C. D. Prem Kumar^1,*, 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 model for the classification of… More >

Naglaa F. El Abady^1,*, Mohamed Taha¹, Hala H. Zayed^1,2

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 papers from 20 distinct (13)… More >

Qingbing Ji^1,2,*, Zhihong Rao^1,2, 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 first clarifies the encryption mechanism… More >

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. Nonetheless, few studies have been… More >

G. Maria Jones^1,*, 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 (DL) algorithms to exploit suspicious… More >

Ziqing Yan^1,2, Pengpeng Yang^1,2, Rongrong Ni^1,2,*, Yao Zhao^1,2, 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 still a challenging task. In… More >

Imam Yuadi^1,*, 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 transforms, and combinations of features.… More >

Muhammad Asim Mubarik¹, Zhijian Wang¹, Yunyoung Nam^2,*, Seifedine Kadry³, Muhammad Azam waqar⁴

Computer Systems Science and Engineering, Vol.37, No.2, pp. 169-186, 2021, DOI:10.32604/csse.2021.014472

Abstract In this research, we developed a plugin for our automated digital forensics framework to extract and preserve the evidence from the Android and the IOS-based mobile phone application, Instagram. This plugin extracts personal details from Instagram users, e.g., name, user name, mobile number, ID, direct text or audio, video, and picture messages exchanged between different Instagram users. While developing the plugin, we identified resources available in both Android and IOS-based devices holding key forensics artifacts. We highlighted the poor privacy scheme employed by Instagram. This work, has shown how the sensitive data posted in the Instagram mobile application can easily… More >

Jian Li¹, Yang Lv¹, Bin Ma^1,*, Meihong Yang², Chunpeng Wang¹, Yang Zheng³

Computer Systems Science and Engineering, Vol.35, No.6, pp. 513-521, 2020, DOI:10.32604/csse.2020.35.513

Abstract Digital video has become one of the most preferred ways for people to share information. Considering people tend to release illegal information in anonymous way, the problem of video source identification attracts more and more attention as an important part of multimedia forensics. The Photo-Response Non-Uniformity (PRNU) based algorithm shows to be a promising solution for the problem of video source identification. However, it is necessary to make a geometric transformation for testing PRNU noise to align it with the reference noise, due to the effect of video stabilization. This paper analyzes the three-dimensional (3D) characteristics of camera jitters and… More >

Bingtao Hu^*, Jinwei Wang

Journal of Information Hiding and Privacy Protection, Vol.2, No.2, pp. 95-105, 2020, DOI:10.32604/jihpp.2020.010464

Abstract With the development of computer graphics, realistic computer graphics (CG) have become more and more common in our field of vision. This rendered image is invisible to the naked eye. How to effectively identify CG and natural images (NI) has been become a new issue in the field of digital forensics. In recent years, a series of deep learning network frameworks have shown great advantages in the field of images, which provides a good choice for us to solve this problem. This paper aims to track the latest developments and applications of deep learning in the field of CG and… More >