6 results about "Attack prevention" patented technology

The invention discloses a multi-person shared health detection device capable of accurately recognizing user identity based on sound. The device comprises a microphone array, a physiological parameter sensor, a processor and a memory. The method comprises the following steps of: performing front-end processing on a collected voice signal to obtain an effective voice segment; extracting a voiceprint embedding vector by using a deep neural network; comparing the vector with a local voiceprint template library to obtain a highest score and candidate identities; carrying out living body and playback attack authenticity discrimination by analyzing multi-dimensional acoustic features and utilizing a classification model; and binding and associating the identity label with the health data collected by the sensor when the identity label is judged to be a real living body and the similarity score meets a judgment condition. The method has the advantages of high noise resistance, attack resistance and end-side low delay, supports offline work and model increment self-adaption, is suitable for families, communities, medical institutions and other scenes, and effectively improves the use convenience and data security of shared health equipment.

The application discloses a kind of attack prevention high-precision face recognition model training method, system, terminal and medium, the method includes the following steps: S1: input n original face data and obtain loss function L1 for training;S2: collect m face data, based on m original face data, reorganization obtains m / 2 reorganization face data;S3: the cosine similarity of reorganization face data and its corresponding two original face data before reorganization is calculated, and the average of the two cosine similarities obtained is obtained, obtains m / 2 average, S4: whether m / 2 average value corresponds to meet threshold value, if yes, corresponding average value is counted as loss value, if no, corresponding loss value is 0;S5: calculate loss value total value L and L2=L / m / 2;S6: loss function L1 and L2 are superposed to obtain the final loss function L 总 .

This invention discloses a method and device for full hand vein biometric recognition to prevent spoofing attacks, relating to the fields of full hand vein recognition, biometric information recognition, and identity authentication. The method includes: Step 1, image acquisition and detection: acquiring a frontal hand image covering the palm and finger areas, ensuring the presence of a palm and a real living person in the frontal hand image; Step 2, ROI extraction: extracting the palm vein ROI and the multi-finger ROI; Step 3, feature extraction: extracting palm vein features and features of the four fingers, and generating corresponding feature hash codes; Step 4, feature matching: first matching the palm vein features, then matching the four finger features; similarity comparison is achieved by calculating the Hamming distance between the feature hash codes; Step 5, score fusion: calculating the matching scores for the palm vein features and the four finger features respectively, then performing Tanh normalization on the matching scores, and finally fusing the normalized matching scores to obtain the final recognition result.

In an embodiment, a method includes identifying, by a first device, a level of degradation. The method also includes transmitting, by the first device during a communication phase, a first signal with a first signal quality based on the level of degradation. The method further includes transmitting, by the first device during a second communication phase, a second signal with a second signal quality. The second signal quality may be greater than the first signal quality.

This invention discloses an attack prevention method based on two-phase proof-of-work, comprising the following steps: setting a first difficulty coefficient D1; determining the validity of the requester's first-phase proof-of-work based on the first difficulty coefficient D1 and the message body msgl and number n1 generated by the requester; if invalid, refusing to provide service to the requester; if valid, dynamically adjusting the difficulty of the second-phase proof-of-work according to the system load, requiring the requester to perform the second-phase proof-of-work; and providing the corresponding service to the requester after the requester successfully completes the second-phase proof-of-work. This method avoids attacks on the service provider by the requester through a large number of spam requests and spam messages, improves system security, enhances user experience, optimizes resource allocation, and strengthens system scalability.