This research project represents cutting-edge contributions to the field of cybersecurity by leveraging machine learning techniques. Each outcome tackles a specific challenge within the domain, ranging from enhancing DDoS attack detection to detecting obfuscated malware in memory dumps, showcasing innovative approaches, and achieving exceptional accuracy rates, thereby significantly advancing cybersecurity practices.
Some snapshots are presented below from the outcomes
Other Publications from the Project
In the project, I assumed a comprehensive role, encompassing all aspects from implementation to manuscript writing. This involved designing and executing experiments, analyzing data, developing machine-learning models, and crafting the research findings into coherent manuscripts. To achieve the project goals, collaboration was essential with peers, advisors, and potentially other researchers in the field, involving discussions, feedback sessions, and coordination of efforts. The outcome of these projects was the successful development of innovative solutions addressing specific cybersecurity challenges, demonstrated through rigorous experimentation and documented in high-quality research papers that contribute significantly to the field.