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Artykuły w czasopismach na temat „Digital tampering”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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1

Shen, Jingyi, Yun Yao, and Hao Mei. "Design of Image Copy-Paste Forensics System Based on Moment Invariants." International Journal for Innovation Education and Research 9, no. 11 (2021): 552–55. http://dx.doi.org/10.31686/ijier.vol9.iss11.3547.

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Copy-paste tampering is a common type of digital image tampering, which refers to copying a part of the image area in the same image, and then pasting it into another area of the image to generate a forged image, so as to carry out malicious operations such as fraud and framing. This kind of malicious forgery leads to the security problem of digital image. The research of digital image copy paste forensics has important theoretical significance and practical value. For digital image copy-paste tampering, this paper is based on moment invariant image copy paste tampering detection algorithm, an

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Chang, Yu Hong. "Based on Digital Image Forensics Double JPEG Compression Algorithm." Advanced Materials Research 1044-1045 (October 2014): 1098–101. http://dx.doi.org/10.4028/www.scientific.net/amr.1044-1045.1098.

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Means of digital image tampering diverse, new technical approach increasingly renovation, therefore, the detection of forged digital tampering issues are complex, and must not universal, once and for all solutions. In this paper, digital image tampering common practices through research, proposed a re-deposit operations for double JPEG image processing software compression testing technology method using image compression and decompression process lossy compression of images tamper with forensic, this method can play an effective role in the detection.

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Freiling, Felix, and Leonhard Hösch. "Controlled experiments in digital evidence tampering." Digital Investigation 24 (March 2018): S83—S92. http://dx.doi.org/10.1016/j.diin.2018.01.011.

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Aminu, Ali Ahmad, and Nwojo Nnanna Agwu. "General Purpose Image Tampering Detection using Convolutional Neural Network and Local Optimal Oriented Pattern (LOOP)." Signal & Image Processing : An International Journal 12, no. 2 (2021): 13–32. http://dx.doi.org/10.5121/sipij.2021.12202.

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Digital image tampering detection has been an active area of research in recent times due to the ease with which digital image can be modified to convey false or misleading information. To address this problem, several studies have proposed forensics algorithms for digital image tampering detection. While these approaches have shown remarkable improvement, most of them only focused on detecting a specific type of image tampering. The limitation of these approaches is that new forensic method must be designed for each new manipulation approach that is developed. Consequently, there is a need to

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Tang, Bin, Mengyao Sun, Haowen Zheng, Haiyun Han, and Yu Jin. "Analysis of Digital Media Image Tampering and Forgery Control." Transactions on Computer Science and Intelligent Systems Research 5 (August 12, 2024): 1073–77. http://dx.doi.org/10.62051/f9e87g27.

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In recent years, the continuous innovation of computer vision processing technology has greatly improved the quality of people's production and life, while the accompanying tampering risk has also gradually increased. There are frequent incidents of people with ulterior motives using computer image processing technology to tamper with digital media and falsifying and cheating others. This paper mainly analyzes the technology and method of digital media image tampering and forgery, the social harm caused by the resulting tampering risk, and puts forward the corresponding management countermeasu

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6

Wei, Wang, and Tang Bin. "Analysis on Feasible Methods of Digital Image Tampering Detection." Highlights in Science, Engineering and Technology 44 (April 13, 2023): 371–76. http://dx.doi.org/10.54097/hset.v44i.7386.

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In order to solve the problem of image tampering detection in the blind forensics of digital images, this study first researches and summarizes the means and methods of image tampering and forgery, and provides suggestions for methods of tampering detection using open source tools for the methods that may be used for falsification. These methods have been publicly tested by open source companies for a long time, which proves their feasibility. The methods and conclusions suggested by the research can be used in the "falsification" application of pictures in many fields, and have certain academ

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7

Mualfah, Desti, Yoze Rizki, and Meiriladiwis Gea. "Analisis Digital Forensik Keaslian Video Rekaman CCTV Menggunakan Metode Localization Tampering." Jurnal CoSciTech (Computer Science and Information Technology) 3, no. 1 (2022): 43–51. http://dx.doi.org/10.37859/coscitech.v3i1.3697.

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Video is one the valid evidence if the handling process is in accordance with digital forensic procedures. Closed circuit television is a video sourse that is often used as authentic evidence in court. The authenticity of the video is something that is often doubted by certain parties. For this reason, this discusses how to detect the authenticity of video as digital evidence by comparing the original video files and tampering video files resulting from attack frame addition and attack frame delection. The media info tool is used to analyze the metadata and the localization tampering method is

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8

Mainoo, Bernard. "Digital Multimedia Tampering Detection for Forensics Analysis." Advances in Multidisciplinary and scientific Research Journal Publication 1, no. 1 (2022): 81–90. http://dx.doi.org/10.22624/aims/crp-bk3-p14.

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In the virtual multimedia era, digital forensics is turning into a rising location of studies way to the huge quantity of picture and video documents generated. Ensuring the integrity of such media is of top-notch significance in lots of situations. This mission has end up extra complex, particularly with the development of symmetrical and asymmetrical community systems which make their authenticity tough. Consequently, it's far definitely vital to find out all feasible modes of manipulation through the improvement of latest forensics detector tools. For example, the symmetry and asymmetry inc

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9

Schneider, Janine, Linus Düsel, Benedikt Lorch, Julia Drafz, and Felix Freiling. "Prudent design principles for digital tampering experiments." Forensic Science International: Digital Investigation 40 (April 2022): 301334. http://dx.doi.org/10.1016/j.fsidi.2022.301334.

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Parashar, Nishtha, and Nirupama Tiwari. "A Survey Of Digital Image Tampering Techniques." International Journal of Signal Processing, Image Processing and Pattern Recognition 8, no. 10 (2015): 91–96. http://dx.doi.org/10.14257/ijsip.2015.8.10.10.

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Parashar, Nishtha, Nirupama Tiwari, and Deepika Dubey. "A Survey of Digital Image Tampering Techniques." International Journal of Signal Processing, Image Processing and Pattern Recognition 9, no. 2 (2016): 415–20. http://dx.doi.org/10.14257/ijsip.2016.9.2.35.

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Joseph*, Silpa, and S. Palani kumar. "Detection and Localization of Image and Video Tampering." International Journal of Innovative Technology and Exploring Engineering 9, no. 4 (2020): 1951–56. http://dx.doi.org/10.35940/ijitee.c1158.029420.

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Digital images and videos are widely used in various fields like courtrooms ,military ,medicine ,research, social media etc. So, maintaining the authenticity and integrity of these digital contents is a major concern. For the past few years, researches were going on to find out tampering in the digital contents. Active and passive approaches are the major classification for digital tampering detection. Here, we discuss some of the active and passive approaches and their significance in the current scenario.

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13

Jain, Ayushi. "Tampering Detection and Content Authentication Using Encrypted Perceptual Hash for Image Database." Mathematical Statistician and Engineering Applications 70, no. 2 (2021): 1695–705. http://dx.doi.org/10.17762/msea.v70i2.2460.

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To detect and locate unapproved alterations or modifications made to digital pictures, tampering detection in images is a crucial study topic in the field of image forensics. As sophisticated picture altering tools become more widely available, it has become more difficult to guarantee the integrity and authenticity of digital visual output. This overview of the literature explores methodology, findings, and contributions in key tampering detection research studies. The breakthroughs in deep learning techniques and steganalysis are highlighted together with more conventional approaches like st

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14

Li, Su Ying. "Round Descriptor Based on SIFT Operator Copy and Paste Forensics." Advanced Materials Research 912-914 (April 2014): 1379–82. http://dx.doi.org/10.4028/www.scientific.net/amr.912-914.1379.

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Powerful digital cameras and image processing software, so that the image of tampering counterfeit technology is developing rapidly, the role of digital images to verify the authenticity and the beginning of forensics technology will become more important. For the most common digital image tampering copy and paste operation, this paper presents a round-based SIFT descriptor operator forensic image copy and paste algorithm that extracts the image to be detected circular feature vector descriptor, and using feature vectors copy and paste the image matching to detect and locate the area. Experime

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15

Shkilev, Roman, Alevtina Kormiltseva, Marina Achaeva, Aiziryak Tarasova, and Marguba Matquliyeva. "Fortifying Textual Integrity: Evolutionary Optimization-powered Watermarking for Tampering Attack Detection in Digital Documents." Fusion: Practice and Applications 14, no. 2 (2024): 97–108. http://dx.doi.org/10.54216/fpa.140208.

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Digital document helps as the lifeblood of present communication, yet their vulnerability to tampering poses major safety anxieties. Digital text watermarking is an effective mechanism to protect the reliability of text-based data in the digital. Introducing a hidden layer of accountability and safety, allows individuals and organizations to trust the written word and make sure the truth behind all the files. Watermarking model identifies the tampering attack by inspecting the embedded signature for distortions or alterations. Watermarks can able to mechanically classify and repair themselves

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16

Sarhan, M. Musa1. "DIGITAL FORGERY." International Journal of Advances In Scientific Research and Engineering (IJASRE) 3, no. 4 (2017): 26–29. https://doi.org/10.5281/zenodo.581732.

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<em>Forgery is the criminal act that provides misleading information about a product or service. It is the process of making, adapting, or imitating documents or objects with the intent to deceive. Digital forgery (or digital tampering) is the process of manipulating documents or images for the intent of financial, social or political gain. This paper provides a brief introduction to the digital forgery.</em>

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17

Crescentia.A, Anto, and Sujatha G. "An Overview of Digital Video Tampering Detection Using Passive Methods and D-Hash Algorithm." International Journal of Engineering & Technology 7, no. 4.6 (2018): 373. http://dx.doi.org/10.14419/ijet.v7i4.6.28444.

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Video tampering and integrity detection can be defined as methods of alteration of the contents of the video which will enable it to hide objects, an occasion or adjust the importance passed on by the collection of images in the video. Modification of video contents is growing rapidly due to the expansion of the video procurement gadgets and great video altering programming devices. Subsequently verification of video files is transforming into something very vital. Video integrity verification aims to search out the hints of altering and subsequently asses the realness and uprightness of the v

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Agarwal, Ritu, and Mallika Pant. "Image tampering detection using genetic algorithm." MATEC Web of Conferences 277 (2019): 02026. http://dx.doi.org/10.1051/matecconf/201927702026.

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As digital images become an indispensable source of information, the authentication of digital images has become crucial. Various techniques of forgery have come into existence, intrusive, and non-intrusive. Image forgery detection hence is becoming more challenging by the day, due to the unwavering advances in image processing. Therefore, image forensics is at the forefront of security applications aiming at restoring trust and acceptance in digital media by exposing counterfeiting methods. The proposed work compares between various feature selection algorithms for the detection of image forg

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19

Fallahpour, Mehdi, Shervin Shirmohammadi, Mehdi Semsarzadeh, and Jiying Zhao. "Tampering Detection in Compressed Digital Video Using Watermarking." IEEE Transactions on Instrumentation and Measurement 63, no. 5 (2014): 1057–72. http://dx.doi.org/10.1109/tim.2014.2299371.

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Hsu, Ching-Sheng, and Shu-Fen Tu. "Probability-based tampering detection scheme for digital images." Optics Communications 283, no. 9 (2010): 1737–43. http://dx.doi.org/10.1016/j.optcom.2009.12.073.

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Chen, Xiangning, Weitao Yuan, Shengbei Wang, Chao Wang, and Lin Wang. "Speech Watermarking for Tampering Detection Based on Modifications to LSFs." Mathematical Problems in Engineering 2019 (December 17, 2019): 1–10. http://dx.doi.org/10.1155/2019/7285624.

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There have been serious issues concerning the protection of speech signals from malicious tampering. Digital watermarking has been paid much attention in solving this problem. This paper proposes a tampering detection approach based on speech watermarking by modifying the line spectral frequencies (LSFs). Watermarks are embedded into LSFs that derived from linear prediction (LP) analysis with dither modulation-quantization index modulation (DM-QIM). Minor modifications to LSFs introduced by quantization not only enable the watermarks to be inaudible to human auditory system but also provide th

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22

Zeng, Pingping, Lianhui Tong, Yaru Liang, Nanrun Zhou, and Jianhua Wu. "Multitask Image Splicing Tampering Detection Based on Attention Mechanism." Mathematics 10, no. 20 (2022): 3852. http://dx.doi.org/10.3390/math10203852.

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In today’s modern communication society, the authenticity of digital media has never been of such importance as it is now. In this aspect, the reliability of digital images is of paramount importance because images can be easily manipulated by means of sophisticated software, such as Photoshop. Splicing tampering is a commonly used photographic manipulation for modifying images. Detecting splicing tampering remains a challenging task in the area of image forensics. A new multitask model based on attention mechanism, densely connected network, Atrous Spatial Pyramid Pooling (ASPP) and U-Net for

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Lu, Wenhuan, Zonglei Chen, Ling Li, et al. "Watermarking Based on Compressive Sensing for Digital Speech Detection and Recovery †." Sensors 18, no. 7 (2018): 2390. http://dx.doi.org/10.3390/s18072390.

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In this paper, a novel imperceptible, fragile and blind watermark scheme is proposed for speech tampering detection and self-recovery. The embedded watermark data for content recovery is calculated from the original discrete cosine transform (DCT) coefficients of host speech. The watermark information is shared in a frames-group instead of stored in one frame. The scheme trades off between the data waste problem and the tampering coincidence problem. When a part of a watermarked speech signal is tampered with, one can accurately localize the tampered area, the watermark data in the area withou

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Guan, Zekai. "A Review of Feature Matching Based Image Tampering Detection Methods." Applied and Computational Engineering 135, no. 1 (2025): 49–56. https://doi.org/10.54254/2755-2721/2025.21080.

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In recent years, digital image tampering detection techniques play an increasingly important role in dealing with digital image authenticity detection. This review analyzes in detail the feature matching based image tampering detection methods that mainly target the copy-paste tampering problem. Among such methods are subdivided into two subcategories: feature block-based and feature point-based detection. Traditional methods such as feature-point based SIFT and feature-block based Zernike Moments match by extracting local features or global features, but their performance is limited under hig

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25

K. K, Sindhu. "Digital Forensic Investigation on File System And Database Tampering." IOSR Journal of Engineering 02, no. 02 (2012): 2142–221. http://dx.doi.org/10.9790/3021-0202214221.

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Anderson, C. "Easy-to-alter digital images raise fears of tampering." Science 263, no. 5145 (1994): 317–18. http://dx.doi.org/10.1126/science.8278802.

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Sitara, K., and B. M. Mehtre. "Digital video tampering detection: An overview of passive techniques." Digital Investigation 18 (September 2016): 8–22. http://dx.doi.org/10.1016/j.diin.2016.06.003.

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Vijayaraghavan, P., M. Joe Nelson, R. Prasanna, and M. K. Raghavendran. "Surveillance Footage Video Tampering Detection." Informatica : Journal of Applied Machines Electrical Electronics Computer Science and Communication Systems 01, no. 01 (2020): 10–16. http://dx.doi.org/10.47812/ijamecs2010102.

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The quality of the captured images was enhanced by some of the first digital video and image processing applications, but as the power of computers expanded, so did the number of applications where video and image processing could make a difference. Video and image processing are used in many different applications nowadays. To provide authenticity to a video several video processing software’s are used. Video tampering detection is the one of the important Security applications. Video processing software is also used to eliminate specific moving foreground from a video. But algorithms which w

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Alfian, Alfiansyah Imanda Putra, Rusydi Umar, and Abdul Fadlil. "Penerapan Metode Localization Tampering dan Hashing untuk Deteksi Rekayasa Video Digital." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 5, no. 2 (2021): 400–406. http://dx.doi.org/10.29207/resti.v5i2.3015.

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The development of digital video technology which is increasingly advanced makes digital video engineering crimes prone to occur. The change in digital video has changed information communication, and it is easy to use in digital crime. One way to solve this digital crime case is to use the NIST (National Institute of Standards and Technology) method for video forensics. The initial stage is carried out by collecting data and carrying out the process of extracting the collected results. A local hash and noise algorithm can then be used to analyze the resulting results, which will detect any di

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Li, Yewen, Wei Song, Xiaobing Zhao, Juan Wang, and Lizhi Zhao. "A Novel Image Tamper Detection and Self-Recovery Algorithm Based on Watermarking and Chaotic System." Mathematics 7, no. 10 (2019): 955. http://dx.doi.org/10.3390/math7100955.

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With the development of image editing software techniques, the content integrity and authenticity of original digital images become more and more important in digital content security. A novel image tampering detection and recovery algorithm based on digital watermarking technology and a chaotic system is proposed, and it can effectively locate the tampering region and achieve the approximate recovery of the original image by using the hidden information. The pseudo-random cyclic chain is realized by the chaotic system to construct the mapping relationship between the image subblocks. It can e

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He, Yong Hui. "Image Tampering with Evidence Algorithm Based on Copy and Paste." Advanced Materials Research 1044-1045 (October 2014): 1178–81. http://dx.doi.org/10.4028/www.scientific.net/amr.1044-1045.1178.

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Authenticity, integrity and authentication primitive technology for digital image content case of digital image forensics, as one branch of information security technology, is not pre-embedded image watermarks to forensic identification. In this paper, a common digital image tampering copy and paste operations have been studied and proposed detection method for this operation to improve the robustness of the algorithm.

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Wang, Xinyi, Shaozhang Niu, and Jiwei Zhang. "Digital Image Forensics Based on CFA Interpolation Feature and Gaussian Mixture Model." International Journal of Digital Crime and Forensics 11, no. 2 (2019): 1–12. http://dx.doi.org/10.4018/ijdcf.2019040101.

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According to the characteristics of the color filter array interpolation in a camera, an image splicing forgery detection algorithm based on bi-cubic interpolation and Gaussian mixture model is proposed. The authors make the assumption that the image is acquired using a color filter array, and that tampering removes the artifacts due to a demosaicing algorithm. This article extracts the image features based on the variance of the prediction error and create image feature likelihood map to detect and locate the image tampered areas. The experimental results show that the proposed method can det

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Khachane, Siddharth, and Deepmalya Mondal. "Image Tampering Detection using Error Level Analysis and Concatenated Neural Networks." International Journal for Research in Applied Science and Engineering Technology 11, no. 7 (2023): 2011–18. http://dx.doi.org/10.22214/ijraset.2023.55067.

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Abstract: Image tampering has become a leading issue in the digital age, which has given rise to serious implications in various fields such as journalism, forensics and photography. Detecting manipulated images with high accuracy is important to ensure the authenticity and credibility of visual content. In this research paper, we propose a robust and effective approach for image tampering detection utilizing a concatenated ResNet and XceptionNet model with Error Level Analysis which has achieved an accuracy of 98.58%.

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M, N. Vinitha Reddy, Thirumalesh K, Devraju P, Waseem Baig M, and Mohammed Ali S. "Bridging Restoration and Forensics: A Novel Framework for Image Tampering Detection." International Journal of Computational Learning & Intelligence 4, no. 3 (2025): 513–21. https://doi.org/10.5281/zenodo.15210515.

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With the widespread manipulation of digital images, accurately detecting and localizing tampered regions has become a critical task in image forensics. However, most existing tampering localization methods struggle when images undergo post-processing operations such as compression, which obscure crucial tampering traces. To address this, we propose a ranking-based tampering detection framework that evaluates image authenticity by assigning ranks, calculating distances between images, and identifying possible tampering. Our system processes images by extracting key features and assigning a rank

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Kingra, Staffy, Naveen Aggarwal, and Raahat Devender Singh. "Video Inter-frame Forgery Detection Approach for Surveillance and Mobile Recorded Videos." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 2 (2017): 831. http://dx.doi.org/10.11591/ijece.v7i2.pp831-841.

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We are living in an age where use of multimedia technologies like digital recorders and mobile phones is increasing rapidly. On the other hand, digital content manipulating softwares are also increasing making it easy for an individual to doctor the recorded content with trivial consumption of time and wealth. Digital multimedia forensics is gaining utmost importance to restrict unethical use of such easily available tampering techniques. These days, it is common for people to record videos using their smart phones. We have also witnessed a sudden growth in the use of surveillance cameras, whi

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Staffy, Kingra, Aggarwal Naveen, and Devender Singh Raahat. "Mobile Recorded Videos." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 2 (2017): 831–41. https://doi.org/10.11591/ijece.v7i2.pp831-841.

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We are living in an age where use of multimedia technologies like digital recorders and mobile phones is increasing rapidly. On the other hand, digital content manipulating softwares are also increasing making it easy for an individual to doctor the recorded content with trivial consumption of time and wealth. Digital multimedia forensics is gaining utmost importance to restrict unethical use of such easily available tampering techniques. These days, it is common for people to record videos using their smart phones. We have also witnessed a sudden growth in the use of surveillance cameras, whi

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Sadiku, Matthew N. O., Adebowale E. Shadare, and Sarhan M. Musa. "Digital Chain of Custody." International Journal of Advanced Research in Computer Science and Software Engineering 7, no. 7 (2017): 117. http://dx.doi.org/10.23956/ijarcsse.v7i7.109.

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Digital chain of custody is the record of preservation of digital evidence from collection to presentation in the court of law. This is an essential part of digital investigation process. Its key objective is to ensure that the digital evidence presented to the court remains as originally collected, without tampering. The chain of custody is important for admissible evidence in court. Without a chain of custody, the opposing attorney can challenge or dismiss the evidence presented. The aim of this paper is to provide a brief introduction to the concept of digital chain custody.

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Manikantan, K. "Analyse And Overview on Digital Image Tampering Detection Using Matlab." International Journal of Computer Sciences and Engineering 6, no. 8 (2018): 902–6. http://dx.doi.org/10.26438/ijcse/v6i8.902906.

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Bourouis, Sami, Roobaea Alroobaea, Abdullah M. Alharbi, Murad Andejany, and Saeed Rubaiee. "Recent Advances in Digital Multimedia Tampering Detection for Forensics Analysis." Symmetry 12, no. 11 (2020): 1811. http://dx.doi.org/10.3390/sym12111811.

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In the digital multimedia era, digital forensics is becoming an emerging area of research thanks to the large amount of image and video files generated. Ensuring the integrity of such media is of great importance in many situations. This task has become more complex, especially with the progress of symmetrical and asymmetrical network structures which make their authenticity difficult. Consequently, it is absolutely imperative to discover all possible modes of manipulation through the development of new forensics detector tools. Although many solutions have been developed, tamper-detection per

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Yang, Chen-Kuei, and Chang-Sheng Huang. "A Novel Watermarking Technique for Tampering Detection in Digital Images." ELCVIA Electronic Letters on Computer Vision and Image Analysis 3, no. 1 (2003): 1. http://dx.doi.org/10.5565/rev/elcvia.65.

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Wei, Hui, Gao-bo Yang, and Ming Xia. "A Digital Video Tampering Forensics Scheme Based on Forensics Hash." Journal of Electronics & Information Technology 35, no. 12 (2014): 2934–41. http://dx.doi.org/10.3724/sp.j.1146.2013.00296.

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Abbadi, Nidhal, and Alyaa Mohsin. "Blind Digital Images Tampering Detection Based on Singular Value Decomposition." International Journal of Intelligent Engineering and Systems 13, no. 6 (2020): 338–48. http://dx.doi.org/10.22266/ijies2020.1231.30.

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The growing use of digital images in a wide range of applications, and growing the availability of many editing photo software, cause to emerge a challenge to discover the images tampering. In this paper, we proposed a method to detect the most important type of forgery image (copy and move). We suggested many steps to classify the image as forgery or non-forgery image, started with preprocessing (included, convert image to gray image, de-noising, and image resize). Then, the image will be divided into several overlapping blocks. For each block, feature extracted (used it as a matching feature

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Saha, Monica. "Forensic Technique for Forgery Detection and Localization in Digital Image." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 2721–27. https://doi.org/10.22214/ijraset.2025.68495.

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Abstract: The widespread availability of advanced image editing software has transformed digital image forgery into an urgent issue in multimedia forensics. Traditional forgery methods—copy-move, splicing, and retouching—taint the authenticity of digital images, allowing malicious individuals to disseminate misinformation, tamper with legal evidence, and compromise digital trust. Forgery detection and localization are crucial for uses in cybersecurity, journalism, law enforcement, and digital forensics.This paper provides a systematic survey and comparative evaluation of the latest forensic me

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Nour Mohammad, Hasan Fayyad-Kazan, Mohamad Saab. "Anti- Forensics: The Tampering of Media." International Journal on Recent and Innovation Trends in Computing and Communication 8, no. 10 (2020): 06–30. http://dx.doi.org/10.17762/ijritcc.v8i10.5447.

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In the context of forensic investigations, the traditional understanding of evidence is changing where nowadays most prosecutors, lawyers and judges heavily rely on multimedia signs. This modern shift has allowed the law enforcement to better reconstruct the crime scenes or reveal the truth of any critical event.In this paper we shed the light on the role of video, audio and photos as forensic evidences presenting the possibility of their tampering by various easy-to-use, available anti-forensics softwares. We proved that along with the forensic analysis, digital processing, enhancement and au

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S, Manjunatha, and Malini M. Patil. "Efficient resampling features and convolution neural network model for image forgery detection." Indonesian Journal of Electrical Engineering and Computer Science 25, no. 1 (2022): 183. http://dx.doi.org/10.11591/ijeecs.v25.i1.pp183-190.

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The extended utilization of picture-enhancing or manipulating tools has led to ease of manipulating multimedia data which includes digital images. These manipulations will disturb the truthfulness and lawfulness of images, resulting in misapprehension, and might disturb social security. The image forensic approach has been employed for detecting whether or not an image has been manipulated with the usage of positive attacks which includes splicing, and copy-move. This paper provides a competent tampering detection technique using resampling features and convolution neural network (CNN). In thi

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S, Manjunatha, and Malini M. Patil. "Efficient resampling features and convolution neural network model for image forgery detection." Indonesian Journal of Electrical Engineering and Computer Science 25, no. 1 (2022): 183–90. https://doi.org/10.11591/ijeecs.v25.i1.pp183-190.

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The extended utilization of picture-enhancing or manipulating tools has led to ease of manipulating multimedia data which includes digital images. These manipulations will disturb the truthfulness and lawfulness of images, resulting in misapprehension, and might disturb social security. The image forensic approach has been employed for detecting whether or not an image has been manipulated with the usage of positive attacks which includes splicing, and copy-move. This paper provides a competent tampering detection technique using resampling features and convolution neural network (CNN). In thi

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Akhtar, Naheed, Mubbashar Saddique, Khurshid Asghar, Usama Ijaz Bajwa, Muhammad Hussain, and Zulfiqar Habib. "Digital Video Tampering Detection and Localization: Review, Representations, Challenges and Algorithm." Mathematics 10, no. 2 (2022): 168. http://dx.doi.org/10.3390/math10020168.

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Digital videos are now low-cost, easy to capture and easy to share on social media due to the common feature of video recording in smart phones and digital devices. However, with the advancement of video editing tools, videos can be tampered (forged) easily for propaganda or to gain illegal advantages—ultimately, the authenticity of videos shared on social media cannot be taken for granted. Over the years, significant research has been devoted to developing new techniques for detecting different types of video tampering. In this paper, we offer a detailed review of existing passive video tampe

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Onn, Ng Ching, Siti Nur Avivah, Mohammad Minhazul Alam, and Abubakar Ahmad. "Secure and Effective Image Integrity and Copyright Protection Using Two-Layer Authentication with Integer Wavelet Transform." IJACI : International Journal of Advanced Computing and Informatics 1, no. 1 (2025): 13–27. https://doi.org/10.71129/ijaci.v1.i1.pp13-27.

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The pervasive adoption of internet and digital communication technologies renders multimedia data, particularly images, vulnerable to piracy due to the ease with which unauthorized users can manipulate them. This research advocates for the application of IWT and SVD grounded in human visual characteristics to embed watermarks into host images, thereby fortifying their resilience against attacks while minimizing distortions in image quality. Authentication bits extracted from the content of 3×3-pixel blocks within the image are subsequently incorporated into the watermarked image, positioned wi

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Gorle, Ramesh, and Anitha Guttavelli. "Enhanced Image Tampering Detection using Error Level Analysis and CNN." Engineering, Technology & Applied Science Research 15, no. 1 (2025): 19683–89. https://doi.org/10.48084/etasr.9593.

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This paper introduces a novel approach to image tampering detection by integrating Error Level Analysis (ELA) with a Convolutional Neural Network (CNN). Traditional forensic methods, such as ELA and Residual Pixel Analysis (RPA), often struggle to detect subtle or advanced manipulations in digital images. To address these limitations, this method leverages ELA to highlight compression-induced variations and CNN to extract and classify spatial features indicative of tampering. The dataset, consisting of both authentic and tampered images, was preprocessed to generate ELA representations, which

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Li, Xuejing, Qiancheng Chen, Runfu Chu, and Wei Wang. "Block mapping and dual-matrix-based watermarking for image authentication with self-recovery capability." PLOS ONE 19, no. 2 (2024): e0297632. http://dx.doi.org/10.1371/journal.pone.0297632.

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Numerous image authentication techniques have been devised to address the potential security issue of malicious tampering with image content since digital images can be easily duplicated, modified, transformed and diffused via the Internet transmission. However, the existing works still remain many shortcomings in terms of the recovery incapability and detection accuracy with extensive tampering. To improve the performance of tamper detection and image recovery, we present a block mapping and dual-matrix-based watermarking scheme for image authentication with self-recovery capability in this p

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