作者机构：
[Lujie Wang; Xiyu Sun; Chenchen He] College of Computer Science and Technology, Hengyang Normal University, Hengyang, China;Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang, China;[Zhong Chen] College of Computer Science and Technology, Hengyang Normal University, Hengyang, China<&wdkj&>Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang, China
通讯机构：
[Zhong Chen] C;College of Computer Science and Technology, Hengyang Normal University, Hengyang, China<&wdkj&>Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang, China
关键词：
Image encryption;Region of interest;Lifting scheme;Chaos;NMS;Object detection
摘要：
Securing image transmissions has become critical as the demand for image sharing and storage grows. In some commercial uses, in order to achieve a balance between encryption security and efficiency, some researchers have tried to encrypt only the region of interest of the user in the image. In order to accurately encrypt region of interest images, this paper proposed a region of interest image encryption algorithm based on lifting scheme and object detection. The algorithm automatically identifies the region of interest in the image and encrypts it securely and effectively. Firstly, the region of interest in the image is detected using the object detection model, and the non-maximum suppression algorithm is modified to solve the problem that the detection box outputted by the object detection model does not completely contain the region of interest. Then the existing pixel extraction method for region of interest images is improved to extract the pixels from the region of interest images at a faster speed, which improves the overall efficiency of the algorithm. Finally, based on the thought of wavelet lifting transform, combined with chaotic system, a two-layer hybrid lifting scheme encryption algorithm is proposed to encrypt the extracted pixels. Experimental results and security analysis show that the algorithm proposed in this paper can effectively protect all objects at once with high security.
通讯机构：
[Chen, Z ] H;Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang 421002, Peoples R China.;Hunan Prov Key Lab Intelligent Informat Proc & App, Hengyang 421002, Peoples R China.
关键词：
Image encryption;Hachimoji DNA coding;DNA computing;six-dimensional hyperchaotic system
摘要：
With the increasing awareness of privacy protection, people pay more and more attention to strengthening the security of image data transmitted over the network. Therefore, this paper designs a chaotic image encrypting algorithm based on dynamic Hachimoji DNA coding and computing to protect images. The Hachimoji DNA coding method provides richer coding rules to dynamically encode images than the traditional DNA coding method, improving the complexity and security of the encryption algorithm. First, the original image is rearranged and encoded with the dynamic Hachimoji DNA coding method according to the sorting and encoding controller sequence generated by a six-dimensional hyperchaotic system. Second, various DNA operations are performed on the encoded image. Among these operations, we not only use the common operations but also propose a new DNA operation called bitwise inversion. Finally, the DNA image is decoded using the dynamic decoding method to obtain the encrypted image. Experiments demonstrated that the image encryption algorithm has a good security effect and can effectively resist common attacks.
通讯机构：
[Chen, Z ] H;Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang 421002, Peoples R China.;Hunan Prov Key Lab Intelligent Informat Proc & App, Hengyang 421002, Peoples R China.
关键词：
color image encryption;hyperchaotic system;region of interest;security analysis
摘要：
The significance of safeguarding the security of image information has escalated significantly, owing to the exponential proliferation of digital images containing sensitive information being disseminated on the Internet. In this paper, we first propose a novel 4D hyperchaotic system and design a new image encryption algorithm in conjunction with the hyperchaotic system. The algorithm uses a split random swap permutation method to permute the image and combines the S-box to diffuse the image. To improve the diffusivity of this encryption algorithm, a cross-random diffusion method is designed to diffuse the image again. Then, we propose a region of interest (ROI) encryption scheme for images. This scheme can automatically identify irregular privacy targets in images and encrypt them. To ensure the security of the region of interest location information during transmission, the scheme compresses the location information of the privacy target using a run-length encoding technique and then embeds the compressed data into the ciphertext image using reversible steganography based on histogram shift. The experimental results and security analysis unequivocally demonstrate that the image encryption algorithm proposed in this paper exhibits robust resistance against a wide array of attacks, thereby ensuring a high level of security. Additionally, the devised image ROI encryption scheme effectively safeguards diverse privacy targets.
通讯机构：
[Chen, Z ] H;Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang 421002, Peoples R China.;Hunan Prov Key Lab Intelligent Informat Proc & App, Hengyang 421002, Peoples R China.
关键词：
fractional order;hyperchaotic system;image encryption;knight tour algorithm
摘要：
The security guarantee of data transmission is becoming more crucial as the frequency of information interchange rises. Ensuring the security of images is essential since they serve as a vital transmission medium. This research suggests an image encryption method that combines the knight tour algorithm with a 6D fractional order hyperchaotic system. First, chaotic sequences are produced using a fractional order hyperchaotic system, which is then utilized to index order and jumble the entire image. To retrieve the image after the second scrambling, choose the knight tour beginning point and run ten rounds of knight tour algorithms on the scrambled image. Thirdly, to maximize the efficiency of picture encryption, employ diffusion methods. The outcomes of the imaging experiment were lastly tested and assessed. The security of the image can be successfully guaranteed by a high-dimensional fractional order hyperchaotic system. This is because its high dimensionality gives it a larger key space than the low dimensional system. This is why it can resist attacks more effectively. After a series of evaluation experiments, it is obvious that this encryption scheme has good encryption performance.
摘要：
As digital images are widely used in social media, medical, military and other fields, ensuring the privacy and security of image data has become a critical concern. Firstly, we propose a novel four-dimensional hyperchaotic system and validate that it exhibits a broad chaotic range, as demonstrated by bifurcation diagrams and Lyapunov exponent experiments. Additionally, simulated circuit diagrams verify the hardware feasibility of the proposed system. Secondly, we design a dynamic iterative scrambling (DIS) scheme that dynamically divides the image into multiple matrices for spatially indexed scrambling. Excellent substitution performance can be ensured by multiple iterations. In the diffusion stage, a multidirectional bit-level L-shaped (MDBL) scheme is proposed. Diffusion is conducted on the bit plane using a designed cross-multiplanar selection algorithm, which fuses the high and low bit planes, thereby enhancing the diffusion performance of MDBL. Thirdly, Based on the above concepts, a novel four-dimensional hyperchaotic system and an encryption algorithm based on bit-level diffusion are proposed. Finally, experimental results and security analyses demonstrate the effectiveness of the novel 4D hyperchaotic system and image encryption scheme. The proposed encryption scheme exhibits robust anti-interference capabilities and effectively safeguards image security.
摘要：
Medical image encryption is essential to protect the privacy and confidentiality of patients' medical records. Deep learning-based encryption, which leverages the nonlinear characteristics of neural networks, has emerged as a promising new method for protecting medical images. In this paper, we present insights into deep learning-based medical image encryption and propose a novel end-to-end medical image encryption scheme based on these insights that leverages feature encoding and decoding for encrypting and decrypting images. Firstly, we explore a method that combines keys generated by the Logistic Map with encoded plaintext image features to improve network diffusion performance. Secondly, we employ a reversible neural network to enhance plaintext image reconstruction while maintaining encryption effectiveness. Finally, we propose a series of novel loss functions to measure the cost with the ideal cryptographic algorithm and continuously optimize our network. Experimental results demonstrate that our scheme improves the performance of image encryption and decryption and resists brute force attacks, statistical attacks, noise and cropping attacks.
摘要：
In this paper, we propose a color image compression and encryption algorithm that combines compressed sensing, Sudoku matrix, and hyperchaotic map to ensure the security of image data and improve transmission and storage efficiency. Firstly, we design a novel two-dimensional sine-logistic coupled hyperchaotic map that exhibits a more continuous and broader chaotic range and more complex hyperchaotic behavior compared to some existing known chaotic maps. Secondly, to mitigate the impact of compression thresholds on image reconstruction quality, we employ multiple optimization strategies to improve the dung beetle optimization algorithm, enhancing its global exploration and local exploitation capabilities, thereby making it more efficient and accurate in handling complex optimization problems. Based on this, we optimize the compression threshold using the improved algorithm to find the optimal threshold for the best image reconstruction quality. Finally, to further enhance the security of the algorithm, we introduce Sudoku matrices in the permutation stage. By using randomly generated Sudoku matrices to permute the image pixel positions, the original image structure is effectively disrupted, increasing the complexity and randomness of the encryption. In the diffusion stage, we employ a bidirectional diffusion operation to ensure that pixel information is effectively spread throughout the image, and we dynamically update the diffusion keys in each round, making the key sequence highly random and unpredictable. Experimental results demonstrate that the proposed algorithm can resist various illegal attacks and offers high security.
摘要：
Currently, many existing image encryption algorithms have encountered challenges in achieving robustness and efficiency, mainly due to insufficient scrambling or inadequate diffusion mechanisms. These limitations can lead to vulnerabilities, making encrypted images more susceptible to attacks and reducing overall security. To address these issues, this paper proposes a new image encryption algorithm (MCLCM-IEA) based on a novel two-dimensional hyperchaotic map (2D-MCLCM). This algorithm integrates a difference algorithm during diffusion and a double-pointer algorithm during scrambling. Additionally, to enhance the security of cipher images, we introduce a plaintext-related weight matrix, which not only expands the key space of MCLCM-IEA but also strengthens its overall security. Benefiting from the superior chaotic properties exhibited by 2D-MCLCM, the strong diffusion efficiency got from the difference diffusion algorithm, and the effective scrambling provided by the double-pointer algorithm, MCLCM-IEA performs exceptionally well in simulation experiments. The results demonstrate that MCLCM-IEA can effectively resist various illegal attacks and showcase robust security and high efficiency.
摘要：
Image transmission is happening more frequently in this era of technologically sophisticated digital information. Additionally, more individuals are becoming aware of its importance. In order to secure images, many academics are participating in research, which is advantageous for guaranteeing data security. In order to strengthen the security of images during transmission, we have investigated new encryption algorithms to guarantee this. First, a current representing the Lorenz chaotic system is introduced into the neuron model. The neuron model generates sequences after receiving the current signal. The next move is made as the current shifts depending on whether the resulting sequences are chaotic or not. If so, the subsequent operation is carried out; otherwise, the current is altered until chaotic sequences are produced. Second, a global scrambling with de-duplication technique is used to scramble the image using the resulting chaotic sequences. To complete the dislocation effect, the Latin square is used to dislocate the image after the initial dislocation. Fourth, the image that has been scrambled is subjected to two rounds of additive mode diffusion. They are diffusion in the forward additive mode and diffusion in the inverse additive mode. Lastly, to improve the diffusion effect, the image is diffused in the finite domain. Eventually, the encrypted image is obtained. After evaluation tests and comparison with related literature, it can be found that the algorithm of this study has certain advantages. Also, the resistance to attack is good. It can protect the security of the image.
摘要：
Growing evidence have demonstrated that many biological processes are inseparable from the participation of key proteins. In this paper, a novel iterative method called linear neighborhood similarity-based protein multifeatures fusion (LNSPF) is proposed to identify potential key proteins based on multifeature fusion. In LNSPF, an original protein-protein interaction (PPI) network will be constructed first based on known protein-protein interaction data downloaded from benchmark databases, based on which, topological features will be further extracted. Next, gene expression data of proteins will be adopted to transfer the original PPI network to a weighted PPI network based on the linear neighborhood similarity. After that, subcellular localization and homologous information of proteins will be integrated to extract functional features for proteins, and based on both functional and topological features obtained above. And then, an iterative method will be designed and carried out to predict potential key proteins. At last, for evaluating the predictive performance of LNSPF, extensive experiments have been done, and compare results between LNPSF and 15 state-of-the-art competitive methods have demonstrated that LNSPF can achieve satisfactory recognition accuracy, which is markedly better than that achieved by each competing method.
摘要：
In recent years, chaotic image encryption algorithms with key and plaintext association have been developed, which are essentially similar to a one-time pad at a time because each encryption requires the transmission of the key. However, some existing schemes cannot uniquely map the seed key to the initial value of the chaotic system, which leads to the reduction of the key space of the encryption system. In addition, some schemes use the same key to encrypt the same image, which does not conform to the one-time pad strategy. This paper solves these problems from two aspects. On the one hand, random pixels are inserted into a plain image and then a hash value is generated using SHA-256. Different seed keys can be obtained even if the same image is encrypted. On the other hand, the Sequential Expansion Algorithm (SEA) and Feedback Iterative Piece-Wise Linear Chaotic Mapping (FI-PWLCM) are proposed to realize the one-to-one correspondence between the seed key and the encrypted key stream. SEA can quickly generate seed key sensitive and random sequences. FI-PWLCM achieves one-to-one correspondence with the seed key through feedback iteration with more control parameters. The mapping not only has the rapidity of PWLCM, but also can produce more complex chaotic sequences. Besides, this paper proposes a Segmented Coordinate Descent (SCD) method for histogram statistical optimization of images to improve the ability of cryptosystems against statistical attacks. Experiments and security analysis show that the algorithm can resist chosen-plaintext (chosen-ciphertext) attacks, brute force attacks, statistical attacks and so on. Compared with most current algorithms, it achieves the best performance in the statistical properties of histogram and entropy.
作者机构：
College of Computer Science and Technology, Hengyang Normal University, Hengyang, 421002, China;Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang, 421002, China
会议名称：
11th International Conference on Computer Engineering and Networks, CENet2021
作者机构：
College of Computer Science and Technology, Hengyang Normal University, Hengyang, 421002, China;Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang, 421002, China
会议名称：
12th International Conference on Computer Engineering and Networks, CENet 2022
期刊：
Frontiers in Genetics,2021年12:763153 ISSN：1664-8021
通讯作者：
He, X.;Zhu, X.
作者机构：
College of Computer Science and Technology, Hengyang Normal University, Hengyang, China;Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang, China;[He, Xin; Kuang, Linai] College of Computer, Xiangtan University, Xiangtan, China;[Chen, Zhiping] College of Computer Engineering and Applied Mathematics, Changsha University, Changsha, China;[Lancine, Camara] The Social Sciences and Management University of Bamako, Bamako, Mali
通讯机构：
[Zhu, X.; He, X.] C;College of Computer Science and Technology, China;College of Computer, China
关键词：
collaborative filtering model;data integration;essential proteins;PDI network;prediction model
期刊：
Advances in Intelligent Systems and Computing,2021年1143:135-143 ISSN：2194-5357
通讯作者：
Chen, Z.
作者机构：
College of Computer Science and Technology, Hengyang Normal University, Hengyang, 421002, China;Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang, 421002, China;[Chen J.] Department of Computer Engineering, Ajou University, Suwon, 16499, South Korea;[Tian X.; Chen Z.; Lei T.] College of Computer Science and Technology, Hengyang Normal University, Hengyang, 421002, China, Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang, 421002, China
通讯机构：
[Chen, Z.] C;College of Computer Science and Technology, China
会议名称：
9th International Conference on Computer Engineering and Networks, CENet2019
会议时间：
18 October 2019 through 20 October 2019
会议论文集名称：
Proceedings of the 9th International Conference on Computer Engineering and Networks
作者机构：
College of Computer Science and Technology, Hengyang Normal University, Hengyang, 421002, China;Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang, 421002, China;[Chen J.] Department of Computer Engineering, AjouUniversity, Suwon, 16499, South Korea;[Zhao H.; Chen Z.] College of Computer Science and Technology, Hengyang Normal University, Hengyang, 421002, China, Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang, 421002, China
会议名称：
10th International Conference on Computer Engineering and Networks, CENet 2020
会议时间：
16 October 2020 through 18 October 2020
会议地点：
中国陕西西安
会议论文集名称：
Proceedings of the 10th International Conference on Computer Engineering and Networks(CENet2020)
关键词：
Fractional order hyperchaotic system;Image encryption algorithm;Poker shuffling operation
