Robust Android Malware Detector

Completed supervised project implementing static disassembly analysis, APK opcode feature vectors, and ensemble machine learning classifiers for resilient Android malware detection.

Android MalwareApktool DisassemblyRandom Forest Classifier

Students

FA25SE28 Student GroupFA25SE28

Supervision

Dr. Junaid AkramLead Supervisor

Institution

Malware ResearchCOMSATS University Islamabad, Lahore Campus

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