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Home > Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 > No. 17: IAAI-21, EAAI-21, AAAI-21 Special Programs and Special Track

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


Proceedings:

No. 17: IAAI-21, EAAI-21, AAAI-21 Special Programs and Special Track

Volume

Issue:

Proceedings of the AAAI Conference on Artificial Intelligence, 35

Track:

IAAI Technical Track on Emerging Applications of AI

Downloads:

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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.

DOI:

10.1609/aaai.v35i17.17806


AAAI

Proceedings of the AAAI Conference on Artificial Intelligence, 35