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The security of neural cryptography is investigated. A key-exchange protocol over a public channel is studied where the parties exchanging secret messages use multilayer neural networks which are trained by their mutual output bits and…

Threats from the internet, particularly malicious software (i.e., malware) often use cryptographic algorithms to disguise their actions and even to take control of a victim's system (as in the case of ransomware). Malware and other threats…

Malware detection is a critical aspect of information security. One difficulty that arises is that malware often evolves over time. To maintain effective malware detection, it is necessary to determine when malware evolution has occurred so…

Modern cryptography, such as Rivest Shamir Adleman (RSA) and Secure Hash Algorithm (SHA), has been designed by humans based on our understanding of cryptographic methods. Neural Network (NN) based cryptography is being investigated due to…

In spam and malware detection, attackers exploit randomization to obfuscate malicious data and increase their chances of evading detection at test time; e.g., malware code is typically obfuscated using random strings or byte sequences to…

Ransomware is still one of the most serious cybersecurity threats. Victims often pay but fail to regain access to their data, while also facing the danger of losing data privacy. These uncertainties heavily shape the attacker-victim…

With the increasing number of cybersecurity threats, it becomes more difficult for researchers to skim through the security reports for malware analysis. There is a need to be able to extract highly relevant sentences without having to read…

Ransomware continues to evolve as one of the most disruptive cyber threats, with recent variants increasingly leveraging automated and AI-assisted techniques to evade traditional signature-based defenses. Early detection of such attacks…

Detecting encryption-driven cyber threats remains a large challenge due to the evolving techniques employed to evade traditional detection mechanisms. An entropy-based computational framework was introduced to analyze multi-domain system…

We present an empirical and large-scale analysis of malware samples captured from two different enterprises from 2017 to early 2018. Particularly, we perform threat vector, social-engineering, vulnerability and time-series analysis on our…

The financial industry relies on deep learning models for making important decisions. This adoption brings new danger, as deep black-box models are known to be vulnerable to adversarial attacks. In computer vision, one can shape the output…

Malware is a significant threat to the security of computer systems and networks which requires sophisticated techniques to analyze the behavior and functionality for detection. Traditional signature-based malware detection methods have…

Machine learning has become a key tool in cybersecurity, improving both attack strategies and defense mechanisms. Deep learning models, particularly Convolutional Neural Networks (CNNs), have demonstrated high accuracy in detecting malware…

Anonymity systems such as Tor aim to enable users to communicate in a manner that is untraceable by adversaries that control a small number of machines. To provide efficient service to users, these anonymity systems make full use of…

Embedded devices are specialised devices designed for one or only a few purposes. They are often part of a larger system, through wired or wireless connection. Those embedded devices that are connected to other computers or embedded systems…

In an era of escalating cyber threats, malware poses significant risks to individuals and organizations, potentially leading to data breaches, system failures, and substantial financial losses. This study addresses the urgent need for…

Malicious software, or malware, presents a continuously evolving challenge in computer security. These embedded snippets of code in the form of malicious files or hidden within legitimate files cause a major risk to systems with their…

Covert communication has become an important area of research in computer security. It involves hiding specific information on a carrier for message transmission and is often used to transmit private data, military secrets, and even…

Malware distribution to the victim network is commonly performed through file attachments in phishing email or from the internet, when the victim interacts with the source of infection. To detect and prevent the malware distribution in the…

As our professional, social, and financial existences become increasingly digitized and as our government, healthcare, and military infrastructures rely more on computer technologies, they present larger and more lucrative targets for…