Using Online Planning and Acting to Recover from Cyberattacks on Software-defined Networks

Authors

  • Sunandita Patra Department of Computer Science and Institute for Systems Research, University of Maryland, College Park, USA
  • Alex Velazquez Naval Research Laboratory, Information Technology Division, Washington, DC, USA
  • Myong Kang Naval Research Laboratory, Information Technology Division, Washington, DC, USA
  • Dana Nau Department of Computer Science and Institute for Systems Research, University of Maryland, College Park, USA

Keywords:

Acting And Planning, Software-defined Networks, Online Recovery From Cyberattacks

Abstract

We describe ACR-SDN, a system to monitor, diagnose, and quickly respond to attacks or failures that may occur in software-defined networks (SDNs). An integral part of ACR-SDN is its use of RAE+UPOM, an automated acting and planning engine that uses hierarchical refinement. To advise ACR-SDN on how to recover a target system from faults and attacks, RAE+UPOM uses attack recovery procedures written as hierarchical operational models. Our experimental results show that the use of refinement planning in ACR-SDN is successful in recovering SDNs from attacks with respect to five performance metrics: estimated time for recovery, efficiency, retry ratio, success ratio, and costEffectiveness.

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Published

2021-05-18

How to Cite

Patra, S., Velazquez, A., Kang, M., & Nau, D. (2021). Using Online Planning and Acting to Recover from Cyberattacks on Software-defined Networks. Proceedings of the AAAI Conference on Artificial Intelligence, 35(17), 15377-15384. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/17806

Issue

Section

IAAI Technical Track on Emerging Applications of AI