Private matching and set intersection computation in multi-agent and industrial control systems

Rasheed, A; Kenneth, A; Mahapatra, R; Puthal, D

Private matching and set intersection computation in multi-agent and industrial control systems

Rasheed, A Kenneth, A Mahapatra, R Puthal, D

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Publication Type:: Conference Proceeding
Citation:: ACM International Conference Proceeding Series, 2017
Issue Date:: 2017-04-04

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Field	Value	Language
dc.contributor.author	Rasheed, A	en_US
dc.contributor.author	Kenneth, A	en_US
dc.contributor.author	Mahapatra, R	en_US
dc.contributor.author	Puthal, D https://orcid.org/0000-0002-8332-278X	en_US
dc.date.issued	2017-04-04	en_US
dc.identifier.citation	ACM International Conference Proceeding Series, 2017	en_US
dc.identifier.isbn	9781450348553	en_US
dc.identifier.uri	http://hdl.handle.net/10453/127555
dc.description.abstract	© 2017 ACM. 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 semi-honest model.	en_US
dc.relation.ispartof	ACM International Conference Proceeding Series	en_US
dc.relation.isbasedon	10.1145/3064814.3064817	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Private matching and set intersection computation in multi-agent and industrial control systems	en_US
dc.type	Conference Proceeding
utslib.for	0803 Computer Software	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US

Abstract:

© 2017 ACM. 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 semi-honest model.

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http://hdl.handle.net/10453/127555