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One of the significant challenges that smart grid networks face is cyber-security. Several studies have been conducted to highlight those security challenges. However, the majority of these surveys classify attacks based on the security…
With the increasing use of information and communication technology in electrical power grids, the security of energy supply is increasingly threatened by cyber-attacks. Traditional cyber-security measures, such as firewalls or intrusion…
Autonomous vehicles rely on camera-based perception systems to comprehend their driving environment and make crucial decisions, thereby ensuring vehicles to steer safely. However, a significant threat known as Electromagnetic Signal…
The widening spectrum of applications and services provided by portable and embedded devices bring a new dimension of concerns in security. Most of those embedded systems (pay-TV, PDAs, mobile phones, etc...) make use of external memory. As…
Data poisoning and leakage risks impede the massive deployment of federated learning in the real world. This chapter reveals the truths and pitfalls of understanding two dominating threats: {\em training data privacy intrusion} and {\em…
Open human mobility data is considered an essential basis for the profound research and analysis required for the transition to sustainable mobility and sustainable urban planning. Cycling data has especially been the focus of data…
The advantages of using communication networks to interconnect controllers and physical plants motivate the increasing number of Networked Control Systems, in industrial and critical infrastructure facilities. However, this integration also…
Small-Signal Stability (SSS) is crucial for the control of power grids. However, False Data Injection (FDI) attacks against SSS can impact the grid stability, hence, the security of SSS needs to be studied. This paper proposes a formal…
We propose a simple method for secure digital signal transmission by making some modifications in the single-step parameter modulation technique proposed earlier into overcome certain inherent deficiencies. In the modified method, the…
Connected vehicles are vulnerable to manipulation and a broad attack surface can be used to intrude in-vehicle networks from anywhere on earth. In this work, we present an integrated security infrastructure comprising network protection,…
Bias in data can have unintended consequences that propagate to the design, development, and deployment of machine learning models. In the financial services sector, this can result in discrimination from certain financial instruments and…
This work considers load-balance control among the relays under the secure transmission protocol via relay cooperation in two-hop wireless networks without the information of both eavesdropper channels and locations. The available two-hop…
High-Altitude Platform Stations (HAPS) are emerging stratospheric nodes within non-terrestrial networks. We provide a structured overview of HAPS subsystems and principal communication links, map cybersecurity and privacy exposure across…
Position verification in wireless sensor networks (WSNs) is quite tricky in presence of attackers (malicious sensor nodes), who try to break the verification protocol by reporting their incorrect positions (locations) during the…
Information theoretic sparse attacks that minimize simultaneously the information obtained by the operator and the probability of detection are studied in a Bayesian state estimation setting. The attack construction is formulated as an…
Safety-critical sensors in autonomous vehicles (AVs) form an essential part of the vehicle's trusted computing base (TCB), yet they are highly susceptible to attacks. Alarmingly, Tier 1 manufacturers have already exposed vulnerabilities to…
Ensuring the reliability of machine learning-based intrusion detection systems remains a critical challenge in Internet of Things (IoT) environments, particularly as data poisoning attacks increasingly threaten the integrity of model…
Deep learning technologies are pivotal in enhancing the performance of WiFi-based wireless sensing systems. However, they are inherently vulnerable to adversarial perturbation attacks, and regrettably, there is lacking serious attention to…
With the escalating threats posed by cyberattacks on Industrial Control Systems (ICSs), the development of customized Industrial Intrusion Detection Systems (IIDSs) received significant attention in research. While existing literature…
This dissertation highlights the growing interest in and adoption of machine learning (ML) approaches for fault detection in modern power grids. Once a fault has occurred, it must be identified quickly and preventative steps must be taken…