Pub Date : 2021-09-01DOI: 10.4018/IJDCF.20210901.OA6
Rupa Ch., S. Shaikh, Mukesh Chinta
In current days, there is a constant evolution in modern technology. The most predominant usage of technology by society is the internet. There are many ways and means on the internet through which data is transmitted. Having such rapid and fast growth of communicating media also increases the exposure to security threats, causing unintellectual information ingress. Steganography is the main aspect of communicating in an aspect that hides the extent of communication. Steganalysis is another essential concern in data concealing, which is the art of identifying the existence of steganography. A framework has been designed to identify the concealed data in the multimedia file in the proposed system. This work’s main strength is analyzing concealed data images without embedding and extracting the image’s payloads. A quantitative steganalysis approach was considered to accomplish the proposed objective. By using this approach, the results were achieved with 98% accuracy.
{"title":"Multimedia Concealed Data Detection Using Quantitative Steganalysis","authors":"Rupa Ch., S. Shaikh, Mukesh Chinta","doi":"10.4018/IJDCF.20210901.OA6","DOIUrl":"https://doi.org/10.4018/IJDCF.20210901.OA6","url":null,"abstract":"In current days, there is a constant evolution in modern technology. The most predominant usage of technology by society is the internet. There are many ways and means on the internet through which data is transmitted. Having such rapid and fast growth of communicating media also increases the exposure to security threats, causing unintellectual information ingress. Steganography is the main aspect of communicating in an aspect that hides the extent of communication. Steganalysis is another essential concern in data concealing, which is the art of identifying the existence of steganography. A framework has been designed to identify the concealed data in the multimedia file in the proposed system. This work’s main strength is analyzing concealed data images without embedding and extracting the image’s payloads. A quantitative steganalysis approach was considered to accomplish the proposed objective. By using this approach, the results were achieved with 98% accuracy.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":"29 1","pages":"101-113"},"PeriodicalIF":0.7,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81152859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-01DOI: 10.4018/IJDCF.20210901.OA3
M. S. K. Reddy, D. Rajput
At present, the field of homeland security faces many obstacles while determining abnormal or suspicious entities within the huge set of data. Several approaches have been adopted from social network analysis and data mining; however, it is challenging to identify the objective of abnormal instances within the huge complicated semantic graphs. The abnormal node is the one that takes an individual or abnormal semantic in the network. Hence, for defining this notion, a graph structure is implemented for generating the semantic profile of each node by numerous kinds of nodes and links that are associated to the node in a specific distance via edges. Once the graph structure is framed, the ternary list is formed on the basis of its adjacent nodes. The abnormalities in the nodes are detected by introducing a new optimization concept referred to as biogeography optimization with fitness sorted update (BO-FBU), which is the extended version of the standard biogeography optimization algorithm (BBO). The abnormal behavior in the network is identified by the similarities among the derived rule features. Further, the performance of the proposed model is compared to the other classical models in terms of certain performance measures. These techniques will be useful to detect digital crime and forensics.
{"title":"Design and Development of Ternary-Based Anomaly Detection in Semantic Graphs Using Metaheuristic Algorithm","authors":"M. S. K. Reddy, D. Rajput","doi":"10.4018/IJDCF.20210901.OA3","DOIUrl":"https://doi.org/10.4018/IJDCF.20210901.OA3","url":null,"abstract":"At present, the field of homeland security faces many obstacles while determining abnormal or suspicious entities within the huge set of data. Several approaches have been adopted from social network analysis and data mining; however, it is challenging to identify the objective of abnormal instances within the huge complicated semantic graphs. The abnormal node is the one that takes an individual or abnormal semantic in the network. Hence, for defining this notion, a graph structure is implemented for generating the semantic profile of each node by numerous kinds of nodes and links that are associated to the node in a specific distance via edges. Once the graph structure is framed, the ternary list is formed on the basis of its adjacent nodes. The abnormalities in the nodes are detected by introducing a new optimization concept referred to as biogeography optimization with fitness sorted update (BO-FBU), which is the extended version of the standard biogeography optimization algorithm (BBO). The abnormal behavior in the network is identified by the similarities among the derived rule features. Further, the performance of the proposed model is compared to the other classical models in terms of certain performance measures. These techniques will be useful to detect digital crime and forensics.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":"10 1","pages":"43-64"},"PeriodicalIF":0.7,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82174124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.4018/IJDCF.20210701.OA1
Xiushi Cao, Tanfeng Sun, Xinghao Jiang, Yi Dong, Ke Xu
In this paper, an intra-prediction mode (IPM)-based video steganography with secure strategy was proposed for H.264 video stream. First of all, according to the property of IPM conversion after calibration, a content-adaptive selection strategy was adopted to measure candidate carrier macroblock. Then, a more efficient encoding strategy based on grouped IPM was applied to encode secret message. This encoding strategy aimed to further enhance the security performance by exploiting the deviation feature of calibrated IPM. Finally, syndrome-trellis code was used as the embedding implementation to minimize distortion. Experimental results demonstrate that this article proposed algorithm presents a novel security performance with any existing IPM-based video steganography.
{"title":"An Intra-Prediction Mode-Based Video Steganography With Secure Strategy","authors":"Xiushi Cao, Tanfeng Sun, Xinghao Jiang, Yi Dong, Ke Xu","doi":"10.4018/IJDCF.20210701.OA1","DOIUrl":"https://doi.org/10.4018/IJDCF.20210701.OA1","url":null,"abstract":"In this paper, an intra-prediction mode (IPM)-based video steganography with secure strategy was proposed for H.264 video stream. First of all, according to the property of IPM conversion after calibration, a content-adaptive selection strategy was adopted to measure candidate carrier macroblock. Then, a more efficient encoding strategy based on grouped IPM was applied to encode secret message. This encoding strategy aimed to further enhance the security performance by exploiting the deviation feature of calibrated IPM. Finally, syndrome-trellis code was used as the embedding implementation to minimize distortion. Experimental results demonstrate that this article proposed algorithm presents a novel security performance with any existing IPM-based video steganography.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":"15 1","pages":"1-15"},"PeriodicalIF":0.7,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79267509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.4018/IJDCF.20210701.OA4
Jiaohua Qin, Zhuo Zhou, Yun Tan, Xuyu Xiang, Zhibin He
Coverless information hiding has become a hot topic in recent years. The existing steganalysis tools are invalidated due to coverless steganography without any modification to the carrier. However, for the text coverless has relatively low hiding capacity, this paper proposed a big data text coverless information hiding method based on LDA (latent Dirichlet allocation) topic distribution and keyword TF-IDF (term frequency-inverse document frequency). Firstly, the sender and receiver build codebook, including word segmentation, word frequency and TF-IDF features, LDA topic model clustering. The sender then shreds the secret information, converts it into keyword ID through the keywords-index table, and searches the text containing the secret information keywords. Secondly, the searched text is taken as the index tag according to the topic distribution and TF-IDF features. At the same time, random numbers are introduced to control the keyword order of secret information.
{"title":"A Big Data Text Coverless Information Hiding Based on Topic Distribution and TF-IDF","authors":"Jiaohua Qin, Zhuo Zhou, Yun Tan, Xuyu Xiang, Zhibin He","doi":"10.4018/IJDCF.20210701.OA4","DOIUrl":"https://doi.org/10.4018/IJDCF.20210701.OA4","url":null,"abstract":"Coverless information hiding has become a hot topic in recent years. The existing steganalysis tools are invalidated due to coverless steganography without any modification to the carrier. However, for the text coverless has relatively low hiding capacity, this paper proposed a big data text coverless information hiding method based on LDA (latent Dirichlet allocation) topic distribution and keyword TF-IDF (term frequency-inverse document frequency). Firstly, the sender and receiver build codebook, including word segmentation, word frequency and TF-IDF features, LDA topic model clustering. The sender then shreds the secret information, converts it into keyword ID through the keywords-index table, and searches the text containing the secret information keywords. Secondly, the searched text is taken as the index tag according to the topic distribution and TF-IDF features. At the same time, random numbers are introduced to control the keyword order of secret information.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":"17 1","pages":"40-56"},"PeriodicalIF":0.7,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81456646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.4018/IJDCF.20210701.OA3
Zheng Zhao, Penghui Wang, Wei Lu
Recently, the spread of videos forged by deepfake tools has been widely concerning, and effective ways for detecting them are urgently needed. It is known that such artificial intelligence-aided forgery makes at least three levels of artifacts, which can be named as microcosmic or statistical features, mesoscopic features, and macroscopic or semantic features. However, existing detection methods have not been designed to exploited them all. This work proposes a new approach to more effective detection of deepfake videos. A multi-layer fusion neural network (MFNN) has been designed to capture the artifacts in different levels. Features maps output from specially designed shallow, middle, and deep layers, which are used as statistical, mesoscopic, and semantic features, respectively, are fused together before classification. FaceForensic++ dataset was used to train and test the method. The experimental results show that MFNN outperforms other relevant methods. Particularly, it demonstrates more advantage in detecting low-quality deepfake videos.
{"title":"Multi-Layer Fusion Neural Network for Deepfake Detection","authors":"Zheng Zhao, Penghui Wang, Wei Lu","doi":"10.4018/IJDCF.20210701.OA3","DOIUrl":"https://doi.org/10.4018/IJDCF.20210701.OA3","url":null,"abstract":"Recently, the spread of videos forged by deepfake tools has been widely concerning, and effective ways for detecting them are urgently needed. It is known that such artificial intelligence-aided forgery makes at least three levels of artifacts, which can be named as microcosmic or statistical features, mesoscopic features, and macroscopic or semantic features. However, existing detection methods have not been designed to exploited them all. This work proposes a new approach to more effective detection of deepfake videos. A multi-layer fusion neural network (MFNN) has been designed to capture the artifacts in different levels. Features maps output from specially designed shallow, middle, and deep layers, which are used as statistical, mesoscopic, and semantic features, respectively, are fused together before classification. FaceForensic++ dataset was used to train and test the method. The experimental results show that MFNN outperforms other relevant methods. Particularly, it demonstrates more advantage in detecting low-quality deepfake videos.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":"9 1","pages":"26-39"},"PeriodicalIF":0.7,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81571140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.4018/IJDCF.20210701.OA5
X. Duan, Baoxia Li, Daidou Guo, Kai Jia, E. Zhang, Chuan Qin
Steganalysis technology judges whether there is secret information in the carrier by monitoring the abnormality of the carrier data, so the traditional information hiding technology has reached the bottleneck. Therefore, this paper proposed the coverless information hiding based on the improved training of Wasserstein GANs (WGAN-GP) model. The sender trains the WGAN-GP with a natural image and a secret image. The generated image and secret image are visually identical, and the parameters of generator are saved to form the codebook. The sender uploads the natural image (disguise image) to the cloud disk. The receiver downloads the camouflage image from the cloud disk and obtains the corresponding generator parameter in the codebook and inputs it to the generator. The generator outputs the same image for the secret image, which realized the same results as sending the secret image. The experimental results indicate that the scheme produces high image quality and good security.
隐写分析技术通过监测载体数据的异常情况来判断载体中是否存在秘密信息，使得传统的信息隐藏技术达到了瓶颈。为此，本文提出了基于改进训练的Wasserstein gan (WGAN-GP)模型的无覆盖信息隐藏方法。发送方用自然图像和秘密图像训练WGAN-GP。生成的图像与保密图像在视觉上完全相同，并将生成器的参数保存成码本。发送者将自然图像(伪装图像)上传到云盘。接收机从云盘中下载伪装图像，从码本中获取相应的发生器参数，输入到发生器中。生成器为秘密图像输出相同的图像，实现了与发送秘密图像相同的结果。实验结果表明，该方案具有较高的图像质量和较好的安全性。
{"title":"Coverless Information Hiding Based on WGAN-GP Model","authors":"X. Duan, Baoxia Li, Daidou Guo, Kai Jia, E. Zhang, Chuan Qin","doi":"10.4018/IJDCF.20210701.OA5","DOIUrl":"https://doi.org/10.4018/IJDCF.20210701.OA5","url":null,"abstract":"Steganalysis technology judges whether there is secret information in the carrier by monitoring the abnormality of the carrier data, so the traditional information hiding technology has reached the bottleneck. Therefore, this paper proposed the coverless information hiding based on the improved training of Wasserstein GANs (WGAN-GP) model. The sender trains the WGAN-GP with a natural image and a secret image. The generated image and secret image are visually identical, and the parameters of generator are saved to form the codebook. The sender uploads the natural image (disguise image) to the cloud disk. The receiver downloads the camouflage image from the cloud disk and obtains the corresponding generator parameter in the codebook and inputs it to the generator. The generator outputs the same image for the secret image, which realized the same results as sending the secret image. The experimental results indicate that the scheme produces high image quality and good security.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":"35 1","pages":"57-70"},"PeriodicalIF":0.7,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77309513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.4018/IJDCF.20210701.OA2
Xuemei Zhao, Tongtong Zhang, Jun Liu, Canju Lu, Huang Lu, Xuehu Yan
Economics has some limitations, such as insecure multiple parties economical investment decision and leakage of business quotation. Secret image sharing (SIS) for (k, n)-threshold is such a technique that protects an image through splitting it into n shadows, a.k.a. shadow images or shares, assigned to n corresponding participants. The secret image can be disclosed by obtaining k or more shadows. Polynomial-based SIS and visual secret sharing (VSS) are the chief research branches. This paper first analyzes the insecure issues in economics and then introduces two methods to apply typical SIS schemes to improve economical security. Finally, experiments are realized to illustrate the efficiency of the methods.
{"title":"Applying Secret Image Sharing to Economics","authors":"Xuemei Zhao, Tongtong Zhang, Jun Liu, Canju Lu, Huang Lu, Xuehu Yan","doi":"10.4018/IJDCF.20210701.OA2","DOIUrl":"https://doi.org/10.4018/IJDCF.20210701.OA2","url":null,"abstract":"Economics has some limitations, such as insecure multiple parties economical investment decision and leakage of business quotation. Secret image sharing (SIS) for (k, n)-threshold is such a technique that protects an image through splitting it into n shadows, a.k.a. shadow images or shares, assigned to n corresponding participants. The secret image can be disclosed by obtaining k or more shadows. Polynomial-based SIS and visual secret sharing (VSS) are the chief research branches. This paper first analyzes the insecure issues in economics and then introduces two methods to apply typical SIS schemes to improve economical security. Finally, experiments are realized to illustrate the efficiency of the methods.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":"39 1","pages":"16-25"},"PeriodicalIF":0.7,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75411297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.4018/IJDCF.20210701.OA6
Tingting Su, Yan Ke, Yi Ding, Jia Liu
This paper proposes a lossless data hiding scheme in learning with errors (LWE)-encrypted domain based on key-switching technique. Lossless data hiding and extraction could be realized by a third party without knowing the private key for decryption. Key-switching-based least-significant-bit (KSLSB) data hiding method has been designed during the lossless data hiding process. The owner of the plaintext first encrypts the plaintext by using LWE encryption and uploads ciphertext to a (trusted or untrusted) third server. Then the server performs KSLSB to obtain a marked ciphertext. To enable the third party to manage ciphertext flexibly and keep the plaintext secret, the embedded data can be extracted from the marked ciphertext without using the private key of LWE encryption in the proposed scheme. Experimental results demonstrate that data hiding would not compromise the security of LWE encryption, and the embedding rate is 1 bit per bit of plaintext without introducing any loss into the directly decrypted result.
{"title":"Lossless Data Hiding in LWE-Encrypted Domains Based on Key-Switching","authors":"Tingting Su, Yan Ke, Yi Ding, Jia Liu","doi":"10.4018/IJDCF.20210701.OA6","DOIUrl":"https://doi.org/10.4018/IJDCF.20210701.OA6","url":null,"abstract":"This paper proposes a lossless data hiding scheme in learning with errors (LWE)-encrypted domain based on key-switching technique. Lossless data hiding and extraction could be realized by a third party without knowing the private key for decryption. Key-switching-based least-significant-bit (KSLSB) data hiding method has been designed during the lossless data hiding process. The owner of the plaintext first encrypts the plaintext by using LWE encryption and uploads ciphertext to a (trusted or untrusted) third server. Then the server performs KSLSB to obtain a marked ciphertext. To enable the third party to manage ciphertext flexibly and keep the plaintext secret, the embedded data can be extracted from the marked ciphertext without using the private key of LWE encryption in the proposed scheme. Experimental results demonstrate that data hiding would not compromise the security of LWE encryption, and the embedding rate is 1 bit per bit of plaintext without introducing any loss into the directly decrypted result.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":"140 1","pages":"71-89"},"PeriodicalIF":0.7,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76392022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-01DOI: 10.4018/IJDCF.20210501.OA1
Bao Kangsheng
Secret information communication model based on channel construction of orthogonal basis can implement secret information hiding and recovery without a key. The orthogonal basis is constructed by the media carrier's self-correlation. Carrier and secret information channels are constructed independently. And it has good properties of avoiding detection. The experiments show that the model with proper carrier components and threshold of secret information coding has the capacity of secret information and robustness. And the secret information capacity and anti-noise capability can be improved by compressed and error correcting or checking codes.
{"title":"Information Hiding Model Based on Channel Construction of Orthogonal Basis","authors":"Bao Kangsheng","doi":"10.4018/IJDCF.20210501.OA1","DOIUrl":"https://doi.org/10.4018/IJDCF.20210501.OA1","url":null,"abstract":"Secret information communication model based on channel construction of orthogonal basis can implement secret information hiding and recovery without a key. The orthogonal basis is constructed by the media carrier's self-correlation. Carrier and secret information channels are constructed independently. And it has good properties of avoiding detection. The experiments show that the model with proper carrier components and threshold of secret information coding has the capacity of secret information and robustness. And the secret information capacity and anti-noise capability can be improved by compressed and error correcting or checking codes.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":"64 1","pages":"1-18"},"PeriodicalIF":0.7,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85664075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-01DOI: 10.4018/IJDCF.20210501.OA5
Liu Yang, W. Meng, Xudong Zhao
In this paper, an angular graph Fourier transform (AGFT) is introduced to encrypt color images with their intrinsic structures. The graph Fourier transform (GFT) is extended to the AGFT and proven to have the desired properties of angular transform and graph transform. In the proposed encryption method, color images are encoded by DNA sequences and confused under the control of chaotic key streams firstly. Secondly, sparse decomposition based on the random walk is applied to scramble pixels spatially, and a series of sub-images are obtained. This step increases encryption efficiency. Finally, the intrinsic sub-image structure is reflected by graphs, and the signals on different subgraphs are transformed into different AGFT domains with particular angular parameters, which makes the proposed method relevant to the original image structure and enhances security. The experimental results demonstrate that the proposed algorithm can resist various potential attacks and achieve better performance than the state-of-the-art algorithms.
{"title":"Color Image Encryption Using Angular Graph Fourier Transform","authors":"Liu Yang, W. Meng, Xudong Zhao","doi":"10.4018/IJDCF.20210501.OA5","DOIUrl":"https://doi.org/10.4018/IJDCF.20210501.OA5","url":null,"abstract":"In this paper, an angular graph Fourier transform (AGFT) is introduced to encrypt color images with their intrinsic structures. The graph Fourier transform (GFT) is extended to the AGFT and proven to have the desired properties of angular transform and graph transform. In the proposed encryption method, color images are encoded by DNA sequences and confused under the control of chaotic key streams firstly. Secondly, sparse decomposition based on the random walk is applied to scramble pixels spatially, and a series of sub-images are obtained. This step increases encryption efficiency. Finally, the intrinsic sub-image structure is reflected by graphs, and the signals on different subgraphs are transformed into different AGFT domains with particular angular parameters, which makes the proposed method relevant to the original image structure and enhances security. The experimental results demonstrate that the proposed algorithm can resist various potential attacks and achieve better performance than the state-of-the-art algorithms.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":"1 1","pages":"59-82"},"PeriodicalIF":0.7,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84035063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：