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  • Open Access

    ARTICLE

    Metaheuristics with Optimal Deep Transfer Learning Based Copy-Move Forgery Detection Technique

    C. D. Prem Kumar1,*, S. Saravana Sundaram2

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 881-899, 2023, DOI:10.32604/iasc.2023.025766

    Abstract The extensive availability of advanced digital image technologies and image editing tools has simplified the way of manipulating the image content. An effective technique for tampering the identification is the copy-move forgery. Conventional image processing techniques generally search for the patterns linked to the fake content and restrict the usage in massive data classification. Contrastingly, deep learning (DL) models have demonstrated significant performance over the other statistical techniques. With this motivation, this paper presents an Optimal Deep Transfer Learning based Copy Move Forgery Detection (ODTL-CMFD) technique. The presented ODTL-CMFD technique aims to derive a DL… 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 More >

  • Open Access

    ARTICLE

    Deep Learning Based Image Forgery Detection Methods

    Liang Xiu-jian1,2,*, Sun He2

    Journal of Cyber Security, Vol.4, No.2, pp. 119-133, 2022, DOI:10.32604/jcs.2022.032915

    Abstract Increasingly advanced image processing technology has made digital image editing easier and easier. With image processing software at one’s fingertips, one can easily alter the content of an image, and the altered image is so realistic that it is illegible to the naked eye. These tampered images have posed a serious threat to personal privacy, social order, and national security. Therefore, detecting and locating tampered areas in images has important practical significance, and has become an important research topic in the field of multimedia information security. In recent years, deep learning technology has been widely… More >

  • Open Access

    ARTICLE

    A Survey of Anti-forensic for Face Image Forgery

    Haitao Zhang*

    Journal of Information Hiding and Privacy Protection, Vol.4, No.1, pp. 41-51, 2022, DOI:10.32604/jihpp.2022.031707

    Abstract Deep learning related technologies, especially generative adversarial network, are widely used in the fields of face image tampering and forgery. Forensics researchers have proposed a variety of passive forensic and related anti-forensic methods for image tampering and forgery, especially face images, but there is still a lack of overview of anti-forensic methods at this stage. Therefore, this paper will systematically discuss the anti-forensic methods for face image tampering and forgery. Firstly, this paper expounds the relevant background, including the relevant tampering and forgery methods and forensic schemes of face images. The former mainly includes four More >

  • Open Access

    ARTICLE

    Text-Independent Algorithm for Source Printer Identification Based on Ensemble Learning

    Naglaa F. El Abady1,*, Mohamed Taha1, Hala H. Zayed1,2

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1417-1436, 2022, DOI:10.32604/cmc.2022.028044

    Abstract Because of the widespread availability of low-cost printers and scanners, document forgery has become extremely popular. Watermarks or signatures are used to protect important papers such as certificates, passports, and identification cards. Identifying the origins of printed documents is helpful for criminal investigations and also for authenticating digital versions of a document in today’s world. Source printer identification (SPI) has become increasingly popular for identifying frauds in printed documents. This paper provides a proposed algorithm for identifying the source printer and categorizing the questioned document into one of the printer classes. A dataset of 1200… More >

  • Open Access

    Vulnerability Analysis of MEGA Encryption Mechanism

    Qingbing Ji1,2,*, Zhihong Rao1,2, Lvlin Ni2, Wei Zhao2, Jing Fu3

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 817-829, 2022, DOI:10.32604/cmc.2022.026949

    Abstract MEGA is an end-to-end encrypted cloud storage platform controlled by users. Moreover, the communication between MEGA client and server is carried out under the protection of Transport Layer Security (TLS) encryption, it is difficult to intercept the key data packets in the process of MEGA registration, login, file data upload, and download. These characteristics of MEGA have brought great difficulties to its forensics. This paper presents a method to attack MEGA to provide an effective method for MEGA’s forensics. By debugging the open-source code of MEGA and analyzing the security white paper published, this paper More >

  • Open Access

    ARTICLE

    Reinforced CNN Forensic Discriminator to Detect Document Forgery by DCGAN

    Seo-young Lim, Jeongho Cho*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6039-6051, 2022, DOI:10.32604/cmc.2022.024862

    Abstract Recently, the technology of digital image forgery based on a generative adversarial network (GAN) has considerably improved to the extent that it is difficult to distinguish it from the original image with the naked eye by compositing and editing a person's face or a specific part with the original image. Thus, much attention has been paid to digital image forgery as a social issue. Further, document forgery through GANs can completely change the meaning and context in a document, and it is difficult to identify whether the document is forged or not, which is dangerous.… More >

  • Open Access

    ARTICLE

    Integrated Approach to Detect Cyberbullying Text: Mobile Device Forensics Data

    G. Maria Jones1,*, S. Godfrey Winster2, P. Valarmathie3

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 963-978, 2022, DOI:10.32604/csse.2022.019483

    Abstract Mobile devices and social networks provide communication opportunities among the young generation, which increases vulnerability and cybercrimes activities. A recent survey reports that cyberbullying and cyberstalking constitute a developing issue among youngsters. This paper focuses on cyberbullying detection in mobile phone text by retrieving with the help of an oxygen forensics toolkit. We describe the data collection using forensics technique and a corpus of suspicious activities like cyberbullying annotation from mobile phones and carry out a sequence of binary classification experiments to determine cyberbullying detection. We use forensics techniques, Machine Learning (ML), and Deep Learning More >

  • Open Access

    ARTICLE

    CNN-Based Forensic Method on Contrast Enhancement with JPEG Post-Processing

    Ziqing Yan1,2, Pengpeng Yang1,2, Rongrong Ni1,2,*, Yao Zhao1,2, Hairong Qi3

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3205-3216, 2021, DOI:10.32604/cmc.2021.020324

    Abstract As one of the most popular digital image manipulations, contrast enhancement (CE) is frequently applied to improve the visual quality of the forged images and conceal traces of forgery, therefore it can provide evidence of tampering when verifying the authenticity of digital images. Contrast enhancement forensics techniques have always drawn significant attention for image forensics community, although most approaches have obtained effective detection results, existing CE forensic methods exhibit poor performance when detecting enhanced images stored in the JPEG format. The detection of forgery on contrast adjustments in the presence of JPEG post processing is… More >

  • Open Access

    ARTICLE

    Digital Forensics for Skulls Classification in Physical Anthropology Collection Management

    Imam Yuadi1,*, Myrtati D. Artaria2, Sakina3, A. Taufiq Asyhari4

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3979-3995, 2021, DOI:10.32604/cmc.2021.015417

    Abstract The size, shape, and physical characteristics of the human skull are distinct when considering individual humans. In physical anthropology, the accurate management of skull collections is crucial for storing and maintaining collections in a cost-effective manner. For example, labeling skulls inaccurately or attaching printed labels to skulls can affect the authenticity of collections. Given the multiple issues associated with the manual identification of skulls, we propose an automatic human skull classification approach that uses a support vector machine and different feature extraction methods such as gray-level co-occurrence matrix features, Gabor features, fractal features, discrete wavelet… More >

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