FlipLeakage: A Game-Theoretic Approach to Protect Against Stealthy Attackers in the Presence of Information Leakage

Farhang, Sadegh; Großklags, Jens

doi:10.1007/978-3-319-47413-7_12

Cited by 25 publications

(19 citation statements)

References 21 publications

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“…Xu et al [31] present zero-sum security games where the attacker acquires partial knowledge on the security resources the defender is protecting, and show the defender's optimal strategy under such attacker's knowledge. More recently, Farhang et al [12] present two-player games where utilities are defined taking account of information leakage, although the defender's goal is different from our setting. They consider a model where the attacker incrementally and stealthily obtains partial information on a secret, while the defender periodically changes the secret after some time to prevent a complete compromise of the system.…”

Section: Related Workmentioning

confidence: 99%

Information Leakage Games

Alvim

Chatzikokolakis

Kawamoto

et al. 2017

Lecture Notes in Computer Science

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We consider a game-theoretic setting to model the interplay between attacker and defender in the context of information flow, and to reason about their optimal strategies. In contrast with standard game theory, in our games the utility of a mixed strategy is a convex function of the distribution on the defender's pure actions, rather than the expected value of their utilities. Nevertheless, the important properties of game theory, notably the existence of a Nash equilibrium, still hold for our (zero-sum) leakage games, and we provide algorithms to compute the corresponding optimal strategies. As typical in (simultaneous) game theory, the optimal strategy is usually mixed, i.e., probabilistic, for both the attacker and the defender. From the point of view of information flow, this was to be expected in the case of the defender, since it is well known that randomization at the level of the system design may help to reduce information leaks. Regarding the attacker, however, this seems the first work (w.r.t. the literature in information flow) proving formally that in certain cases the optimal attack strategy is necessarily probabilistic.

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Section: Related Workmentioning

confidence: 99%

Information Leakage Games

Alvim

Chatzikokolakis

Kawamoto

et al. 2017

Lecture Notes in Computer Science

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“…Hence, the leakage loss term dominates the defender's payoff function u d at this small migration cost. Indeed, referring to (12), u d is monotonically decreasing in τ d when C d → 0. On the other hand, when the migration cost is high as shown in Fig.…”

Section: B Cost Effect and Monotonicitymentioning

confidence: 99%

A Game-Theoretic Framework for the Virtual Machines Migration Timing Problem

Anwar

Atia

Guirguis

2021

IEEE Trans. Cloud Comput.

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In a multi-tenant cloud, a number of Virtual Machines (VMs) are collocated on the same physical machine to optimize performance, power consumption and maximize profit. This, however, increases the risk of a malicious VM performing side-channel attacks and leaking sensitive information from neighboring VMs. To this end, this paper develops and analyzes a game-theoretic framework for the VM migration timing problem in which the cloud provider decides when to migrate a VM to a different physical machine to reduce the risk of being compromised by a collocated malicious VM. The adversary decides the rate at which she launches new VMs to collocate with the victim VMs. Our formulation captures a data leakage model in which the cost incurred by the cloud provider depends on the duration of collocation with malicious VMs. It also captures costs incurred by the adversary in launching new VMs and by the defender in migrating VMs. We establish sufficient conditions for the existence of Nash equilibria for general cost functions, as well as for specific instantiations, and characterize the best response for both players. Furthermore, we extend our model to characterize its impact on the attacker's payoff when the cloud utilizes intrusion detection systems that detect side-channel attacks.Our theoretical findings are corroborated with extensive numerical results in various settings.

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“…Similarly, we model the defender's utility as the negation of the amount of time the attacker remains in the system multiplied by δ i ∈ [1,10], a coefficient describing how disruptive the attacker type i is. Coefficients δ i model the fact that different attackers may also be more or less disruptive to the defender.…”

Section: Utilitiesmentioning

confidence: 99%

Modeling observability in adaptive systems to defend against advanced persistent threats

Kinneer

Wagner

Fang

et al. 2019

Proceedings of the 17th ACM-IEEE International Conference on Formal Methods and Models for System Design

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Advanced persistent threats (APTs) are a particularly troubling challenge for software systems. The adversarial nature of the security domain, and APTs in particular, poses unresolved challenges to the design of self-* systems, such as how to defend against multiple types of attackers with different goals and capabilities. In this interaction, the observability of each side is an important and under-investigated issue in the self-* domain. We propose a model of APT defense that elevates observability as a first-class concern. We evaluate this model by showing how an informed approach that uses observability improves the defender's utility compared to a uniform random strategy, can enable robust planning through sensitivity analysis, and can inform observability-related architectural design decisions. CCS CONCEPTS • Security and privacy → Formal security models; Systems security; • Computing methodologies → Artificial intelligence; Model development and analysis.

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FlipLeakage: A Game-Theoretic Approach to Protect Against Stealthy Attackers in the Presence of Information Leakage

Cited by 25 publications

References 21 publications

Information Leakage Games

Information Leakage Games

A Game-Theoretic Framework for the Virtual Machines Migration Timing Problem

Modeling observability in adaptive systems to defend against advanced persistent threats

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