Optimizing Preventive and Reactive Defense Resource Allocation with Uncertain Sensor Signals

Shojaeighadikolaei, Faezeh; Xu, Shouhuai; Paarporn, Keith

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https://hdl.handle.net/2142/130287 Copy

Description

Title

Optimizing Preventive and Reactive Defense Resource Allocation with Uncertain Sensor Signals

Author(s)

• Shojaeighadikolaei, Faezeh
• Xu, Shouhuai
• Paarporn, Keith

Issue Date

2025-09-17

Keyword(s)

• Resource allocation
• Optimization
• Preventive and reactive defense

Abstract

Cyber attacks continue to be a cause of concern despite advances in cyber defense techniques. Although cyber attacks cannot be fully prevented, standard decision-making frameworks typically focus on how to prevent them from succeeding, without considering the cost of cleaning up the damages incurred by successful attacks. This motivates us to investigate a new resource allocation problem formulated in this paper: The defender must decide how to split its investment between preventive defenses, which aim to harden nodes from attacks, and reactive defenses, which aim to quickly clean up the compromised nodes. This encounters a challenge imposed by the uncertainty associated with the observation, or sensor signal, whether a node is truly compromised or not; this uncertainty is real because attack detectors are not perfect. We investigate how the quality of sensor signals impacts the defender’s strategic investment in the two types of defense, and ultimately the level of security that can be achieved. In particular, we show that the optimal investment in preventive resources increases, and thus reactive resource investment decreases, with higher sensor quality. We also show that the defender’s performance improvement, relative to a baseline of no sensors employed, is maximal when the attacker can only achieve low attack success probabilities.

Publisher

Allerton Conference on Communication, Control, and Computing

Series/Report Name or Number

2025 61st Allerton Conference on Communication, Control, and Computing Proceedings

ISSN

2836-4503

Type of Resource

Text

Genre of Resource

Conference Paper/Presentation

Language

eng

Handle URL

https://hdl.handle.net/2142/130287&&

Copyright and License Information

Copyright 2025 owned by the authors.

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