Keyword Search:

Bookmark and Share

Passive video forgery detection techniques: a survey

Abdul Wahab, Ainuddin Wahid and Aminu Bagiwa, Mustapha and Idna Idris, Mohd Yamani and Khan, Suleman and Razak, Zaidi and Kamel Ariffin, Muhammad Rezal (2014) Passive video forgery detection techniques: a survey. In: 10th International Conference on Information Assurance and Security 2014, 28-30 Nov. 2014, Okinawa, Japan. pp. 29-34.

Full text not available from this repository.


Technological advancement of various video and image processing tools has made tempering of digital video easy and faster. This review paper focuses on passive techniques that are employed for detecting forgeries in a digital video. Passive forgery detection techniques are methods used for detecting the authenticity of a video without depending on pre-embedded information. The techniques exploit the use of statistical or mathematical properties that are distorted as a result of video tempering for forgery detection. Passive video forgery detection approach has a great prospect in multimedia security, information security and pattern recognition. In this paper, we divide passive techniques for video forensics into three categories; Statistical correlation of video features, frame-based for detecting statistical anomalies, and the inconsistency features of different digital equipment. The discussion also covers the trends, limitations and idea for improvements of passive forgery detection techniques

Item Type:Conference or Workshop Item (Paper)
Keyword:Digital investigation; Video forensics; Video forgery; Forgery detection; Passive techniques
Faculty or Institute:Faculty of Science
Institute for Mathematical Research
Publisher:IEEE (IEEE Xplore)
DOI Number:10.1109/ISIAS.2014.7064616
ID Code:38892
Deposited By: Nursyafinaz Mohd Noh
Deposited On:19 Jun 2015 12:16
Last Modified:19 Jun 2015 12:16

Repository Staff Only: Edit item detail

Document Download Statistics

This item has been downloaded for since 19 Jun 2015 12:16.

View statistics for "Passive video forgery detection techniques: a survey"