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Data-Driven Defense Through Leakage Minimization

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Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis

Abstract

In Part I of this book, we presented data-driven attack models capable of breaching the confidentiality of the system. In this form of attacks, attackers utilize the side-channels (such as acoustics, power, electromagnetic emissions, and so on) in the physical domain to estimate and steal cyber-domain data (such as G/M-codes). Since these emissions depend on the physical structure of the system, one way to minimize the information leakage is to modify the physical domain. However, this process can be costly due to added hardware modification. Instead, in this chapter we present a novel methodology that allows the cyber-domain tools [such as computer-aided manufacturing (CAM)] to be aware of the existing information leakage. We will demonstrate how by changing either machine process or product design parameters in the cyber-domain, we can minimize the information leakage. The methodology presented in this chapter aids the existing cyber-domain and physical domain security solution by utilizing the cross-domain relationship.

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Rokka Chhetri, S., Al Faruque, M.A. (2020). Data-Driven Defense Through Leakage Minimization. In: Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis. Springer, Cham. https://doi.org/10.1007/978-3-030-37962-9_4

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  • DOI: https://doi.org/10.1007/978-3-030-37962-9_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37961-2

  • Online ISBN: 978-3-030-37962-9

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