Military College of Signals
Researches AI-Powered Cybersecurity Lab (AI-CSL)

AI-Powered Cybersecurity Lab (AI-CSL)

1. Introduction:

The AI-Powered Cybersecurity Lab (AI-CSL) is dedicated to exploring how artificial intelligence can transform the field of cybersecurity. With a focus on creating intelligent systems, the lab develops advanced tools and strategies to identify vulnerabilities, detect emerging threats, and respond to cyber incidents. Combining expertise in machine learning, data analytics, and cybersecurity, the team works to address complex challenges and enhance the resilience of digital systems. AI-CSL’s mission is to push the boundaries of research at the intersection of AI and cybersecurity, delivering practical solutions that protect critical infrastructure and sensitive information in an increasingly connected world.

2. Research Areas

  • AI-Driven Threat Intelligence
  • Automated Vulnerability Identification and Remediation
  • Adversarial Machine Learning and Defense Mechanisms
  • Privacy and Security in AI Applications
  • Real-Time Anomaly Detection in Network Traffic

3. Group Members

Ser Name Designation​ Specialization Contact
1. Dr. Faiz Ul Islam ​Assistant Professor AI (ML/DL) in cybersecurity [email protected]
2. Dr. Narmeen Shafqat Assistant Professor Cybersecurity and Privacy, Cyber laws [email protected]
3. Aiman Aakif Assistant Professor Machine Learning,  Malware analysis, Network Security [email protected]
4. Anum Hasan Lecturer ML in security [email protected]
5. Arusa Kanwal Lecturer Image Forensics, Network Security [email protected]

 

4. Publications

  • Zhong, Dongbo, Qi Xi, Faiz Ul Islam, Zhiyong Cui, and Yufei Xie. “An efficient key tag missing identification protocol for multiple regions in the Industrial Internet of Things.” Physical Communication (2024): 102409.
  • Li, Xiaofei, Ronghua Luo, and Faiz Ul Islam. “Tracking and detection of basketball movements using multi-feature data fusion and hybrid YOLO-T2LSTM network.” Soft Computing 28, no. 2 (2024): 1653-1667.
  • Faiz Ul Islam, Guangjie Liu, Weiwei Liu, and Qazi Mazhar ul Haq. “A deep learning‐based framework to identify and characterise heterogeneous secure network traffic.” IET information Security 17, no. 2 (2023): 294-308.
  • Faiz Ul Islam, Guangjie Liu, Jiangtao Zhai, and Weiwei Liu. “VoIP traffic detection in tunneled and anonymous networks using deep learning.” IEEE Access 9 (2021): 59783-59799.
  • Faiz Ul Islam, Guangjie Liu, and Weiwei Liu. “Identifying VoIP traffic in VPN tunnel via flow spatio-temporal features.” Mathematical Biosciences and Engineering 17, no. 5 (2020): 4747-4772.

5. PhD Students

  • Muhammad Shoaib
  • Naeem Amjad
  • Sibghat Ullah
  • Amir Ali

6. Contact Person

 

MCS Research