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Barak Amihood

dblp:313/3134 · DBLP profile ↗
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2ranked-venue papers
2as first author
2since 2021 · last 2024
0000-0002-8386-1548ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 1 · 1 first-author · 1 since 2021Theory of computation · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Mathematical optimization · 50% Algorithms and data structures · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Mathematical optimization
control theory
0.212024
Covertly Controlling a Linear System · IEEE Trans. Inf. Forensics Secur. 2024
Algorithms and data structures › numerical linear algebra
linear system solving
0.212024
Covertly Controlling a Linear System · IEEE Trans. Inf. Forensics Secur. 2024

Methods — techniques the papers use, named apart from their topics

information-theoretic covertness analysis · 0.8AR(1) system modeling · 0.8
YearPublicationVenuePosition
2024 Covertly Controlling a Linear System
abstract
Consider the problem of covertly controlling a linear system. In this problem, Alice desires to control (stabilize or change the behavior of) a linear system, while keeping an observer, Willie, unable to decide if the system is indeed being controlled or not. We formally define the problem, under a model where Willie can only observe the system’s output. Focusing on AR(1) systems, we show that when Willie observes the system’s output through a clean channel, an inherently unstable linear system cannot be covertly stabilized. However, under some conditions on the parameters and observation time, an inherently stable linear system can be covertly controlled, in the sense of covertly changing its parameter or resetting its memory. Moreover, we give positive and negative results for two important controllers: a minimal-information controller, where Alice is allowed to use only 1 bit per sample, and a maximal-information controller, where Alice is allowed to view the real-valued output. The results reveal an interesting interplay in covert control, between the amount of information used by the c ontroller, control performance and covertness.
Barak Amihood, Asaf Cohen 0001
IEEE Trans. Inf. Forensics Secur.1
2022 Covertly Controlling a Linear System
abstract
Consider the problem of covertly controlling a linear system. In this problem, Alice desires to control (stabilize or change the parameters of) a linear system, while keeping an observer, Willie, unable to decide if the system is indeed being controlled or not.We formally define the problem, under the model when Willie can only observe the system’s output. Focusing on AR(1) systems, we show that when Willie observes the system’s output through a clean channel, an inherently unstable linear system can not be covertly stabilized. However, an inherently stable linear system can be covertly controlled, in the sense of covertly changing its parameter. Moreover, we give positive and negative results for two important controllers: a minimal-information controller, where Alice is allowed to use only 1 bit per sample, and a maximal-information controller, where Alice is allowed to view the real-valued output. Unlike covert communication, where the trade-off is between rate and covertness; and in cyber-physical systems the trade-off is between control and attack detection, the results reveal an interesting three–fold trade–off in covert control: the amount of information used by the controller, control performance and covertness. To the best of our knowledge, this is the first study formally defining covert control.
Barak Amihood, Asaf Cohen 0001
ITW1