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Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Blind Image Source Device Identification: Practicality and Challenges

Blind Image Source Device Identification: Practicality and Challenges
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Author(s): Udaya Sameer Venkata (Department of Computer Science and Engineering, National Institute of Technology, Rourkela, India) and Ruchira Naskar (Department of Computer Science and Engineering, National Institute of Technology, Rourkela, India)
Copyright: 2020
Pages: 18
Source title: Cyber Warfare and Terrorism: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-2466-4.ch034

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Abstract

This article describes how digital forensic techniques for source investigation and identification enable forensic analysts to map an image under question to its source device, in a completely blind way, with no a-priori information about the storage and processing. Such techniques operate based on blind image fingerprinting or machine learning based modelling using appropriate image features. Although researchers till date have succeeded to achieve extremely high accuracy, more than 99% with 10-12 candidate cameras, as far as source device prediction is concerned, the practical application of the existing techniques is still doubtful. This is due to the existence of some critical open challenges in this domain, such as exact device linking, open-set challenge, classifier overfitting and counter forensics. In this article, the authors identify those open challenges, with an insight into possible solution strategies.

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