Malware Feature Extraction via Machine Learning Algorithm

Supervised research evaluating feature selection techniques for automated malware detection across PE executable headers.

Malware ClassificationFeature SelectionMachine Learning

Students

Eilsen Law Yi Sheng

Supervision

Dr. Junaid AkramLead Supervisor

Institution

Malware ResearchXiamen University Malaysia

Supervised Projects Portfolio

More Supervised Projects

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Full-Stack & Systems

MegiLance — AI and Blockchain-Powered Freelancing Platform

A supervised final-year engineering development project combining a full-stack freelancing marketplace with AI decision assistance and blockchain payment escrow.

Ghulam Mujtaba, Muhammad Waqar Ul MulkView Case Study

Vulnerability & Security

Software Vulnerability Detection using LLM Model

A running research project leveraging Large Language Models (LLMs) to detect complex software vulnerabilities in source code through fine-tuning and AST-based prompt engineering.

Syed Muhammad Irtaza Shahid, Muhammad Waleed, Muhammad Muneeb AzharView Case Study

Vulnerability & Security

Token-Based Semantic Code Clone Detection

A running software security project building a scalable token-based semantic code clone detection platform to capture Type-3 and Type-4 clones across large open-source repositories.

Ali Muhammad, Ali Murtaza, Hafiz Muhammad Shams ul HudaView Case Study