Search

The method of detecting the whole tampered image increases many unnecessary calculations. In order to reduce the computational complexity and further improve the detection accuracy, this paper proposed a copy-move forgery detection method based on improved saliency map and local feature matching. Firstly, it combined the gradient of image to improve the saliency map, and separated the local salient regions containing high texture information of the image. Secondly, it only used SIFT（Scale Invariant Feature Transform） algorithm to extract feature points in this local area. Then, it adopted density clustering and two-stage matching strategy for images with low saliency, and adopted the strategy of superpixel segmentation and salient block feature matching for images with high saliency. Finally, it combined PSNR and morphological operations to locate the tampered area. Experiments on two public datasets show that the average detection time of this method is less than 10s, and the average detection accuracy is greater than 97%,which are better than the compared methods. The experimental results show that this method can greatly reduce the detection time, effectively improve the detection accuracy, and has good robustness to geometric transformation and post-processing operations. [ABSTRACT FROM AUTHOR]

Ginseng is one of the rare traditional Chinese medicine in China, with a long history of application. There are many prescriptions of ginseng recorded in ancient traditional Chinese medicine books, yet the name, origin, place of origin, collection and processing, and quality identification of ginseng have changed with the changes of the times. In this paper, the origin and development of ginseng is re-examined, which is convenient for clinical clarification of confusion and forgery. And the modern clinical research of ginseng is summarized to provide reference for the inheritance, use and resource development of ginseng. [ABSTRACT FROM AUTHOR]

AI face-swapping technologies, such as DeepFake, bring negative effects in daily life. However, existing face forgery detection algorithms have weak robustness and lack interpretable ability. Aiming at the above problem, this paper proposes a face frequency-domain watermarking algorithm (Face-FW) which combines Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Single Value Decomposition (SVD). To detect face forgery and verify the attribution of the original face, the algorithm extracts face features from a face image, and then compresses and encrypts them into a binary watermarking. Finally, Face-FW embeds the generated watermarking to frequency domain of the image. At the same time, the algorithm uses a dynamic feature fusion algorithm to broaden the scope of applications. This paper generates test sets CASIA-DF and IMDB-DF by embedding watermarking meanwhile tampering the faces in the selected standard face image datasets CASIA-FaceV5 and IMDB-WIKI. Experimental results demonstrate that Face-FW reaches detection success rates of 97.6% and 96.9% on the test sets respectively and achieves a better performance than compared methods. Moreover, the algorithm can provide face authentication for face images according to the non-integrated watermarking, showing strong robustness and interpretability. [ABSTRACT FROM AUTHOR]

On account of the problem that forgery target and source of digital image copy-move manipulation cannot be distinguished, this study improves the similarity matching algorithm and uses non-local self-attention mechanism to solve the classification problem of copy-move forgery source and target areas, under the premise that manipulated regions are detected. The overall framework is a dual-branch detection network. The main branch uses the classic U-net to segment the pixel of forgery regions, and the auxiliary branch uses the siamese network to extract features and calculate the autocorrelation to separate the forgery targets and source area pixels. Finally, three-categories results can be predicted by end-to-end training after fusing two branches. The experiment result shows that the pixel-level classification accuracy of the proposed algorithm when detecting the localized target area reaches 80.47%, and the F1 value and accuracy are better than the compared algorithm. The visualization results and robustness experiments also show that the proposed algorithm has excellent generalization performance. [ABSTRACT FROM AUTHOR]

Aiming at the problems that the Raft algorithm cannot resist the attacks of Byzantine nodes and the logs are easy to tamper with, this paper proposes an RB-Raft (Resist Byzantine-Raft) algorithm that resists Byzantine nodes. Firstly, this paper uses the method of hash chain to iteratively hash each log. At the same time, verification of the log through the dynamic verification mechanism, so that the malicious behavior of the leader node has a certain fault tolerance rate, which solves the problem of log forgery and verification. Secondly, this paper proposes a "Legacy" mechanism based on threshold encryption, which makes it legal for Candidate nodes to pull votes. This mechanism can prevent Byzantine nodes from randomly the attack of pulling votes to replace leader nodes, and solves the problem that Byzantine nodes affect the system consistency. The experimental results show that the proposed RB-Raft algorithm has the ability to resist Byzantine nodes, and its log recognition rate can reach 100%. At the same time, compared with PBFT, the consensus latency of the algorithm in this paper is reduced by 53.3%, and the throughput is increased by 61.8%. The algorithm proposed in this paper is suitable for consensus in untrusted consortium chains. [ABSTRACT FROM AUTHOR]

Nowadays intelligent power production uses electric power images widely. However, due to the development of image editing software, some power images are maliciously tampered, which seriously affects the power production process. In order to solve this problem, this paper proposed a dual-channel CenterNet model for power image splicing forgery detection. The color channel extracted the obvious visual features of the image. The stage-analysis channel explored the noise feature. At the same time, the algorithm used a feature fusion module based on attention mechanism, it integrated the dual-channel features to enhanced the feature recognition ability. Experiments show that the model can get better detection performance and has practical significance in the forgery detection application of power images. [ABSTRACT FROM AUTHOR]

In order to increase the accuracy rate of signature verification for higher-level forgery, this paper developed a dynamic signature verification method based on timing feature fusion. First, during the writing process, it created a dynamic timeline, and extracted two timing features, the handwriting pressure and writing speed. Then it designed a fusion model of timing features based on the data of the features above. This paper calculated the similarity between the test signature and the sample signature by a similarity measure method of multidimensional spatial model. Finally, it realized signature verification by the analysis of similarity. The experiments show that the proposed algorithm has the advantages of high accuracy rate and good universality. [ABSTRACT FROM AUTHOR]

In the scenario of wireless generation of three common radio frequency identification keys, the security key problem of replay attack, key forgery attack and RFID tag identity ID leakage and the lack of algorithm theory are found in the corresponding key generation algorithms. This paper designed a more secure RFID-based key generation algorithm based on activation flag. The improved algorithm only combined multiple super-lightweight bit operations to construct a secure algorithm framework, which reduced cost and improves efficiency. It used the activation flag AckBit mechanism and the freshness mechanism to resist replay and key forgery attacks. Through the complete GNY logic proof process and safety comparison analysis, it proved the safety and feasibility of the target algorithm. Finally, this paper presented the comparison of the tag cost between the original algorithm and the improved algorithm, which shows that the improved algorithm has higher security under the condition of satisfying the low cost. [ABSTRACT FROM AUTHOR]

This paper proposed a (t,n) threshold quantum secret sharing scheme by means of d-dimensional entanglement swapping. The proposed scheme executed t times of d-dimensional entanglement swapping, which aggregated secret shadows into F, particle of the reconstructor. Finally, the reconstructor measured this particle to reconstruct the original secret. Security analysis shows that the proposed scheme can resist intercept-resend. entangle-measure. collusion and forgery attacks. By comparison with other similar schemes in performance, the proposed scheme is more flexible, practical and universal. In addition, its total overheads of computation and measurement are lowest in current similar quantum secret sharing schemes. [ABSTRACT FROM AUTHOR]