The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Blind Image Source Device Identification: Practicality and Challenges
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.
Related Content
|
Vivek Bhardwaj, Bilal Ahmed, Mirza Shuja, Deepak Thakur, Tanya Gera, Mukesh Kumar.
© 2026.
26 pages.
|
|
Vivek Bhardwaj, Tanima Thakur, Mrinalini Rana, Jeyaganesh Viswanathan.
© 2026.
24 pages.
|
|
Abhishek Sharma, Abhishek Mishra, Shweta Jain, Khushboo Karodiya, Priyanka Sharma.
© 2026.
10 pages.
|
|
Akash Mishra, Nandini Bansod, Dinesh Baban Kamble.
© 2026.
18 pages.
|
|
Anjali Rawat, George Kurian, Romil Rawat, Janet Olivia Richmond, Anand Rajavat, Purvee Bhardwaj.
© 2026.
28 pages.
|
|
Antonio Gonzalez-Torres.
© 2026.
26 pages.
|
|
Anjali Rawat, A. Samson Arun Raj, Janet Olivia Richmond, Anand Rajavat, Antonio González-Torres, Purvee Bhardwaj.
© 2026.
22 pages.
|
|
|