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In this chapter, we will present a data-driven defense mechanism in cyber-physical systems against kinetic cyber-attacks. Kinetic cyber-attacks cause physical damage to the system from the cyber-domain. In cyber-physical manufacturing, kinetic cyber-attacks are realized by introducing flaws in the design of the 3D objects. These flaws may eventually compromise the structural integrity of the printed objects. In CPS, researchers have designed various attack detection method to detect the attacks on the integrity of the system. However, in cyber-physical additive manufacturing, attack detection method is still in its infancy. Moreover, analog emissions (such as acoustics, electromagnetic emissions, etc.) from the side-channels have not been fully considered as a parameter for attack detection. This chapter presents a novel attack detection method that is able to detect zero-day kinetic cyber-attacks by identifying anomalous analog emissions which arise as an outcome of the attack. This is achieved by statistically estimating functions that map the relation between the analog emissions and the corresponding cyber-domain data (such as G-code) to model the behavior of the system. We will then present the analysis of the proposed method to detect potential zero-day kinetic cyber-attacks in fused deposition modeling based cyber-physical additive manufacturing systems.
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- Data-Driven Kinetic Cyber-Attack Detection
Sujit Rokka Chhetri
Mohammad Abdullah Al Faruque
- Chapter 5