mode to obtain a third image, and performing exposure compensation processing on the third image to obtain a fourth image; s6, an optimal path search algorithm is adopted to determine a splicing seam with the minimum visual cost in the overlapping area of the fourth image, feathering fusion is carried out along the splicing seam, and a fifth image is obtained; s7, cutting the fifth image to obtain a target spliced image; and the problem of matching fuzziness caused by repeated textures is effectively solved.

This technology is applied in the field of network security. This invention provides a method and apparatus for defending against SSH brute-force attacks through log analysis. The purpose of this invention is to solve the problem of inefficiency in existing security defense measures when they cannot cope with brute-force attacks. The main solution includes: acquiring security logs and system logs from monitoring devices and providing them to the perception module; acquiring the attacker's source IP address, username, and time; the perception module recording the attack source IP address, username, and time information in memory and performing statistics within a set time period; querying third-party professional threat intelligence to return the attack source IP address attribution information and threat score; the log threat analysis module defining the danger level of the brute-force threat based on the attack source IP address and threat score; and implementing different corresponding response measures based on the risk identification results of the threat analysis module.

The invention discloses a low signal-to-noise ratio ADS-B (Automatic Dependent Surveillance-Broadcast) signal coherent receiving method based on an expectation maximization algorithm, which belongs to the technical field of coherent receiving methods, and comprises the following steps of: realizing accurate synchronization of ADS-B signals through energy accumulation and matched filtering, and then estimating and compensating frequency offset and phase offset through the expectation maximization algorithm, and finally, decoding and brute force error correction are carried out. According to the method, information bits behind a leading head are fully considered, the value probability of each bit is analyzed, and actually transmitted data information is taken as a hidden variable, so that the estimation precision of frequency offset and phase offset is greatly improved, the sensitivity index of a satellite-based ADS-B receiver can be effectively improved, the sensitivity of the receiver can reach-102dBm under 90% of correct decoding probability, and the accuracy of the receiver is improved. And meanwhile, the processing delay of the frequency phase offset estimation is less than 50 us, so that the coherent receiving method with limited resources can be used on the small cubesat more easily.

The present application belongs to the technical field of encrypted transmission, and particularly relates to a kind of encrypted processing method of geographic information data, comprising: constructing different levels of encryption keys according to role permissions, each level of key contains a plurality of groups of chaotic mapping parameters, and the next level contains all parameters of the previous level. Each group of chaotic mapping parameters is used to encrypt geographic images, and the results of each group are used to form the ciphertext of the corresponding level. The specific process is as follows: S1, generate a chaotic sequence; S2, select pixel points in the image without replacement based on the chaotic sequence, encode the selected pixel points using AMBTC, obtain high quantization values, low quantization values, and binary masks, and concatenate the corresponding binary numbers to form the encoding result; S3, repeat S2 until all pixels are selected, and collect the encoding results to form the encryption result under this group of parameters. The present application combines permission management and chaotic characteristics, realizes hierarchical encryption of geographic images, and can resist statistical analysis attacks and brute force attacks.

The present invention discloses a simulated interview method based on an AI big model, which relates to the technical field of simulated interviews. The present invention collects the recorded data uploaded by the authorized user after each simulated interview, and analyzes the data by a fuzzification processing module. During the analysis, the recorded video data of each question text contained in the recorded data is fuzzified frame by frame, so that the blurring of each frame of image is reversible. On the one hand, the targetedness of the blurring is ensured while the degree of the blurring is guaranteed, and the blurring strength of different pixel points is dynamic. Compared with the traditional blurring algorithm, the reversibility of the blurring is achieved. On the other hand, the mean is calculated for each pixel point in the image, so that the encryption result of each frame of image is unique, which effectively resists brute force cracking, and only the face area is fuzzified. Compared with encrypting the entire recorded data, computing resources and processing time are saved.

The application provides a DFA algorithm-based card bin matching method and system, and relates to the technical field of Internet. The method comprises the following steps: constructing a card bin library, and locally caching database card bin information; storing the information into the local cache; when a service is started and initialized, first querying the database card bin information data to obtain a list set; traversing the set to take the card bin therein as a key and the entity data as a value; taking the first 6 bits of the card bin with 6 bits or more as the key, and directly taking the card bin with less than 6 bits as the key; first judging whether there is a key; when there is no key, taking a newly created list set as a value, and putting the card bin into the card bin library in a reverse order according to the length of the card bin; when there is a key, putting the card bin data into the list set, and storing the card bin into the card bin library in a reverse order according to the length of the card bin. The method can realize accurate and efficient matching of the card bin, and avoids the problem of removing the database brute force query.

The invention discloses a sun multiband / sequence image registration method based on deep learning. The method comprises the following steps: respectively extracting key point thermodynamic diagrams and intermediate feature representations of a sun band reference image and a to-be-registered image by using a key point extraction model; local maximum values in the key point thermodynamic diagrams of the sun band reference image and the to-be-registered image are searched through local maximum value operation; comparing the local maximum value with a preset pixel threshold value, and taking the pixel greater than the pixel threshold value as a key point; a descriptor extractor is used for extracting descriptors of key points of a sun band reference image and an image to be registered, and then a bidirectional matching brute force algorithm is used for determining a most matched key point pair; for the most matched key point pair, a random sample consistency algorithm is adopted to determine transformation parameters of image registration; and transforming the to-be-registered image according to the transformation parameter to obtain a registered image. The method provided by the invention has a relatively good effect in image registration of the sun active area and the quiet area, and can be used for image registration of different wave bands at the same time.