Improving the Security of Visual Challenges

Author:

Valente Junia1ORCID,Bahirat Kanchan1,Venechanos Kelly1,Cardenas Alvaro A.2,Balakrishnan Prabhakaran1

Affiliation:

1. The University of Texas at Dallas, Richardson, Texas

2. University of California, Santa Cruz, California

Abstract

This article proposes new tools to detect the tampering of video feeds from surveillance cameras. Our proposal illustrates the unique cyber-physical properties that sensor devices can leverage for their cyber-security. While traditional attestation algorithms exchange digital challenges between devices authenticating each other, our work instead proposes challenges that manifest physically in the field of view of the camera (e.g., a QR code in a display). This physical (challenge) and cyber (verification) attestation mechanism can help protect systems even when the sensors (cameras) and actuators (a display, infrared LEDs, color light bulbs) are compromised. In this article, we consider skillful adversaries that can capture the correct challenges (our system is sending) and can re-create them in the response to try fooling our verification system, and we propose new algorithms to detect these powerful attackers. Also, we introduce new visual challenges that make harder for anti-forensics attackers to succeed, and we present experimental results showing how our system is robust against a variety of attacks ranging from naive attacks to more sophisticated anti-forensics attackers.

Funder

Army Research Office

Laboratory of Analytic Sciences

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Control and Optimization,Computer Networks and Communications,Hardware and Architecture,Human-Computer Interaction

Reference25 articles.

1. Denso Wave Incorporated. 2015. QR code error correction feature. Retrieved from http://www.qrcode.com/en/about/error_correction.html. Denso Wave Incorporated. 2015. QR code error correction feature. Retrieved from http://www.qrcode.com/en/about/error_correction.html.

2. A video forensic technique for detecting frame deletion and insertion

3. Dan Goodin. 2012. A Fort Knox for Web crypto keys: Inside Symantec’s SSL certificate vault. Retrieved from https://arstechnica.com/security/2012/11/inside-symantecs-ssl-certificate-vault/. Dan Goodin. 2012. A Fort Knox for Web crypto keys: Inside Symantec’s SSL certificate vault. Retrieved from https://arstechnica.com/security/2012/11/inside-symantecs-ssl-certificate-vault/.

4. Dan Goodin. 2015. Prosecutors suspect man hacked lottery computers to score winning ticket. Retrieved from https://arstechnica.com/tech-policy/2015/04/prosecutors-suspect-man-hacked-lottery-computers-to-score-winning-ticket/. Dan Goodin. 2015. Prosecutors suspect man hacked lottery computers to score winning ticket. Retrieved from https://arstechnica.com/tech-policy/2015/04/prosecutors-suspect-man-hacked-lottery-computers-to-score-winning-ticket/.

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