18 results about "Signature detection" patented technology

The invention discloses a signature recognition method and device, a storage medium, electronic equipment and a product, and the method comprises the steps: carrying out the extraction of a signature region in a file through a detection sub-model, and obtaining a first image; performing enhancement processing on the first image by using the preprocessing sub-model to obtain a second image; and obtaining a target signature feature in the second image through the identification sub-model, and determining the similarity between the target signature feature and a preset signature feature in a database, so as to determine a target identification result of the signature region based on the similarity. By adopting the technical scheme, the problem that the signature detection and recognition precision cannot be effectively improved when a complex background and a low-quality image are processed is solved. And furthermore, through cooperative work of the detection sub-model, the enhancement sub-model and the identification sub-model, a signature region is accurately positioned from the document, the image quality is optimized, and signature features are compared and analyzed, so that the authenticity of the signature is efficiently judged.

The disclosure includes a system and method for fake signature detection including identifying, using one or more processors, within a document image a signature portion, the signature portion representing a signature; applying, using the one or more processors, one or more fake signature detection models to the signature portion; determining, using the one or more processors and the one or more fake signature detection models, whether the signature represented in the signature portion is a fake signature; and presenting, using the one or more processors, the determination.

The invention discloses a legal document fall positioning and quality inspection method and device based on semantic understanding, and relates to the technical field of legal review, and the method comprises the steps: analyzing electronic document data, extracting text content, associating the text content with corresponding coordinate metadata, and generating multi-modal document data; performing deep semantic and structural analysis on the multi-modal document data, extracting a text sequence, executing natural language analysis and semantic analysis, obtaining a phrase role labeling result, judging a termination position, and obtaining a semantic boundary; based on the semantic boundary and the coordinate metadata, performing retrieval positioning on the multi-modal document data, extracting coordinate text data and page evidence image segments, obtaining a structured entity and segmented signature blocks through entity recognition and signature detection, and constructing a signature element map; according to the method, automatic verification and accurate fund positioning of the document are realized, the processing efficiency is improved, manual intervention is reduced, and the method is widely applicable to automatic examination and compliance inspection of the electronic document.

The invention provides a handwritten signature detection method and device and an electronic product, and the method comprises the steps: carrying out the joint prediction: predicting an input handwritten signature image through a detection head, outputting the parameters of a predicted rotating rectangular frame and a predicted horizontal rectangular frame, and carrying out the consistency constraint; generating a corresponding Gaussian attention map based on the predicted rotating rectangular frame parameter; carrying out point-by-point multiplication on the Gaussian attention map and an originally input handwritten signature image, and extracting a region of interest; the region of interest is sent to a classification head, a three-classification task is completed, three classification probability values are output, a rotating rectangular frame with the classification probability of the handwritten signature larger than a set threshold value is a detected handwritten signature frame, finally, redundant rotating rectangular frames are removed through maximum suppression, and a detection result is obtained. According to the method and the device, the problem of handwritten signature detection under target inclination, direction variation and non-signature handwritten signature interference in the prior art can be effectively solved.

The invention discloses a value network-oriented block chain consensus system and method, electronic equipment and a storage medium, and belongs to the technical field of block chains. Comprising a view initialization and leader selection module for determining a leader of a current view from an effective verifier set under the condition that each view starts; the fast path consensus module is used for detecting a network state, initiating a proposal of a new block by a leader under the condition that the network is in a synchronous state and has no Byzantine fault, and submitting the new block to the block chain according to a voting result of each copy node in the effective verifier set for the proposal; and the double-signature detection and punishment module generates and broadcasts the double-signature evidence of the replica node under the condition that the same replica node is detected to sign different blocks at the same height, and moves the replica node out of the effective verifier set. According to the method, the efficiency is maximized under an ideal network, the robustness is maintained under a non-ideal environment, and the delay under unnecessary conditions is reduced.

Disclosed, in one general aspect, is a computer network security threat monitoring system that includes storage to receive and store executable malware binary files and commonly used binary files certified as malware free. It also includes a search tool to accesses the malware binary storage and select a subset of the stored executable malware binary files for characterization. An iterative pattern detection engine iteratively derives a set of malware identification patterns that are found in successive portions of the selected subset of the stored executable binary files but not in the stored benign executable binary files. An optimized pattern selection engine selects an optimized subset of these malware identification patterns, with the patterns in the optimized subset together matching every one of the selected subset of the stored executable binary files but none of the stored benign executable binary files.

Computer-implemented methods, systems and program products extending traditional cloud-centric intrusion detection to edge networks. NIDPS is decentralized between the edge and cloud. Edge gateways equipped with NIDPS agents capture packets of network traffic and pre-process the data. Pre-processing output is compressed and sent to cloud intrusion detection services equipped with latest available rules and signatures. As cloud IDS detects security threats using rules and signatures, NIDPS agents are alerted and switched from “lazy mode” to “preventative mode.” While in preventative mode, NIDPS agents inspect packets of network traffic in accordance with the rules and signatures associated with the detected security threat, dropping packets that trigger the rules and signatures, while still compressing and transmitting other packets to cloud IDS for analysis. Once no active rules or signatures are enforced for pre-set or configured periods of time, NIDPS agents revert back to “lazy mode” to conserve network resources.

A technique includes accessing file write operations that are provided by an operating system of a computer system. The file write operations are associated with a file. The technique includes determining an observed signature of the file based on the file write operations; and based on the observed signature, detecting an issue that is associated with the file. A responsive action is initiated in response to the detection of the issue.

Data processing arrangement (100), comprising: a processor (101) designed to execute a computer program that includes multiple program instructions; a signature detection arrangement (102) designed to detect a signature of the program instructions executed by the processor (101); a memory (103) that stores a reference signature predetermined for the computer program; wherein the processor (101) is designed, when executing a program instruction of the multiple program instructions which is a conditional branch into a branch and specifies the next program instruction of the multiple program instructions to be executed, to provide the signature detection arrangement (102) with information about the specification; the signature determination order (102) is designed to take the information into account when determining the signature where the information about the indication is the information that the branch is to be taken, and the signature determination order (102) is designed to take the information into account in such a way that taking the information into account negates the difference in the updates of the signature because the program instructions are skipped or executed as a result of taking the branch or where the information regarding the indication is the information that the branch is not to be taken, and the signature determination order (102) is designed to take the information into account in such a way that taking the information into account negates the difference in the updates of the signature because the program instructions are skipped or executed as a result of not taking the branch; and a detector (104) designed to check whether the determined signature is equal to the reference signature when part of the computer program has been executed or when the computer program has been fully executed.

This application relates to the field of Internet of Things (IoT) security, and provides an IoT intrusion detection method, apparatus, device, and readable storage medium. The method is applied to an IoT intrusion detection system including IoT nodes; the method includes: upon detecting a registration request from a new node, calculating an aggregate trust value for the new node through the IoT nodes, where the IoT nodes include general nodes and dedicated nodes; if the aggregate trust value is greater than or equal to a first threshold, performing signature detection on the new node through a dedicated node to obtain detection information; if the trust value of the dedicated node sending the detection information is greater than or equal to a second threshold, performing network attack detection on the new node; and updating the trust ledger of the IoT nodes when a network attack is detected. Updating the trust ledger of the IoT nodes when a network attack is detected in the IoT promotes trust between IoT nodes, thereby effectively identifying network attacks from malicious nodes.

The application discloses a signature recognition technology based on rhythm characteristics, obtains sample signature discrete track points and verification signature discrete track points, adopts speed logarithmic segmentation to obtain sample signature strokes and corresponding verification signature strokes, calculates rhythm characteristics of the sample signature strokes and the corresponding verification signature strokes, carries out distance measurement according to the rhythm characteristics to obtain total rhythm characteristic distance, and thus determines whether the verification signature is a signature of the signer or a copied signature. The application proposes rhythm characteristics with strokes as basic granularity, does not depend on a large amount of training data, is not limited to any language, character or handwriting form, processes any type of signal wave, satisfies translation stretching, rotation and sampling mode invariance of signature track based on a more scientific and reasonable normalization mode and measurement mode, supports cross-device verification, and can efficiently and accurately distinguish between copying and imitation.

The invention relates to the technical field of data encryption, and discloses an intelligent encryption method, device and system for application sensitive data. Comprising the following steps: executing a secret key mixing operation of a static secret key and a dynamic secret key in a coding encryption environment to obtain a mixed secret key result, and further executing corresponding encryption and coding format conversion operation on target application data and the mixed secret key result, signature detection and integrity verification operations are executed in the operation decryption environment, and corresponding decryption and decoding format conversion operations are executed on the target format ciphertext data, so that the comprehensiveness and rationality of an intelligent encryption and decryption mode of the application sensitive data are improved; furthermore, the diversity, pertinence and independence of the encryption operation environment and the decryption operation environment of the application sensitive data are improved, so that the encryption and decryption accuracy and the encryption and decryption reliability of the application sensitive data are improved, and the use safety and the management reliability of the application sensitive data are further improved; and the management accuracy and management efficiency of the application sensitive data are improved.

Systems, apparatus and methods for detecting materials in a target area are provided herein. The system includes an imaging device, and a computing device. The imaging device is configured to collect input data including hyperspectral image data of the target area. The computing device is configured to receive the input data. The computing device is further configured to analyze the input data using a hyperspectral signature detection model trained to detect at least one spectral signature in the input data indicative of a potential threat, the hyperspectral signature detection model comprising a machine learning based model configured to receive the input data and generate annotated data as an output. At least a portion of the analyzing includes pattern of life algorithms. The computing device is further configured to provide the output to a user device.

A method of authenticating a user device in providing access to a computer resource, the method includes identifying a device fingerprint record stored in an access log. The method includes produce, based on the device fingerprint record, a digital signature includes one or more session characteristics. The method includes determining, by a processing device from the digital signature, a root signature pattern associated with the one or more session characteristics. The method includes identifying an access request for a computer resource as an unauthorized access based on the device fingerprint record and the root signature pattern.

This utility model belongs to the field of tobacco production technology and discloses a stem stick detection device. The stem stick detection device includes a support, a collection mechanism, a collection mechanism, and a recycling mechanism. The support is disposed on a supporting surface; the collection mechanism is connected to the support and includes an interconnected collection channel and a collection chamber. The end of the collection channel away from the collection chamber is connected to a discharge port to allow the stem sticks to enter the collection chamber, which is made of a transparent material; the collection mechanism is connected to the support and located on one side of the collection chamber. The collection mechanism is used to photograph and collect information about the stem sticks inside the collection chamber and to detect the presence of foreign matter; the recycling mechanism includes a first driving component and a recycling box. The output end of the first driving component is connected to a sealing plate at the bottom of the collection chamber. The recycling box is located below the collection chamber. The first driving component can drive the sealing plate to tilt towards the recycling box so that the stem sticks can fall into the recycling box. This device can automatically complete the loading and unloading of stem sticks and realize automatic sampling and detection of stem sticks.

This application provides a threat detection and response method, apparatus, electronic device, and storage medium. The method includes: acquiring a real-time data stream; inputting the real-time data stream into a preset deep learning model to obtain a threat detection result for the real-time data stream; and, if the threat detection result indicates the existence of a threat and determines that the threat detection result meets a preset threat severity, executing a response strategy related to the real-time data stream. This application achieves the purpose of attack detection, achieving the technical effects of being signature-free, having high detection accuracy, being able to handle unknown threats, and having a fast response speed, thus solving the problems existing in related technologies.

A method of authenticating a user device in providing access to a computer resource, the method includes: extracting a plurality of device fingerprint records from an access log, each of the device fingerprint records associated with an unauthorized access of a computer resource; from each of the plurality of device fingerprint records, extracting a digital signature, each of the digital signatures comprising a plurality of session characteristics; determining, by a processing device from the digital signatures, a root signature pattern, the root signature pattern comprising a combination of values of one or more of the plurality of session characteristics; and identify a subsequent access request for the computer resource as an unauthorized access based on a comparison of a device fingerprint associated with the subsequent access request and the root signature pattern.