Cyber Threat
Cyber threats encompass a broad range of malicious activities targeting digital systems, with the primary objective of mitigating these threats and improving cybersecurity defenses. Current research focuses on leveraging machine learning, particularly employing models like graph neural networks, large language models (LLMs), and random forests, to detect and predict attacks, analyze threat intelligence, and even proactively expose malicious registrations. This research is crucial for enhancing cybersecurity across various sectors, from finance and agriculture to critical infrastructure, by improving threat detection accuracy, automating responses, and developing more robust and explainable security systems.
Papers
Cyber Risks of Machine Translation Critical Errors : Arabic Mental Health Tweets as a Case Study
Hadeel Saadany, Ashraf Tantawy, Constantin Orasan
How to integrate cloud service, data analytic and machine learning technique to reduce cyber risks associated with the modern cloud based infrastructure
Upakar Bhatta