Texture based attacks on intrinsic signature based printer identification

Aravind K. Mikkilineni; Nitin Khanna; Edward J. Delp

doi:10.1117/12.845377

27 January 2010 Texture based attacks on intrinsic signature based printer identification

Aravind K. Mikkilineni, Nitin Khanna, Edward J. Delp

Proceedings Volume 7541, Media Forensics and Security II; 75410T (2010) https://doi.org/10.1117/12.845377
Event: IS&T/SPIE Electronic Imaging, 2010, San Jose, California, United States

Abstract

Several methods exist for printer identification from a printed document. We have developed a system that performs printer identification using intrinsic signatures of the printers. Because an intrinsic signature is tied directly to the electromechanical properties of the printer, it is difficult to forge or remove. There are many instances where existance of the intrinsic signature in the printed document is undesireable. In this work we explore texture based attacks on intrinsic printer identification from text documents. An updated intrinsic printer identification system is presented that merges both texture and banding features. It is shown that this system is scable and robust against several types of attacks that one may use in an attempt to obscure the intrinsic signature.

Citation Download Citation

Aravind K. Mikkilineni, Nitin Khanna, and Edward J. Delp "Texture based attacks on intrinsic signature based printer identification", Proc. SPIE 7541, Media Forensics and Security II, 75410T (27 January 2010); https://doi.org/10.1117/12.845377

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available