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Journal articles on the topic 'Electronic forgery'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Sezonov, Viktor, Mykhailo Fialka, Eduard Poltavski, Nataliia Prokopenko, and Maryna Fomenko. "Forensic Examination of Electronic Documents." Law, State and Telecommunications Review 14, no. 2 (2022): 81–93. http://dx.doi.org/10.26512/lstr.v14i2.40965.

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[Purpose] The purpose of the study is to reveal the concept and essence of forensic prevention of crimes of forgery of electronic documents, to identify problems in the use of information to establish a system of countering crime and document management. [Methodology] The following approaches were used in the work: system-structural, dialectical, empirical. Forgery of electronic documents and their use is investigated not only within the framework of a single criminal case but also by a set of crimes committed depending on the mechanism that is the main one in the structure of criminal technol

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2

Djamshedovich, Sadullaev Jaxongir. "Analysis of objective and subjective elements of the crime of document forgery, selling, or using forged documents." American Journal of Political Science Law and Criminology 7, no. 3 (2025): 65–70. https://doi.org/10.37547/tajpslc/volume07issue03-11.

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Document forgery represents one of the most pervasive and multifaceted crimes across jurisdictions, affecting areas such as contract law, property rights, financial transactions, and public trust in government-issued records. This study analyzes the objective (actus reus) and subjective (mens rea) elements of document forgery, selling of forged documents, and using forged documents, drawing on an extensive body of international legal scholarship, case law, and statutory frameworks. We discuss the conceptual foundations of forgery, the delineation between material and intellectual falsification

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Djamshedovich, Sadullaev Jaxongir. "Analysis of objective and subjective elements of the crime of document forgery, selling, or using forged documents." American Journal of Political Science Law and Criminology 7, no. 4 (2025): 23–28. https://doi.org/10.37547/tajpslc/volume07issue04-05.

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Document forgery represents one of the most pervasive and multifaceted crimes across jurisdictions, affecting areas such as contract law, property rights, financial transactions, and public trust in government-issued records. This study analyzes the objective (actus reus) and subjective (mens rea) elements of document forgery, selling of forged documents, and using forged documents, drawing on an extensive body of international legal scholarship, case law, and statutory frameworks. We discuss the conceptual foundations of forgery, the delineation between material and intellectual falsification

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Chervinska, Lyubov Volodymyrivna. "On the Problem of Normative Definition of the Concept of «Official Document» in the Criminal Code of Ukraine." Alʹmanah prava, no. 15 (September 1, 2024): 654–59. https://doi.org/10.33663/2524-017x-2024-15-654-659.

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der Articles 357 «Forgery of Documents, Seals, Stamps and Forms, Sale or Use of Forged Documents, Seals, Stamps», 358 «Forgery of Documents, Seals, Stamps and Forms, Sale or Use of Forged Documents, Seals, Stamps», 366 «Official Forgery» of the Criminal Code of Ukraine. The author analyzes the legal regulation of circulation of official documents of Ukraine and establishes the legislator’s approach to determining the content of a document, an official document, and its subtypes — paper and electronic official documents. The study of the regulatory consolidation and doctrinal development of the

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Lin, Yih-Kai, and Ting-Yu Yen. "A Meta-Learning Approach for Few-Shot Face Forgery Segmentation and Classification." Sensors 23, no. 7 (2023): 3647. http://dx.doi.org/10.3390/s23073647.

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The technology for detecting forged images is good at detecting known forgery methods. It trains neural networks using many original and corresponding forged images created with known methods. However, when encountering unseen forgery methods, the technology performs poorly. Recently, one suggested approach to tackle this problem is to use a hand-crafted generator of forged images to create a range of fake images, which can then be used to train the neural network. However, the aforementioned method has limited detection performance when encountering unseen forging techniques that the hand-cra

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Trček, Denis. "Minimising the risk of electronic document forgery." Computer Standards & Interfaces 19, no. 2 (1998): 161–67. http://dx.doi.org/10.1016/s0920-5489(98)00010-5.

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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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Zulki Zulkifli Noor. "Proof of the Legal Power of Electronic Certificates Against Criminal Acts of Forgery." Journal of Law, Politic and Humanities 4, no. 6 (2024): 2571–75. https://doi.org/10.38035/jlph.v4i6.846.

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his study aims to analyze the legal force of electronic certificates in relation to the crime of forgery. Electronic certificates as one of the digital legal instruments are recognized in Law Number 11 of 2008 concerning Electronic Information and Transactions (UU ITE), providing a strong legal basis for their recognition and validity in the evidence process. However, in its application, there are various challenges, especially related to data security and the risk of forgery. Through a normative legal approach, this study examines various laws and regulations as well as relevant case studies

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Xue, Ziyu, Xiuhua Jiang, Qingtong Liu, and Zhaoshan Wei. "Global–Local Facial Fusion Based GAN Generated Fake Face Detection." Sensors 23, no. 2 (2023): 616. http://dx.doi.org/10.3390/s23020616.

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Media content forgery is widely spread over the Internet and has raised severe societal concerns. With the development of deep learning, new technologies such as generative adversarial networks (GANs) and media forgery technology have already been utilized for politicians and celebrity forgery, which has a terrible impact on society. Existing GAN-generated face detection approaches rely on detecting image artifacts and the generated traces. However, these methods are model-specific, and the performance is deteriorated when faced with more complicated methods. What’s more, it is challenging to

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Kadam, Kalyani, Swati Ahirrao, and Ketan Kotecha. "AHP validated literature review of forgery type dependent passive image forgery detection with explainable AI." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 5 (2021): 4489. http://dx.doi.org/10.11591/ijece.v11i5.pp4489-4501.

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Nowadays, a lot of significance is given to what we read today: newspapers, magazines, news channels, and internet media, such as leading social networking sites like Facebook, Instagram, and Twitter. These are the primary wellsprings of phony news and are frequently utilized in malignant manners, for example, for horde incitement. In the recent decade, a tremendous increase in image information generation is happening due to the massive use of social networking services. Various image editing software like Skylum Luminar, Corel PaintShop Pro, Adobe Photoshop, and many others are used to creat

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فتيحة عمارة. "جريمة التزوير الإلكتروني = The Crime of Electronic Forgery". مجلة القانون و المجتمع 7, № 1 (2019): 166–89. http://dx.doi.org/10.12816/0054549.

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Al-Ameri, Mohammed Abdulbasit Ali, Bunyamin Ciylan, and Basim Mahmood. "Spectral Data Analysis for Forgery Detection in Official Documents: A Network-Based Approach." Electronics 11, no. 23 (2022): 4036. http://dx.doi.org/10.3390/electronics11234036.

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Despite the huge advances in digital communications in the last decade, physical documents are still the most common media for information transfer, especially in the official context. However, the readily available document processing devices and techniques (printers, scanners, etc.) facilitate the illegal manipulation or imitation of original documents by forgers. Therefore, verification of the authenticity and detection of forgery is of paramount importance to all agencies receiving printed documents. We suggest an unsupervised forgery detection framework that can distinguish whether a docu

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Li, Li, Jianfeng Lu, Shanqing Zhang, Linda Mohaisen, and Mahmoud Emam. "Frame Duplication Forgery Detection in Surveillance Video Sequences Using Textural Features." Electronics 12, no. 22 (2023): 4597. http://dx.doi.org/10.3390/electronics12224597.

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Frame duplication forgery is the most common inter-frame video forgery type to alter the contents of digital video sequences. It can be used for removing or duplicating some events within the same video sequences. Most of the existing frame duplication forgery detection methods fail to detect highly similar frames in the surveillance videos. In this paper, we propose a frame duplication forgery detection method based on textural feature analysis of video frames for digital video sequences. Firstly, we compute the single-level 2-D wavelet decomposition for each frame in the forged video sequenc

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Witasari, Aryani, and Aris Setiono. "PERLINDUNGAN HUKUM PENGGUNA JASA ELECTRONIC BANKING (E-BANKING) DI TINJAU DARI PERSPEKTIF HUKUM PIDANA DI INDONESIA." Jurnal Pembaharuan Hukum 2, no. 1 (2016): 126. http://dx.doi.org/10.26532/jph.v2i1.1422.

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Crime e-banking frequent one ATM card forgery. The perpetrators made a complete fake ATM cards with a magnetic stripe that already contains data records of card fraud. In addition to falsify the card, the perpetrators also know the PIN number of the card is duplicated / forged. ATM card forgery or duplication can be done because the necessary equipment to do so can be easily obtained in the market. This study uses normative legal approach by researching library materials or secondary data only, which relates to the legal protection of e-banking customers in the perspective of criminal law, usi

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Shelar, Yogita, Dr Prashant Sharma, and Dr Chandan Singh D. Rawat. "Image Forgery Detection Using Integrated Convolution-LSTM (2D) and Convolution (2D)." International Journal of Electrical and Electronics Research 11, no. 2 (2023): 631–38. http://dx.doi.org/10.37391/ijeer.110253.

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Digital forensics and computer vision must explore image forgery detection and their related technologies. Image fraud detection is expanding as sophisticated image editing software becomes more accessible. This makes changing photos easier than with the older methods. Convolution LSTM (1D) and Convolution LSTM (2D) + Convolution (2D) are popular deep learning models. We tested them using the public CASIA.2.0 image forgery database. ConvLSTM (2D) and its combination outperformed ConvLSTM (1D) in accuracy, precision, recall, and F1-score. We also provided a related work on image forgery detecti

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Jegaveerapandian, Liba Manopriya, Arockia Jansi Rani, Prakash Periyaswamy, and Sakthivel Velusamy. "A survey on passive digital video forgery detection techniques." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 6 (2023): 6324. http://dx.doi.org/10.11591/ijece.v13i6.pp6324-6334.

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Digital media devices such as smartphones, cameras, and notebooks are becoming increasingly popular. Through digital platforms such as Facebook, WhatsApp, Twitter, and others, people share digital images, videos, and audio in large quantities. Especially in a crime scene investigation, digital evidence plays a crucial role in a courtroom. Manipulating video content with high-quality software tools is easier, which helps fabricate video content more efficiently. It is therefore necessary to develop an authenticating method for detecting and verifying manipulated videos. The objective of this pa

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Nampoothiri V, Parameswaran, and Dr N. Sugitha. "An Optimized Fuzzy C-Means with Deep Neural Network for Image Copy-Move Forgery Detection." International Journal of Electrical and Electronics Research 12, no. 1 (2024): 308–14. http://dx.doi.org/10.37391/ijeer.120142.

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Copy Move Forgery Detection (CMFD) is one of the significant forgery attacks in which a region of the same image is copied and pasted to develop a forged image. Initially, the input digital images are preprocessed. Here the contrast of input image is enhanced. After preprocessing, Optimized Fuzzy C-means (OFCM) clustering is used to group the images into several clusters. Here the traditional FCM centroid selection is optimized by means of Salp Swarm Algorithm (SSA). The main inspiration of SSA is the swarming behavior of salps when navigating and foraging in oceans. Based on that algorithm, o

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18

Murray, L. "Art attack: spot the forgery." Engineering & Technology 16, no. 8 (2021): 58–63. http://dx.doi.org/10.1049/et.2021.0806.

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Chandrakala, Chandrakala, and Mungamuri Sasikala. "An efficient novel dual deep network architecture for video forgery detection." International Journal of Reconfigurable and Embedded Systems (IJRES) 13, no. 2 (2024): 458. http://dx.doi.org/10.11591/ijres.v13.i2.pp458-471.

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The technique of video copy-move forgery (CMF) is commonly employed in various industries; digital videography is regularly used as the foundation for vital graphic evidence that may be modified using the aforementioned method. Recently in the past few decades, forgery in digital images is detected via machine intellect. The second issue includes continuous allocation of parallel frames having relevant backgrounds erroneously results in false implications, detected as CMF regions third include as the CMF is divided into inter-frame or intra-frame forgeries to detect video copy is not possible

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Lin, Yih-Kai, and Hao-Lun Sun. "Few-Shot Training GAN for Face Forgery Classification and Segmentation Based on the Fine-Tune Approach." Electronics 12, no. 6 (2023): 1417. http://dx.doi.org/10.3390/electronics12061417.

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There are many techniques for faking videos that can alter the face in a video to look like another person. This type of fake video has caused a number of information security crises. Many deep learning-based detection methods have been developed for these forgery methods. These detection methods require a large amount of training data and thus cannot develop detectors quickly when new forgery methods emerge. In addition, traditional forgery detection refers to a classifier that outputs real or fake versions of the input images. If the detector can output a prediction of the fake area, i.e., a

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21

Restutomo Herjiwandono, Bayu, Sukisno Sukisno, and Nia Komalasari. "Perancangan Aplikasi Signature Electronic Dengan Qr-Code Pada Pt. Sankyu Indonesia Internasional." Jurnal Ilmiah Fakultas Teknik 4, no. 2 (2025): 149–89. https://doi.org/10.33592/jimtek.v4i2.7168.

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In the digital era, information technology is transforming various aspects of life, including education and business. Electronic Signature (eSign) have become a significant innovation in document verification and authentication, offering time efficiency and reduced administrative costs. PT. Sankyu Indonesia Internasional faces challenges in document management with manual Signature s, such as loss, damage, and forgery. To address this, an eSign application integrated with QR-Code was designed. This solution speeds up verification, reduces the risk of forgery, and enhances document Security. QR

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Maysaa, Abd Ulkareem Naser, Talib Jasi Eman, and M. Al-Mashhadi Haider. "QR code based two-factor authentication to verify paper-based documents." TELKOMNIKA Telecommunication, Computing, Electronics and Control 18, no. 4 (2020): 1834–42. https://doi.org/10.12928/TELKOMNIKA.v18i4.14339.

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Important paper-based documents exposed to forgery such as: official certificates, birth, marriage, death certificates, selling and buying documents and other legal documents is more and more serious and sophisticated. With the purposes of fraud, appropriation of property, job application and assignment in order to swindle public authorities, this forgery has led to material loss, belief deterioration as well as social instability. There are many techniques has been proposed to overcome this issue such as: ink stamps, live signatures, documented the transaction in third party like the court or

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Abd El-Latif, Eman I., and Nour Eldeen Khalifa. "COVID-19 digital x-rays forgery classification model using deep learning." IAES International Journal of Artificial Intelligence (IJ-AI) 12, no. 4 (2023): 1821. http://dx.doi.org/10.11591/ijai.v12.i4.pp1821-1827.

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<p>Nowadays, the internet has become a typical medium for sharing digital<br />images through web applications or social media and there was a rise in<br />concerns about digital image privacy. Image editing software’s have prepared<br />it incredibly simple to make changes to an image's content without leaving<br />any visible evidence for images in general and medical images in particular.<br />In this paper, the COVID-19 digital x-rays forgery classification model<br />utilizing deep learning will be introduced. The proposed system will be able<b

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Qazi, Tanzeela, Mushtaq Ali, Khizar Hayat, and Baptiste Magnier. "Seamless Copy–Move Replication in Digital Images." Journal of Imaging 8, no. 3 (2022): 69. http://dx.doi.org/10.3390/jimaging8030069.

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The importance and relevance of digital-image forensics has attracted researchers to establish different techniques for creating and detecting forgeries. The core category in passive image forgery is copy–move image forgery that affects the originality of image by applying a different transformation. In this paper, a frequency-domain image-manipulation method is presented. The method exploits the localized nature of discrete wavelet transform (DWT) to attain the region of the host image to be manipulated. Both patch and host image are subjected to DWT at the same level l to obtain 3l+1 sub-ban

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Sun, Yi, Jun Zheng, Lingjuan Lyn, et al. "The Same Name Is Not Always the Same: Correlating and Tracing Forgery Methods across Various Deepfake Datasets." Electronics 12, no. 11 (2023): 2353. http://dx.doi.org/10.3390/electronics12112353.

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Deepfakes are becoming increasingly ubiquitous, particularly in facial manipulation. Numerous researchers and companies have released multiple datasets of face deepfakes labeled to indicate different methods of forgery. However, naming these labels is often arbitrary and inconsistent, leading to the fact that most researchers now choose to use only one of the datasets for research work. However, researchers must use these datasets in practical applications and conduct traceability research. In this study, we employ some models to extract forgery features from various deepfake datasets and util

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Gadekar,, Supriya S. "Roadmap for Digital Image Forgery Detection Using Deep Learning." Tuijin Jishu/Journal of Propulsion Technology 44, no. 5 (2023): 1732–48. http://dx.doi.org/10.52783/tjjpt.v44.i5.2849.

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Technology advances are prominent today while influencing all aspects of our lives. Misuse of information has also increased as a result of technical improvements. As a result, investigators have the enormous task of recognizing modified information and distinguishing this from genuine data. Among the most prevalent techniques for electronic image alteration is splicing, which includes replicating a specific section using the same or different photograph and transferring it to a new image. In the wake of this issue, picture identification of forgeries has arisen as a viable approach for confir

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Chen, L. F., Z. K. Liu, and B. Y. Peng. "Security protection against optical forgery attack." Optics & Laser Technology 168 (January 2024): 109889. http://dx.doi.org/10.1016/j.optlastec.2023.109889.

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Li, Qian, Rangding Wang, and Dawen Xu. "A Video Splicing Forgery Detection and Localization Algorithm Based on Sensor Pattern Noise." Electronics 12, no. 6 (2023): 1362. http://dx.doi.org/10.3390/electronics12061362.

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Video splicing forgery is a common object-based intra-frame forgery operation. It refers to copying some regions, usually moving foreground objects, from one video to another. The splicing video usually contains two different modes of camera sensor pattern noise (SPN). Therefore, the SPN, which is called a camera fingerprint, can be used to detect video splicing operations. The paper proposes a video splicing detection and localization scheme based on SPN, which consists of detecting moving objects, estimating reference SPN, and calculating signed peak-to-correlation energy (SPCE). Firstly, fo

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Abdulazeem Ahmed, Eman, Malek Alzaqebah, Sana Jawarneh, et al. "Comparison of specific segmentation methods used for copy move detection." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 2 (2023): 2363. http://dx.doi.org/10.11591/ijece.v13i2.pp2363-2374.

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<p><span lang="EN-US">In this digital age, the widespread use of digital images and the availability of image editors have made the credibility of images controversial. To confirm the credibility of digital images many image forgery detection types are arises, copy-move forgery is consisting of transforming any image by duplicating a part of the image, to add or hide existing objects. Several methods have been proposed in the literature to detect copy-move forgery, these methods use the key point-based and block-based to find the duplicated areas. However, the key point-based and b

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Rai, Ashraf Fathi Al, and Nayel Musa AlOmran. "Criminal protection of electronic signatures from forgery in Jordanian and UAE legislation." International Journal of Electronic Governance 16, no. 2 (2024): 246–62. http://dx.doi.org/10.1504/ijeg.2024.140786.

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Alsakar, Yasmin M., Nagham E. Mekky, and Noha A. Hikal. "Detecting and Locating Passive Video Forgery Based on Low Computational Complexity Third-Order Tensor Representation." Journal of Imaging 7, no. 3 (2021): 47. http://dx.doi.org/10.3390/jimaging7030047.

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Great attention is paid to detecting video forgeries nowadays, especially with the widespread sharing of videos over social media and websites. Many video editing software programs are available and perform well in tampering with video contents or even creating fake videos. Forgery affects video integrity and authenticity and has serious implications. For example, digital videos for security and surveillance purposes are used as evidence in courts. In this paper, a newly developed passive video forgery scheme is introduced and discussed. The developed scheme is based on representing highly cor

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Rajalakshmi, C., Al M. Germanus, and R. Balasubramanian. "Copy move forgery detection using key point localized super pixel based on texture features." Computer Optics 43, no. 2 (2019): 270–76. http://dx.doi.org/10.18287/2412-6179-2019-43-2-270-276.

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The most important barrier in the image forensic is to ensue a forgery detection method such can detect the copied region which sustains rotation, scaling reflection, compressing or all. Traditional SIFT method is not good enough to yield good result. Matching accuracy is not good. In order to improve the accuracy in copy move forgery detection, this paper suggests a forgery detection method especially for copy move attack using Key Point Localized Super Pixel (KLSP). The proposed approach harmonizes both Super Pixel Segmentation using Lazy Random Walk (LRW) and Scale Invariant Feature Transfo

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Zhao, Kaiqi, Xiaochen Yuan, Zhiyao Xie, Yan Xiang, Guoheng Huang, and Li Feng. "SPA-Net: A Deep Learning Approach Enhanced Using a Span-Partial Structure and Attention Mechanism for Image Copy-Move Forgery Detection." Sensors 23, no. 14 (2023): 6430. http://dx.doi.org/10.3390/s23146430.

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With the wide application of visual sensors and development of digital image processing technology, image copy-move forgery detection (CMFD) has become more and more prevalent. Copy-move forgery is copying one or several areas of an image and pasting them into another part of the same image, and CMFD is an efficient means to expose this. There are improper uses of forged images in industry, the military, and daily life. In this paper, we present an efficient end-to-end deep learning approach for CMFD, using a span-partial structure and attention mechanism (SPA-Net). The SPA-Net extracts featur

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Kohli, Aditi, Abhinav Gupta, and Divya Singhal. "CNN based localisation of forged region in object-based forgery for HD videos." IET Image Processing 14, no. 5 (2020): 947–58. http://dx.doi.org/10.1049/iet-ipr.2019.0397.

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Moscatelli, Alberto. "Physically unclonable functions fight forgery." Nature Nanotechnology 17, no. 8 (2022): 818. http://dx.doi.org/10.1038/s41565-022-01194-1.

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Li, Zichen, Zhongxian Li, Yixian Yang, and Weilin Wu. "A new forgery attack on message recovery signatures." Journal of Electronics (China) 17, no. 3 (2000): 234–37. http://dx.doi.org/10.1007/s11767-000-0035-7.

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Huang, Shuan-Yu, Arvind Mukundan, Yu-Ming Tsao, Youngjo Kim, Fen-Chi Lin, and Hsiang-Chen Wang. "Recent Advances in Counterfeit Art, Document, Photo, Hologram, and Currency Detection Using Hyperspectral Imaging." Sensors 22, no. 19 (2022): 7308. http://dx.doi.org/10.3390/s22197308.

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Forgery and tampering continue to provide unnecessary economic burdens. Although new anti-forgery and counterfeiting technologies arise, they inadvertently lead to the sophistication of forgery techniques over time, to a point where detection is no longer viable without technological aid. Among the various optical techniques, one of the recently used techniques to detect counterfeit products is HSI, which captures a range of electromagnetic data. To aid in the further exploration and eventual application of the technique, this study categorizes and summarizes existing related studies on hypers

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Enumula, Mahesh, Dr M. Giri, and Dr V. K. Sharma. "A New Efficient Forgery Detection Method using Scaling, Binning, Noise Measuring Techniques and Artificial Intelligence (Ai)." International Journal of Innovative Technology and Exploring Engineering 12, no. 9 (2023): 17–21. http://dx.doi.org/10.35940/ijitee.i9703.0812923.

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In the market new updated editing tools and technologies are available to edit images and with help of these tools images are easily forged. In this research paper we proposed new forgery detection technique with estimation of noise on various scale of input image affect of noise in input image, frequency of images are also changed due to noise, noise signal correlated with original input images and in compressed images quantization level frequency also changed due to noise.We partition input image into M X N blocks, resized blocks are proceed further, image colors are also taken into consider

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Qazi, Tanzeela, Weiyao Lin, Samee U. Khan, et al. "Survey on blind image forgery detection." IET Image Processing 7, no. 7 (2013): 660–70. http://dx.doi.org/10.1049/iet-ipr.2012.0388.

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Taha Ahmed, Ismail, Baraa Tareq Hammad, and Norziana Jamil. "A comparative analysis of image copy-move forgery detection algorithms based on hand and machine-crafted features." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 2 (2021): 1177. http://dx.doi.org/10.11591/ijeecs.v22.i2.pp1177-1190.

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<span>Digital image forgery (DIF) is the act of deliberate alteration of an image to change the details transmitted by it. The manipulation may either add, delete or alter any of the image features or contents, without leaving any hint of the change induced. In general, copy-move forgery, also referred to as replication, is the most common of the various kinds of passive image forgery techniques. In the copy-move forgery, the basic process is copy/paste from one area to another in the same image. Over the past few decades various image copy-move forgery detection (IC-MFDs) surveys have b

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Ms., Jaya Giri. "Examination of Tampered Electronic Documents 'Kamalvidya'." International Journal of Trend in Scientific Research and Development 2, no. 5 (2018): 2221–31. https://doi.org/10.31142/ijtsrd18302.

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With the changing scenario of world, towards electronic passage it is important for one to maintain authenticity and move the document "As It Is" from the source to the destination in a defined manner. Computer reads any e document in binary language i.e. 0 and 1. The programme so designed is named "KamalVidya". Using this programme, it is possible to examine tampered electronic documents and will display the altered text in the allotted space. This programme can be used to investigate tampered e document as well as can be use to establish a secure passage for e document tr

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Yang, Jiachen, Guipeng Lan, Shuai Xiao, Yang Li, Jiabao Wen, and Yong Zhu. "Enriching Facial Anti-Spoofing Datasets via an Effective Face Swapping Framework." Sensors 22, no. 13 (2022): 4697. http://dx.doi.org/10.3390/s22134697.

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In the era of rapid development of the Internet of things, deep learning, and communication technologies, social media has become an indispensable element. However, while enjoying the convenience brought by technological innovation, people are also facing the negative impact brought by them. Taking the users’ portraits of multimedia systems as examples, with the maturity of deep facial forgery technologies, personal portraits are facing malicious tampering and forgery, which pose a potential threat to personal privacy security and social impact. At present, the deep forgery detection methods a

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Kumar, B. L. V. Vinay, and K. Raja Kumar. "Blockchain Solution for Evidence Forgery Detection." Journal of Computational and Theoretical Nanoscience 17, no. 12 (2020): 5570–76. http://dx.doi.org/10.1166/jctn.2020.9454.

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Rapidly improving video editing software tools have made video content manipulation feasible. Consequently malicious attackers are trying to manipulate the videos. Detecting video tampering is a major need for many applications. In this paper we propose a model called Evidence chain based on Blockchain to ensure the credibility of the video. Unlike bitcoin which is a digital currency the Proposed system documents video hash by using hash based technology and elliptic curve cryptography. Video segments are hashed and stored in chronological order as a chain of blocks which are detectable and no

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Jerold, Jerold, Suhaidi Suhaidi, and Isnaini Isnaini. "Upaya Imigrasi dalam Penerapan Sanksi Pidana Terhadap Pengguna Dokumen Perjalanan Palsu." ARBITER: Jurnal Ilmiah Magister Hukum 1, no. 2 (2019): 126–34. http://dx.doi.org/10.31289/arbiter.v1i2.115.

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The purpose of this study is to find out how the forms of falsification of the Travel Documents of the Republic of Indonesia, how the application of criminal sanctions for the forgeries of the Travel Documents of the Republic of Indonesia according to positive Indonesian law and how immigration actions in overcoming the fraudulent Travel Documents of the Republic of Indonesia occur. The research method used in this research is descriptive analysis, data collection techniques with literature studies and interviews, the types of data are primary data and secondary data, while the data analysis u

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Sumaiya Shaikh, Et al. "Video Forgery Detection: A Comprehensive Study of Inter and Intra Frame Forgery With Comparison of State-Of-Art." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9 (2023): 1487–97. http://dx.doi.org/10.17762/ijritcc.v11i9.9130.

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Availability of sophisticated and low-cost smart phones, digital cameras, camcorders, surveillance CCTV cameras are extensively used to create videos in our daily life. The prevalence of video sharing techniques presently available in the market are: YouTube, Facebook, Instagram, snapchat and many more are in utilization to share the information related to videos. Besides this, there are many software which can edit the content of video: Window Movie Maker, Video Editor, Adobe Photoshop etc., with this available software anyone can edit the video content which is called as “Forgery” if edited

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Zhang, Tianyi, and Yong Wang. "RLFAT: A Transformer-Based Relay Link Forged Attack Detection Mechanism in SDN." Electronics 12, no. 10 (2023): 2247. http://dx.doi.org/10.3390/electronics12102247.

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SDN is a modern internet architecture that has transformed the traditional internet structure in recent years. By segregating the control and data planes of the network, SDN facilitates centralized management, scalability, dynamism, and programmability. However, this very feature makes SDN controllers vulnerable to cyber attacks, which can cause network-wide crashes, unlike conventional networks. One of the most stealthy attacks that SDN controllers face is the relay link forgery attack in topology deception attacks. Such an attack can result in erroneous overall views for SDN controllers, lea

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Gardella, Marina, Pablo Musé, Jean-Michel Morel, and Miguel Colom. "Forgery Detection in Digital Images by Multi-Scale Noise Estimation." Journal of Imaging 7, no. 7 (2021): 119. http://dx.doi.org/10.3390/jimaging7070119.

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A complex processing chain is applied from the moment a raw image is acquired until the final image is obtained. This process transforms the originally Poisson-distributed noise into a complex noise model. Noise inconsistency analysis is a rich source for forgery detection, as forged regions have likely undergone a different processing pipeline or out-camera processing. We propose a multi-scale approach, which is shown to be suitable for analyzing the highly correlated noise present in JPEG-compressed images. We estimate a noise curve for each image block, in each color channel and at each sca

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Barglazan, Adrian-Alin, Remus Brad, and Constantin Constantinescu. "Image Inpainting Forgery Detection: A Review." Journal of Imaging 10, no. 2 (2024): 42. http://dx.doi.org/10.3390/jimaging10020042.

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In recent years, significant advancements in the field of machine learning have influenced the domain of image restoration. While these technological advancements present prospects for improving the quality of images, they also present difficulties, particularly the proliferation of manipulated or counterfeit multimedia information on the internet. The objective of this paper is to provide a comprehensive review of existing inpainting algorithms and forgery detections, with a specific emphasis on techniques that are designed for the purpose of removing objects from digital images. In this stud

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Yu, Miaomiao, Jun Zhang, Shuohao Li, Jun Lei, Fenglei Wang, and Hao Zhou. "Deep forgery discriminator via image degradation analysis." IET Image Processing 15, no. 11 (2021): 2478–93. http://dx.doi.org/10.1049/ipr2.12234.

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Xu, De, and Qing Yang. "The Systems Approach and Design Path of Electronic Bidding Systems Based on Blockchain Technology." Electronics 11, no. 21 (2022): 3501. http://dx.doi.org/10.3390/electronics11213501.

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The electronic tendering and bidding system has realized the digitalization, networking, and high integration of the whole process of tendering, bidding, bid evaluation, and contract, which has a wide range of applications. However, the trust degree, cooperation, and transaction efficiency of the parties involved in electronic bidding are low, and bidding fraud and collusion are forbidden repeatedly. Blockchain technology has the characteristics of decentralization, transparent transactions, traceability, non-tampering and forgery detection, and data security. This paper proposes a design path

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