Titlebook: Intelligent Secure Trustable Things; Michael Karner,Johannes Peltola,Peter Priller Book‘‘‘‘‘‘‘‘ 2024 The Editor(s) (if applicable) and The

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The InSecTT Reference Architecturemain views or perspectives of the architecture, on how AI interacts with each one of these perspectives and in the end we provide two examples of use case alignment and the analysis of the impact of AI on the individual architectures.

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Going to the Edge: Bringing Artificial Intelligence and Internet of Things Togetherrtificial Intelligence together. InSecTT aims at creating trust in AI-based intelligent systems and solutions as a major part of the AIoT. This article provides an overview of the concept and ideas behind InSecTT, serving as a baseline for all subsequent chapters and articles.

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InSecTT Technologies for the Enhancement of Industrial Security and Safetyor intrusion detection, (c) generation of realistic process control and network oriented datasets with injected anomalies and (d) performing safety and security analysis on automated guided vehicle platoons.

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Algorithmic and Implementation-Based Threats for the Security of Embedded Machine Learning Modelslighting new critical attack vectors that rely on side-channel and fault injection analysis and significantly extend the attack surface of AIoT systems (Artificial Intelligence of Things). More particularly, we focus on two advanced threats against models deployed in 32-bit microcontrollers: model extraction and weight-based adversarial attacks.

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AI-Enhanced Connection Management for Cellular Networksthe connection. To counteract this and to increase resilience, onboard systems may be equipped with a number of uplink options that can be used. This chapter discusses the use of AI to assess and manage the available connections and to move data traffic between the available links according to their expected data rates.

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