Passive Video Tampering Detection Using Noise Features

2016 ◽  
pp. 279-303
Author(s):  
Ramesh Chand Pandey ◽  
Sanjay Kumar Singh ◽  
K. K. Shukla
Keyword(s):  
Digital Signature ◽  
Digital Video ◽  
Low Cost ◽  
Digital Watermark ◽  
Detection Technique ◽  
Video Editing ◽  
Tampering Detection ◽  
Detection Techniques ◽  
Processing Pipeline ◽  
Active Video

With increasing availability of low-cost video editing softwares and tools, the authenticity of digital video can no longer be trusted. Active video tampering detection technique utilize digital signature or digital watermark for the video tampering detection, but when the videos do not include such signature then it is very challenging to detect tampering in such video. To detect tampering in such video, passive video tampering detection techniques are required. In this chapter we have explained passive video tampering detection by using noise features. When video is captured with camera it passes through a Camera processing pipeline and this introduces noise in the video. Noise changes abruptly from authentic to forged frame blocks and provides a clue for video tampering detection. For extracting the noise we have considered different techniques like denoising algorithms, wavelet based denoising filter, and neighbor prediction.

scholarly journals A Review : Video Tampering Attacks and Detection Techniques

2019 ◽  
pp. 158-168
Author(s):  
Ruksana Habeeb ◽  
L. C. Manikandan
Keyword(s):  
Digital Video ◽  
Review Paper ◽  
Image Editing ◽  
Forgery Detection ◽  
Tampering Detection ◽  
Detection Techniques ◽  
Visual Evidence ◽  
Different Types ◽  
Video Forgery

Technological advancements of various video and image editing tools has reached such a level that the tampering of digital video or image can be performed easily without degrading their quality or leaving any visual evidence. This review paper presents an overview of various types of video forgery and the different types of techniques that are employed for its detection. Passive and active forgery detection techniques are commonly used methods for detecting the tampering in a digital video. Passive and active tampering detection techniques are utilized for detecting the integrity as well as the authenticity of a given video. The aim of this review is to provide some productive information about video tampering attacks for upcoming researchers.

BLUE SCREEN VIDEO FORGERY DETECTION AND LOCALIZATION USING AN ENHANCED 3-STAGE FOREGROUND ALGORITHM

2021 ◽  
Vol 5 (2) ◽  
pp. 133-144
Author(s):  
Kasim Shafii ◽  
Mustapha Aminu Bagiwa ◽  
A. A. Obiniyi ◽  
N. Sulaiman ◽  
A. M. Usman ◽  
...  
Keyword(s):  
Detection Rate ◽  
Digital Video ◽  
Gaussian Mixture ◽  
Detection Technique ◽  
Video Editing ◽  
Digital Videos ◽  
Positive Detection Rate ◽  
Video Forgery Detection ◽  
Video Forgery ◽  
Detection And Localization

The availability of easy to use video editing software has made it easy for cyber criminals to combine different videos from different sources using blue screen composition technology. This, makes the authenticity of such digital videos questionable and needs to be verified especially in the court of law. Blue Screen Composition is one of the ways to carry out video forgery using simple to use and affordable video editing software. Detecting this type of video forgery aims at revealing and observing the facts about a video so as to conclude whether the contents of the video have undergone any unethical manipulation. In this work, we propose an enhanced 3-stage foreground algorithm to detect Blue Screen manipulation in digital video. The proposed enhanced detection technique contains three (3) phases, extraction, detection and tracking. In the extraction phase, a Gaussian Mixture Model (GMM) is used to extract foreground element from a target video. Entropy function as a descriptive feature of image is extracted and calculated from the target video in the detection phase. The tracking phase seeks to use Minimum Output Sum of Squared Error (MOSSE) object tracking algorithm to fast track forged blocks of small sizes in a digital video. The result of the experiments demonstrates that the proposed detection technique can adequately detect Blue Screen video forgery when the forged region is small with a true positive detection rate of 98.02% and a false positive detection rate of 1.99%. The result of this our research can be used to

scholarly journals Digital Video Tampering Detection and Localization: Review, Representations, Challenges and Algorithm

Mathematics ◽  
2022 ◽  
Vol 10 (2) ◽  
pp. 168
Author(s):  
Naheed Akhtar ◽  
Mubbashar Saddique ◽  
Khurshid Asghar ◽  
Usama Ijaz Bajwa ◽  
Muhammad Hussain ◽  
...  
Keyword(s):  
Social Media ◽  
Low Cost ◽  
Video Recording ◽  
Research Work ◽  
Digital Videos ◽  
Tampering Detection ◽  
Detection Techniques ◽  
Significant Research ◽  
Art Research ◽  
Detection And Localization

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 tampering detection techniques in a systematic way. The answers to research questions prepared for this study are also elaborated. The state-of-the-art research work is analyzed extensively, highlighting the pros and cons and commonly used datasets. Limitations of existing video forensic algorithms are discussed, and we conclude with research challenges and future directions.

Browser Security Attacks and Detection Techniques: A Case of Tabnabbing

2020 ◽  
Vol 8 (1) ◽  
pp. 33-41
Author(s):  
Dr. S. Sarika ◽  
Keyword(s):  
Credit Card ◽  
State Of The Art ◽  
Experimental Results ◽  
Detection Technique ◽  
Security Attacks ◽  
Agent Based ◽  
Detection Techniques ◽  
Browser Security ◽  
Cyber Threats ◽  
Multi Agent

Phishing is a malicious and deliberate act of sending counterfeit messages or mimicking a webpage. The goal is either to steal sensitive credentials like login information and credit card details or to install malware on a victim’s machine. Browser-based cyber threats have become one of the biggest concerns in networked architectures. The most prolific form of browser attack is tabnabbing which happens in inactive browser tabs. In a tabnabbing attack, a fake page disguises itself as a genuine page to steal data. This paper presents a multi agent based tabnabbing detection technique. The method detects heuristic changes in a webpage when a tabnabbing attack happens and give a warning to the user. Experimental results show that the method performs better when compared with state of the art tabnabbing detection techniques.

scholarly journals Coview: A Cooperative Architecture for Digital Video Editing

2006 ◽  
Vol 115 (11-12) ◽  
pp. 482-491 ◽  
Author(s):  
Benjamim Fonseca ◽  
Eurico Carrapatoso
Keyword(s):  
Digital Video ◽  
Video Editing

scholarly journals An Overview of Digital Video Tampering Detection Using Passive Methods and D-Hash Algorithm

2018 ◽  
Vol 7 (4.6) ◽  
pp. 373
Author(s):  
Anto Crescentia.A ◽  
Sujatha. G
Keyword(s):  
Digital Video ◽  
Forgery Detection ◽  
Tampering Detection ◽  
Integrity Verification ◽  
Hash Algorithm ◽  
Area Of Concern ◽  
Detection Strategies ◽  
Inter Frame ◽  
Passive Techniques ◽  
Integrity Check

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 video. These strategies might be ordered into active and passive techniques. Therefore our area of concern in this paper is to present our views on different passive video tampering detection strategies and integrity check. Passive video tampering identification strategies are grouped into consequent three classifications depending on the type of counterfeiting as: Detection of double or multiple compressed videos, Region altering recognition and Video inter-frame forgery detection. So as to detect the tampering of the video, it is split into frames and hash is generated for a group of frames referred to as Group of Pictures. This hash value is verified by the receiver to detect tampering.    

An Improved Passive Anti-Islanding Technique for Distributed-Generation Photovoltaic Systems

2013 ◽  
Vol 433-435 ◽  
pp. 995-999
Author(s):  
Shao Ru Zhang ◽  
Shao Yuan Li
Keyword(s):  
High Reliability ◽  
Low Cost ◽  
Phase Variation ◽  
Operating Mode ◽  
Detection Zone ◽  
Electrical Grid ◽  
Detection Techniques ◽  
Frequency Detection ◽  
Grid Connected Inverter ◽  
Passive Techniques

Islanding detection techniques for DGPV are employed in order to determine the status of the electrical grid. In fact, the grid-connected inverter must be stopped once the islanding operating mode is detected according to standards and grid-code limits. Passive anti-islanding techniques monitor grid parameters to detect islanding. One advantage of passive techniques is a lower THD injected into the grid by active techniques. Thus, passive techniques were studied and an improved passive detection technique was proposed in this paper. The ratio of phase variation and the voltage variation at the point of common coupling (PCC) was adopted to detect islanding. In addition, this method combined with the under/over voltage detection and the under/over frequency detection. Then, the proposed technique not only has the merit of low cost and easy to operate, but also has multiple judgment and high reliability. The simulation results under Matlab/Simulink show that the proposed technique is very effective in reducing the non-detection zone and that the islanding operation can be detected more rapidly and effectively than traditional passive techniques, and that it can not misjudge when the load reduce suddenly.

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