Private matching and set intersection computation in multi-agent and industrial control systems
Document Type
Presentation
Presentation Date
2017
Abstract or Description
Presentation given at the 12th ACM Cyber and Information Security Research Conference.
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.
Sponsorship/Conference/Institution
12th ACM Cyber and Information Security Research Conference
Location
Oak Ridge, TN
Source
https://dl.acm.org/doi/10.1145/3064814.3064817
Recommended Citation
Rasheed, Amar, A. Kenneth, Rabi N. Mahapatra, Deepak Puthal.
2017.
"Private matching and set intersection computation in multi-agent and industrial control systems."
Department of Computer Science Faculty Presentations.
Presentation 112.
source: https://dl.acm.org/doi/10.1145/3064814.3064817
https://digitalcommons.georgiasouthern.edu/compsci-facpres/112
