Game-Theoretic Neyman-Pearson Detection to Combat Strategic Evasion

Fuente: arXiv
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Autori principali: Hu, Yinan, Chen, Juntao, Zhu, Quanyan
Natura: Preprint
Pubblicazione: 2022
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author Hu, Yinan
Chen, Juntao
Zhu, Quanyan
author_facet Hu, Yinan
Chen, Juntao
Zhu, Quanyan
contents The security in networked systems depends greatly on recognizing and identifying adversarial behaviors. Traditional detection methods focus on specific categories of attacks and have become inadequate for increasingly stealthy and deceptive attacks that are designed to bypass detection strategically. This work aims to develop a holistic theory to countermeasure such evasive attacks. We focus on extending a fundamental class of statistical-based detection methods based on Neyman-Pearson's (NP) hypothesis testing formulation. We propose game-theoretic frameworks to capture the conflicting relationship between a strategic evasive attacker and an evasion-aware NP detector. By analyzing both the equilibrium behaviors of the attacker and the NP detector, we characterize their performance using Equilibrium Receiver-Operational-Characteristic (EROC) curves. We show that the evasion-aware NP detectors outperform the passive ones in the way that the former can act strategically against the attacker's behavior and adaptively modify their decision rules based on the received messages. In addition, we extend our framework to a sequential setting where the user sends out identically distributed messages. We corroborate the analytical results with a case study of anomaly detection.
format Preprint
id arxiv_https___arxiv_org_abs_2206_05276
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Game-Theoretic Neyman-Pearson Detection to Combat Strategic Evasion
Hu, Yinan
Chen, Juntao
Zhu, Quanyan
Cryptography and Security
Computer Science and Game Theory
Information Theory
Systems and Control
The security in networked systems depends greatly on recognizing and identifying adversarial behaviors. Traditional detection methods focus on specific categories of attacks and have become inadequate for increasingly stealthy and deceptive attacks that are designed to bypass detection strategically. This work aims to develop a holistic theory to countermeasure such evasive attacks. We focus on extending a fundamental class of statistical-based detection methods based on Neyman-Pearson's (NP) hypothesis testing formulation. We propose game-theoretic frameworks to capture the conflicting relationship between a strategic evasive attacker and an evasion-aware NP detector. By analyzing both the equilibrium behaviors of the attacker and the NP detector, we characterize their performance using Equilibrium Receiver-Operational-Characteristic (EROC) curves. We show that the evasion-aware NP detectors outperform the passive ones in the way that the former can act strategically against the attacker's behavior and adaptively modify their decision rules based on the received messages. In addition, we extend our framework to a sequential setting where the user sends out identically distributed messages. We corroborate the analytical results with a case study of anomaly detection.
title Game-Theoretic Neyman-Pearson Detection to Combat Strategic Evasion
topic Cryptography and Security
Computer Science and Game Theory
Information Theory
Systems and Control
url https://arxiv.org/abs/2206.05276