TY - GEN
T1 - Moving target defense for the placement of intrusion detection systems in the cloud
AU - Sengupta, Sailik
AU - Chowdhary, Ankur
AU - Huang, Dijiang
AU - Kambhampati, Subbarao
N1 - Funding Information:
Acknowledgements. This research is supported in part by the AFOSR grant FA9550-18-1-0067, ONR grants N00014-16-1-2892, N00014-18-1-2442, N00014-18-12840, the NASA grant NNX17AD06G, the NRL N00173-15-G017, NSF Grants 1642031, 1528099, and 1723440, and NSFC Grants 61628201 and 61571375. The first author is also supported in part by the IBM Ph.D. Fellowship 2018-19.
Publisher Copyright:
© 2018, Springer Nature Switzerland AG.
PY - 2018
Y1 - 2018
N2 - A lot of software systems are deployed in the cloud. Owing to realistic demands for an early product launch, oftentimes there are vulnerabilities that are present in these deployed systems (or eventually found out). The cloud service provider can find and leverage this knowledge about known vulnerabilities and the underlying communication network topology of the system to position network and host-based Intrusion Detection Systems (IDS) that can effectively detect attacks. Unfortunately, deploying IDS on each host and network interface impacts the performance of the overall system. Thus, in this paper, we address the problem of placing a limited number of IDS by using the concept of Moving Target Defense (MTD). In essence, we propose an MTD system that allows a defender to shift the detection surfaces and strategically switch among the different IDS placement configurations in each round. To find a secure switching strategy, we (1) formulate the problem of placing a limited number of IDS systems in a large cloud network as a Stackelberg Game between the cloud administrator and an (external or stealthy) attacker, (2) design scalable methods to find the optimal strategies for switching IDS placements at the start of each round, and (3) formally define the problem of identifying the most critical vulnerability that should be fixed, and propose a solution for it. We compare the strategy generated by our method to other state-of-the-art strategies, showcasing the effectiveness and scalability of our method for real-world scenarios.
AB - A lot of software systems are deployed in the cloud. Owing to realistic demands for an early product launch, oftentimes there are vulnerabilities that are present in these deployed systems (or eventually found out). The cloud service provider can find and leverage this knowledge about known vulnerabilities and the underlying communication network topology of the system to position network and host-based Intrusion Detection Systems (IDS) that can effectively detect attacks. Unfortunately, deploying IDS on each host and network interface impacts the performance of the overall system. Thus, in this paper, we address the problem of placing a limited number of IDS by using the concept of Moving Target Defense (MTD). In essence, we propose an MTD system that allows a defender to shift the detection surfaces and strategically switch among the different IDS placement configurations in each round. To find a secure switching strategy, we (1) formulate the problem of placing a limited number of IDS systems in a large cloud network as a Stackelberg Game between the cloud administrator and an (external or stealthy) attacker, (2) design scalable methods to find the optimal strategies for switching IDS placements at the start of each round, and (3) formally define the problem of identifying the most critical vulnerability that should be fixed, and propose a solution for it. We compare the strategy generated by our method to other state-of-the-art strategies, showcasing the effectiveness and scalability of our method for real-world scenarios.
KW - Intrusion Detection Systems
KW - Moving Target Defense
KW - Stackelberg games
UR - http://www.scopus.com/inward/record.url?scp=85055871552&partnerID=8YFLogxK
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U2 - 10.1007/978-3-030-01554-1_19
DO - 10.1007/978-3-030-01554-1_19
M3 - Conference contribution
AN - SCOPUS:85055871552
SN - 9783030015534
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 326
EP - 345
BT - Decision and Game Theory for Security - 9th International Conference, GameSec 2018, Proceedings
A2 - Bushnell, Linda
A2 - Poovendran, Radha
A2 - Basar, Tamer
PB - Springer Verlag
T2 - 9th International Conference on Decision and Game Theory for Security, GameSec 2018
Y2 - 29 October 2018 through 31 October 2018
ER -