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Attacks in cyberspace have got attention due to risk at privacy, breach of trust and financial losses for individuals as well as organizations. In recent years, these attacks have become more complex to analyze technically, as well as to…
Insider threats (InTs) within organizations are small in number but have a disproportionate ability to damage systems, information, and infrastructure. Existing InT research studies the problem from psychological, technical, and educational…
The problem of private information "leakage" (inadvertently or by malicious design) from the myriad large centralized searchable data repositories drives the need for an analytical framework that quantifies unequivocally how safe private…
The rapid progress in technology innovation usage and distribution has increased in the last decade. The rapid growth of the Internet of Things (IoT) systems worldwide has increased network security challenges created by malicious third…
Research on information diffusion generally assumes complete knowledge of the underlying network. However, in the presence of factors such as increasing privacy awareness, restrictions on application programming interfaces (APIs) and…
Our everyday interactions with pervasive systems generate traces that capture various aspects of human behavior and enable machine learning algorithms to extract latent information about users. In this paper, we propose a machine learning…
The advent of Web 3.0, underpinned by blockchain technologies, promises to transform the internet's landscape by empowering individuals with decentralized control over their data. However, this evolution brings unique security challenges…
The development of artificial intelligence has significantly transformed people's lives. However, it has also posed a significant threat to privacy and security, with numerous instances of personal information being exposed online and…
Today, telecommunication service providers (telcos) are exposed to cyber-attacks executed by compromised IoT devices connected to their customers' networks. Such attacks might have severe effects not only on the target of attacks but also…
Internet of Things (IoT) is being considered as the growth engine for industrial revolution 4.0. The combination of IoT, cloud computing and healthcare can contribute in ensuring well-being of people. One important challenge of IoT network…
Organizations invest heavily in technical controls for their Information Assurance (IA) infrastructure. These technical controls mitigate and reduce the risk of damage caused by outsider attacks. Most organizations rely on training to…
This paper investigates capabilities of Privacy-Preserving Deep Learning (PPDL) mechanisms against various forms of privacy attacks. First, we propose to quantitatively measure the trade-off between model accuracy and privacy losses…
Anonymity networks are becoming increasingly popular in today's online world as more users attempt to safeguard their online privacy. Tor is currently the most popular anonymity network in use and provides anonymity to both users and…
Advances in fifth-generation (5G) networks enable unprecedented reliability, speed, and connectivity compared to previous mobile networks. These advancements can revolutionize various sectors by supporting applications requiring real-time…
The rapid proliferation of Internet of Things (IoT) technologies, projected to exceed 30 billion interconnected devices by 2030, has significantly escalated the complexity of cybersecurity challenges. This survey aims to provide a…
Privacy has always been a critical issue in the digital era, particularly with the increasing use of Internet of Things (IoT) devices. As the IoT continues to transform industries such as healthcare, smart cities, and home automation, it…
IoT devices are increasingly utilized in critical infrastructure, enterprises, and households. There are several sophisticated cyber-attacks that have been reported and many networks have proven vulnerable to both active and passive attacks…
A wide variety of privacy metrics have been proposed in the literature to evaluate the level of protection offered by privacy enhancing-technologies. Most of these metrics are specific to concrete systems and adversarial models, and are…
The scientific method presents a key challenge to privacy because it requires many samples to support a claim. When samples are commercially valuable or privacy-sensitive enough, their owners have strong reasons to avoid releasing them for…
This article attempts to create a software and hardware complex that can work autonomously and demonstrates the ease of implementation of attacks on denial of service on wireless networks, which in turn emphasizes the need to provide…