Moving target defense: A symbiotic framework for Al & security

Sailik Sengupta, Subbarao Kambhampati

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Modern day technology has found its way into every aspect of our lives-be it the server storing our social information, the hand-held smartphones, the home security systems or a remotely monitored pacemaker. Unfortunately, this also increases the opportunity for agents with malicious intent to violate the privacy, availability or integrity of these applications. In fact, with the advancement of Artificial Intelligence (AI) and faster hardware, the process of finding and exploiting vulnerabilities is no longer as time-consuming as before. Moving Target Defense (MTD) is emerging as an effective technique in addressing these security concerns. This technique, as used by the cyber security community, however, does not incorporate the dynamics of a multi-agent system between an attacker and defender, resulting in sub-optimal behavior. My study of such systems in a multi-agent context helps to enhance the security of MTD systems and proposes a list of challenges for the AI community. Furthermore, borrowing the example of MTD systems from the cyber security community, we can address some security concerns of the present day AI algorithms. In this abstract, I describe my research work that uses AI for enhancing security of a multi-agent MTD system and highlight research avenues in using MTD for enhancing security of present AI algorithms.

Original languageEnglish (US)
Title of host publication16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1861-1862
Number of pages2
Volume3
ISBN (Electronic)9781510855076
StatePublished - Jan 1 2017
Event16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017 - Sao Paulo, Brazil
Duration: May 8 2017May 12 2017

Other

Other16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017
CountryBrazil
CitySao Paulo
Period5/8/175/12/17

Fingerprint

Artificial intelligence
Pacemakers
Smartphones
Multi agent systems
Security systems
Servers
Availability
Hardware

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

Cite this

Sengupta, S., & Kambhampati, S. (2017). Moving target defense: A symbiotic framework for Al & security. In 16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017 (Vol. 3, pp. 1861-1862). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).

Moving target defense : A symbiotic framework for Al & security. / Sengupta, Sailik; Kambhampati, Subbarao.

16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017. Vol. 3 International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2017. p. 1861-1862.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Sengupta, S & Kambhampati, S 2017, Moving target defense: A symbiotic framework for Al & security. in 16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017. vol. 3, International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), pp. 1861-1862, 16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017, Sao Paulo, Brazil, 5/8/17.
Sengupta S, Kambhampati S. Moving target defense: A symbiotic framework for Al & security. In 16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017. Vol. 3. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). 2017. p. 1861-1862
Sengupta, Sailik ; Kambhampati, Subbarao. / Moving target defense : A symbiotic framework for Al & security. 16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017. Vol. 3 International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2017. pp. 1861-1862
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