Arusa Kanwal

Cybersecurity and AI expert with experience in network security, machine learning, and digital image processing. Skilled in adversarial machine learning, image forensics, and deep learning applications like forgery detection and brain tumor detection. Published researcher and university lecturer, proficient in Python, MATLAB, and C#, specializing in AI-driven cybersecurity solutions.

• Gender: Female
• Nationality: Pakistani

• 1st International Conference on Communication Technology, MCS, NUST, 2017
• International Conference on Computing Research, CUST, 12/01/22

• Exploring Security Dynamics in SDN Controller Architectures: Threat Landscape and Implications, A. Kanwal, M. Nizamuddin, W. Iqbal, W. Aman, Y. Abbas, S. Mussiraliyeva, IEEE Access, 01/01/24, 10.1109/ACCESS.2024.3390968
• Copy-Move forgery detection based on SURF and RANSAC, A. Kanwal, I. Fatima, R. Habib, MDPI, Under Review, 2024

• Merit based scholarship for MS, Punjab Government, 2017-2019
• Merit based scholarship for BE, NUST, 2012-2014

• Kangaroo math competition, 5th, 2006
• English spelling competition, 3rd, 2004

• Muhammad Waseem Iqbal

Assistant Professor - College of Engineering

Sultan Qaboos University,  Oman  

waseem.iqbal@mcs.edu.pk  

• Muhammad Kamran Khan

Assistant Professor – Electrical Engineering Department

National University of Sciences and Technology (NUST),  Pakistan  

kamran.khan@mcs.nust.edu.pk  

• Sara Durrani

Lecturer – Computer Science Department

Bahria University, Islamabad  

Sara.buic@bahria.edu.pk

• Cyber Security - I have an extensive expertise in network security, information security, and cryptography, with hands-on experience in vulnerability exploitation, reverse engineering, malware analysis, and wireless security. I have worked on adversarial machine learning techniques for cybersecurity applications, including object classification, intrusion detection, and web fingerprinting. The practical skills include the use of tools like Metasploit, Social Engineering Toolkit, and Armitage for penetration testing and ethical hacking.
• Machine learning and Deep learning - I have developed deep learning-based systems for brain tumor detection and age estimation, showcasing their proficiency in artificial intelligence applications. My research also includes designing image forgery detection techniques using SURF, kNN-matching, and segmentation, achieving enhanced precision and recall metrics. Additionally, I have leveraged Generative Adversarial Networks (GANs) for sub-domain enumeration, demonstrating expertise in cutting-edge AI techniques.
• Digital Image Processing - With significant experience in image forensics, I have developed advanced systems for copy-move forgery detection and surveillance recording using MATLAB. The work emphasizes precise and effective image-based analysis.
• Teaching and Research - As a lecturer at NUST and CUST, I have taught key courses like Data Structures, Cryptographic Design Engineering, and Object-Oriented Programming. My research contributions include published work in high-impact journals, further strengthening their expertise in AI-driven cybersecurity and image processing.