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Federated learning (FL) is a decentralized machine learning (ML) approach that can be used for intrusion detection in Internet of Things (IoT) devices. It involves the local training of AI models and their aggregation at...

Abstract Cloud computing is quite popular because of its scalability and flexibility merits. However, faces significant security risks from malware, which exploits infrastructure weaknesses to cause unauthorized access, ...

Chilling effects are inhibitions of legitimate behaviors and are an important ethical side effect of surveillance. With the centrality of media users’ data for digital communication it is important to gain insights int...

The integration of artificial intelligence (AI) into human-robot interaction (HRI) in healthcare has fundamentally revolutionized the emotional, social, and cognitive interaction between humans and robotic systems. This ...

The Security systems using cameras as monitors or what is commonly known as Closed Circuit Television (CCTV) have recently become more prevalent. However, to have a monitoring system or monitoring requires a fairly expen...

Abstract Unmanned Aerial Systems (UAS) have become increasingly integral to industries such as agriculture, surveillance, transportation, and entertainment, raising significant concerns about their vulnerability to cyber...

Abstract Smart home networks are a rapidly evolving part of the Internet of Things (IoT), where connected devices exchange information to automate energy use, enhance comfort, and improve user safety. Despite their benef...

Abstract The rapid adoption of encrypted communication protocols has raised privacy levels but has also dealt a significant blow to traditional intrusion detection systems that rely on payload inspection for anomaly dete...

With the rise of generative AI, a new generation of intelligent phishing has emerged, where attackers leverage Large Language Models (LLMs) to craft websites with high semantic plausibility, posing critical challenges to...