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International Journal of Digital Crime and Forensics最新文献

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Behavioural Evidence Analysis: A Paradigm Shift in Digital Forensics 行为证据分析:数字取证的范式转变
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2021-09-01 DOI: 10.4018/IJDCF.20210901.OA2
Barkha Shree, Parneeta Dhaliwal
{"title":"Behavioural Evidence Analysis: A Paradigm Shift in Digital Forensics","authors":"Barkha Shree, Parneeta Dhaliwal","doi":"10.4018/IJDCF.20210901.OA2","DOIUrl":"https://doi.org/10.4018/IJDCF.20210901.OA2","url":null,"abstract":"Recent developments in digital forensics (DF) have emphasized that along with inspection of digital evidence, the study of behavioural clues based on behavioural evidence analysis (BEA) is vital for accurate and complete criminal investigation. This paper reviews the existing BEA approaches and process models and concludes the lack of standardisation in the BEA process. The research comprehends that existing BEA methodologies are restricted to specific characteristics of the forensic domain in question. To address these limitations, the paper proposes a standardised approach detailing the step-by-step implementation of BEA in the DF process. The proposed model presents a homogenous technique that can be practically applied to real-life cases. This standard BEA framework classifies digital evidence into categories to decipher associated offender characteristics. Unlike existing models, this new approach collects evidence from diverse sources and leaves no aspect unattended while probing criminal behavioural cues, thus facilitating its applicability across varied forensic domains.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78183032","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}
引用次数: 0
Secure Storage and Sharing of Visitor Images Generated by Smart Entrance on Public Cloud 公共云智能入口生成访客图像的安全存储与共享
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2021-09-01 DOI: 10.4018/IJDCF.20210901.OA4
Rajashree Soman, R. Sukumar
{"title":"Secure Storage and Sharing of Visitor Images Generated by Smart Entrance on Public Cloud","authors":"Rajashree Soman, R. Sukumar","doi":"10.4018/IJDCF.20210901.OA4","DOIUrl":"https://doi.org/10.4018/IJDCF.20210901.OA4","url":null,"abstract":"Visitor validation at entrance generates a large number of image files that need to be transmitted over to cloud for future reference. The image data needs to be protected by active and passive adversaries from performing cryptographic attacks on these data. The image data also needs to be authenticated before giving it for future use. Focusing on reliable and secure image sharing, the proposed method involves building a novel cloud platform, which aims to provide a secure storage in the public cloud. The main objective of this paper is to provide a new way of secure image data storage and transmission on cloud using cryptographic algorithms. To overcome the flaws in current system, a novel method using BigchainDB, which has advantages of blockchain technology and traditional database, is proposed for storing attributes of image.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79253264","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}
引用次数: 3
Holistic Analytics of Digital Artifacts: Unique Metadata Association Model 数字文物的整体分析:独特的元数据关联模型
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2021-09-01 DOI: 10.4018/IJDCF.20210901.OA5
A. K. Mohan, Sethumadhavan Madathil, K. V. Lakshmy
{"title":"Holistic Analytics of Digital Artifacts: Unique Metadata Association Model","authors":"A. K. Mohan, Sethumadhavan Madathil, K. V. Lakshmy","doi":"10.4018/IJDCF.20210901.OA5","DOIUrl":"https://doi.org/10.4018/IJDCF.20210901.OA5","url":null,"abstract":"Investigation of every crime scene with digital evidence is predominantly required in identifying almost all atomic files behind the scenes that have been intentionally scrubbed out. Apart from the data generated across digital devices and the use of diverse technology that slows down the traditional digital forensic investigation strategies. Dynamically scrutinizing the concealed or sparse metadata matches from the less frequent archives of evidence spread across heterogeneous sources and finding their association with other artifacts across the collection is still a horrendous task for the investigators. The effort of this article via unique pockets (UP), unique groups (UG), and unique association (UA) model is to address the exclusive challenges mixed up in identifying incoherent associations that are buried well within the meager metadata field-value pairs. Both the existing similarity models and proposed unique mapping models are verified by the unique metadata association model.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88748605","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}
引用次数: 1
A New Framework for Matching Forensic Composite Sketches With Digital Images 一种新的法医合成草图与数字图像匹配框架
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2021-09-01 DOI: 10.4018/IJDCF.20210901.OA1
T. ChethanaH., Trisiladevi C. Nagavi
{"title":"A New Framework for Matching Forensic Composite Sketches With Digital Images","authors":"T. ChethanaH., Trisiladevi C. Nagavi","doi":"10.4018/IJDCF.20210901.OA1","DOIUrl":"https://doi.org/10.4018/IJDCF.20210901.OA1","url":null,"abstract":"Face sketch recognition is considered as a sub-problem of face recognition. Matching composite sketches with its corresponding digital image is one of the challenging tasks. A new convolution neural network (CNN) framework for matching composite sketches with digital images is proposed in this work. The framework consists of a base CNN model that uses swish activation function in the hidden layers. Both composite sketches and digital images are trained separately in the network by providing matching pairs and mismatching pairs. The final output resulted from the network’s final layer is compared with the threshold value, and then the pair is assigned to the same or different class. The proposed framework is evaluated on two datasets, and it exhibits an accuracy of 78.26% with extended-PRIP (E-PRIP) and 69.57% with composite sketches with age variations (CSA) respectively. Experimental analysis shows the improved results compared to state-of-the-art composite sketch matching systems.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74929855","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}
引用次数: 1
Multimedia Concealed Data Detection Using Quantitative Steganalysis 使用定量隐写分析的多媒体隐藏数据检测
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2021-09-01 DOI: 10.4018/IJDCF.20210901.OA6
Rupa Ch., S. Shaikh, Mukesh Chinta
{"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":null,"pages":null},"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}
引用次数: 3
Design and Development of Ternary-Based Anomaly Detection in Semantic Graphs Using Metaheuristic Algorithm 基于元启发式算法的语义图三元异常检测的设计与开发
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2021-09-01 DOI: 10.4018/IJDCF.20210901.OA3
M. S. K. Reddy, D. Rajput
{"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":null,"pages":null},"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}
引用次数: 0
An Intra-Prediction Mode-Based Video Steganography With Secure Strategy 基于内预测模型的视频隐写安全策略
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2021-07-01 DOI: 10.4018/IJDCF.20210701.OA1
Xiushi Cao, Tanfeng Sun, Xinghao Jiang, Yi Dong, Ke Xu
{"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":null,"pages":null},"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}
引用次数: 0
A Big Data Text Coverless Information Hiding Based on Topic Distribution and TF-IDF 基于主题分布和TF-IDF的大数据文本无覆盖信息隐藏
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2021-07-01 DOI: 10.4018/IJDCF.20210701.OA4
Jiaohua Qin, Zhuo Zhou, Yun Tan, Xuyu Xiang, Zhibin He
{"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":null,"pages":null},"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}
引用次数: 3
Applying Secret Image Sharing to Economics 将秘密图像共享应用于经济学
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2021-07-01 DOI: 10.4018/IJDCF.20210701.OA2
Xuemei Zhao, Tongtong Zhang, Jun Liu, Canju Lu, Huang Lu, Xuehu Yan
{"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":null,"pages":null},"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}
引用次数: 1
Multi-Layer Fusion Neural Network for Deepfake Detection 深度伪造检测的多层融合神经网络
IF 0.7
International Journal of Digital Crime and Forensics Pub Date : 2021-07-01 DOI: 10.4018/IJDCF.20210701.OA3
Zheng Zhao, Penghui Wang, Wei Lu
{"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":null,"pages":null},"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}
引用次数: 4
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