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

Sunandita Patra, Alexander Velazquez, Myong H. Kang, Dana S. Nau

AAAI 2021 pp. 15377-15384

doi:10.1609/AAAI.V35I17.17806 /aaai/2021/patra2021aaai-using/

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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Cite

Text

Patra et al. "Using Online Planning and Acting to Recover from Cyberattacks on Software-Defined Networks." AAAI Conference on Artificial Intelligence, 2021. doi:10.1609/AAAI.V35I17.17806

Markdown

[Patra et al. "Using Online Planning and Acting to Recover from Cyberattacks on Software-Defined Networks." AAAI Conference on Artificial Intelligence, 2021.](https://mlanthology.org/aaai/2021/patra2021aaai-using/) doi:10.1609/AAAI.V35I17.17806

BibTeX

@inproceedings{patra2021aaai-using,
  title     = {{Using Online Planning and Acting to Recover from Cyberattacks on Software-Defined Networks}},
  author    = {Patra, Sunandita and Velazquez, Alexander and Kang, Myong H. and Nau, Dana S.},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2021},
  pages     = {15377-15384},
  doi       = {10.1609/AAAI.V35I17.17806},
  url       = {https://mlanthology.org/aaai/2021/patra2021aaai-using/}
}