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  • Open Access

    ARTICLE

    Research on Metaverse Security and Forensics

    Guangjun Liang1,2,3, Jianfang Xin4,*, Qun Wang1,2, Xueli Ni1,2,3, Xiangmin Guo1,2,3, Pu Chen1

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 799-825, 2023, DOI:10.32604/cmc.2023.038403

    Abstract As a subversive concept, the metaverse has recently attracted widespread attention around the world and has set off a wave of enthusiasm in academic, industrial, and investment circles. However, while the metaverse brings unprecedented opportunities for transformation to human society, it also contains related risks. Metaverse is a digital living space with information infrastructure, interoperability system, content production system, and value settlement system as the underlying structure in which the inner core is to connect real residents through applications and identities. Through social incentives and governance rules, the metaverse reflects the digital migration of human society. This article will conduct… More >

  • Open Access

    ARTICLE

    Hyper-Tuned Convolutional Neural Networks for Authorship Verification in Digital Forensic Investigations

    Asif Rahim1, Yanru Zhong2, Tariq Ahmad3,*, Sadique Ahmad4,*, Mohammed A. ElAffendi4

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1947-1976, 2023, DOI:10.32604/cmc.2023.039340

    Abstract Authorship verification is a crucial task in digital forensic investigations, where it is often necessary to determine whether a specific individual wrote a particular piece of text. Convolutional Neural Networks (CNNs) have shown promise in solving this problem, but their performance highly depends on the choice of hyperparameters. In this paper, we explore the effectiveness of hyperparameter tuning in improving the performance of CNNs for authorship verification. We conduct experiments using a Hyper Tuned CNN model with three popular optimization algorithms: Adaptive Moment Estimation (ADAM), Stochastic Gradient Descent (SGD), and Root Mean Squared Propagation (RMSPROP). The model is trained and… More >

  • Open Access

    ARTICLE

    Comparison Study and Forensic Analysis between Experiment and Coupled Dynamics Simulation for Submerged Floating Tunnel Segment with Free Ends under Wave Excitations

    Woo Chul Chung1, Chungkuk Jin2,*, MooHyun Kim3, Ju-young Hwang4

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 155-174, 2023, DOI:10.32604/cmes.2023.026754

    Abstract This paper presents dynamic-behavior comparisons and related forensic analyses of a submerged floating tunnel (SFT) between numerical simulation and physical experiment under regular and irregular waves. The experiments are conducted in the 3D wave tank with 1:33.3 scale, and the corresponding coupled time-domain simulation tool is devised for comparison. The entire SFT system consists of a long concrete tunnel and 12 tubular aluminum mooring lines. Two numerical simulation models, the Cummins equation with 3D potential theory including second-order wave-body interaction effects and the much simpler Morison-equation-based formula with the lumped-mass-based line model, are designed and compared. Forensic analyses for mooring-line… More >

  • Open Access

    REVIEW

    An Overview of Image Tamper Detection

    Xingyu Chen*

    Journal of Information Hiding and Privacy Protection, Vol.4, No.2, pp. 103-113, 2022, DOI:10.32604/jihpp.2022.039766

    Abstract With the popularization of high-performance electronic imaging equipment and the wide application of digital image editing software, the threshold of digital image editing becomes lower and lower. This makes it easy to trick the human visual system with professionally altered images. These tampered images have brought serious threats to many fields, including personal privacy, news communication, judicial evidence collection, information security and so on. Therefore, the security and reliability of digital information has been increasingly concerned by the international community. In this paper, digital image tamper detection methods are classified according to the clues that they rely on, detection methods… More >

  • Open Access

    ARTICLE

    Detecting Double JPEG Compressed Color Images via an Improved Approach

    Xiaojie Zhao1, Xiankui Meng1, Ruyong Ren2, Shaozhang Niu2,*, Zhenguang Gao3

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1765-1781, 2023, DOI:10.32604/cmc.2023.029552

    Abstract Detecting double Joint Photographic Experts Group (JPEG) compression for color images is vital in the field of image forensics. In previous researches, there have been various approaches to detecting double JPEG compression with different quantization matrices. However, the detection of double JPEG color images with the same quantization matrix is still a challenging task. An effective detection approach to extract features is proposed in this paper by combining traditional analysis with Convolutional Neural Networks (CNN). On the one hand, the number of nonzero pixels and the sum of pixel values of color space conversion error are provided with 12-dimensional features… More >

  • Open Access

    ARTICLE

    Computer Forensics Framework for Efficient and Lawful Privacy-Preserved Investigation

    Waleed Halboob1,*, Jalal Almuhtadi1,2

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 2071-2092, 2023, DOI:10.32604/csse.2023.024110

    Abstract Privacy preservation (PP) in Digital forensics (DF) is a conflicted and non-trivial issue. Existing solutions use the searchable encryption concept and, as a result, are not efficient and support only a keyword search. Moreover, the collected forensic data cannot be analyzed using existing well-known digital tools. This research paper first investigates the lawful requirements for PP in DF based on the organization for economic co-operation and development OECB) privacy guidelines. To have an efficient investigation process and meet the increased volume of data, the presented framework is designed based on the selective imaging concept and advanced encryption standard (AES). The… More >

  • Open Access

    ARTICLE

    Detection of Copy-Move Forgery in Digital Images Using Singular Value Decomposition

    Zaid Nidhal Khudhair1,4, Farhan Mohamed2, Amjad Rehman3,*, Tanzila Saba3, Saeed Ali bahaj3

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4135-4147, 2023, DOI:10.32604/cmc.2023.032315

    Abstract This paper presents an improved approach for detecting copy-move forgery based on singular value decomposition (SVD). It is a block-based method where the image is scanned from left to right and top to down by a sliding window with a determined size. At each step, the SVD is determined. First, the diagonal matrix’s maximum value (norm) is selected (representing the scaling factor for SVD and a fixed value for each set of matrix elements even when rotating the matrix or scaled). Then, the similar norms are grouped, and each leading group is separated into many subgroups (elements of each subgroup… More >

  • Open Access

    ARTICLE

    Enhancing CNN for Forensics Age Estimation Using CGAN and Pseudo-Labelling

    Sultan Alkaabi1,*, Salman Yussof1, Sameera Al-Mulla2

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2499-2516, 2023, DOI:10.32604/cmc.2023.029914

    Abstract Age estimation using forensics odontology is an important process in identifying victims in criminal or mass disaster cases. Traditionally, this process is done manually by human expert. However, the speed and accuracy may vary depending on the expertise level of the human expert and other human factors such as level of fatigue and attentiveness. To improve the recognition speed and consistency, researchers have proposed automated age estimation using deep learning techniques such as Convolutional Neural Network (CNN). CNN requires many training images to obtain high percentage of recognition accuracy. Unfortunately, it is very difficult to get large number of samples… More >

  • Open Access

    ARTICLE

    CVIP-Net: A Convolutional Neural Network-Based Model for Forensic Radiology Image Classification

    Syeda Naila Batool, Ghulam Gilanie*

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1319-1332, 2023, DOI:10.32604/cmc.2023.032121

    Abstract Automated and autonomous decisions of image classification systems have essential applicability in this modern age even. Image-based decisions are commonly taken through explicit or auto-feature engineering of images. In forensic radiology, auto decisions based on images significantly affect the automation of various tasks. This study aims to assist forensic radiology in its biological profile estimation when only bones are left. A benchmarked dataset Radiology Society of North America (RSNA) has been used for research and experiments. Additionally, a locally developed dataset has also been used for research and experiments to cross-validate the results. A Convolutional Neural Network (CNN)-based model named… More >

  • Open Access

    REVIEW

    A Thorough Investigation on Image Forgery Detection

    Anjani Kumar Rai*, Subodh Srivastava

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1489-1528, 2023, DOI:10.32604/cmes.2022.020920

    Abstract Image forging is the alteration of a digital image to conceal some of the necessary or helpful information. It cannot be easy to distinguish the modified region from the original image in some circumstances. The demand for authenticity and the integrity of the image drive the detection of a fabricated image. There have been cases of ownership infringements or fraudulent actions by counterfeiting multimedia files, including re-sampling or copy-moving. This work presents a high-level view of the forensics of digital images and their possible detection approaches. This work presents a thorough analysis of digital image forgery detection techniques with their… More >

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