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Phishing attacks are the most common type of cyber-attacks used to obtain sensitive information and have been affecting individuals as well as organisations across the globe. Various techniques have been proposed to identify the phishing…
Deep Neural Networks (DNNs), from AlexNet to ResNet to ChatGPT, have made revolutionary progress in recent years, and are widely used in various fields. The high performance of DNNs requires a huge amount of high-quality data, expensive…
Distributed systems require robust, scalable identifier schemes to ensure data uniqueness and efficient indexing across multiple nodes. This paper presents a comprehensive analysis of the evolution of distributed identifiers, comparing…
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…
The obstacles of each security system combined with the increase of cyber-attacks, negatively affect the effectiveness of network security management and rise the activities to be taken by the security staff and network administrators. So,…
In critical infrastructures, communication networks are used to exchange vital data among elements of Industrial Control Systems (ICSes). Due to the criticality of such systems and the increase of the cybersecurity risks in these contexts,…
InterPlanetary File System~(IPFS) is one of the most promising decentralized off-chain storage mechanisms, particularly relevant for blockchains, aiming to store the content forever, thus it is crucial to understand its composition, deduce…
Iris recognition technology has attracted an increasing interest in the last decades in which we have witnessed a migration from research laboratories to real world applications. The deployment of this technology raises questions about the…
Threat modeling and risk assessments are common ways to identify, estimate, and prioritize risk to national, organizational, and individual operations and assets. Several threat modeling and risk assessment approaches have been proposed…
The rapid expansion of the Internet of Things (IoT) has revolutionized various domains, offering significant benefits through enhanced interconnectivity and data exchange. However, the security challenges associated with IoT networks have…
A considerable portion of the machine learning literature applied to intrusion detection uses outdated data sets based on a simulated network with a limited environment. Moreover, flaws usually appear in datasets and the way we handle them…
Semiconductor intellectual property (IP) theft incurs hundreds of billions in annual losses, driven by advanced reverse engineering (RE) techniques. Traditional ``cryptic'' IC camouflaging methods typically focus on hiding localized gate…
How can we justify the validity of our computer security methods? This meta-methodological question is related to recent explorations on the science of computer security, which have been hindered by computer security's unique properties. We…
Attacks on Internet routing are typically viewed through the lens of availability and confidentiality, assuming an adversary that either discards traffic or performs eavesdropping. Yet, a strategic adversary can use routing attacks to…
Nowadays, every organization might be attacked through its network printers. The malicious exploitation of printing protocols is a dangerous and underestimated threat against every printer today, as highlighted by recent published…
In this paper, we present a comprehensive survey of authentication protocols for Internet of Things (IoT). Specifically, we select and in-detail examine more than forty authentication protocols developed for or applied in the context of the…
With the ongoing exhaustion of free address pools at the registries serving the global demand for IPv4 address space, scarcity has become reality. Networks in need of address space can no longer get more address allocations from their…
Deep Neural Networks (DNN) are susceptible to backdoor attacks where malicious attackers manipulate the model's predictions via data poisoning. It is hence imperative to develop a strategy for training a clean model using a potentially…
In recent years, neural networks have become the default choice for image classification and many other learning tasks, even though they are vulnerable to so-called adversarial attacks. To increase their robustness against these attacks,…
The scalable, low overhead attributes of Peer-to-Peer (P2P) Internet protocols and networks lend themselves well to being exploited by criminals to execute a large range of cybercrimes. The types of crimes aided by P2P technology include…