Private Matching and Set Intersection Computation in Multi‐Agent and Industrial Control Systems
Document Type
Conference Proceeding
Publication Date
4-4-2017
Publication Title
Proceedings of the Cyber and Information Security Research Conference
DOI
10.1145/3064814.3064817
ISBN
978-1-4503-4855-3
Abstract
Distributed autonomous systems that rely on dataset matching and set intersection computation for decision making capabilities are vulnerable to datasets poisoning attacks. Among these systems, Industrial Control Systems (ICS) operating on critical infrastructures. Attacker with a compromised Programmable Logic Controllers (PLCs) can take advantage of the PLC-to-PLC information sharing process to construct and inject anomalous data that target the result of dataset matching and set intersection computation and hence bring the process operations into unstable state. We introduce a protocol that utilizes secure hamming distance computation from oblivious transfer to compute a joint set between two system's agents that hold private input datasets of length n. The proposed protocol achieves full security in the semihonest model.
Recommended Citation
Rasheed, Amar, A. Kenneth, Rabi Mahapatra, Deepak Puthal.
2017.
"Private Matching and Set Intersection Computation in Multi‐Agent and Industrial Control Systems."
Proceedings of the Cyber and Information Security Research Conference New York, NY: Association for Computing Machinery.
doi: 10.1145/3064814.3064817 isbn: 978-1-4503-4855-3
https://digitalcommons.georgiasouthern.edu/compsci-facpubs/199
