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

Autor:	Sunandita Patra, Alex Velazquez, Myong Kang, Dana Nau
Rok vydání:	2021
Předmět:	General Medicine
Zdroj:	Proceedings of the AAAI Conference on Artificial Intelligence. 35:15377-15384
ISSN:	2374-3468 2159-5399
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::2ed95ff19c9e30e68a5239b452d928bd https://doi.org/10.1609/aaai.v35i17.17806 Zobrazit plný text záznamu