Bissal Javaid

PROFESSIONAL PROFILE Final-year Computer Science student with interdisciplinary experience in cybersecurity, machine learning, and generative AI, focused on DDoS detection using real-world network traffic datasets. Seeking an entry-level or research-oriented role to apply AI-driven threat detection, network security, and data analysis skills in real-world cyber defense environments. EDUCATION BS in Computer Science SEECS , Islamabad , 3.29 (2026) INTERNSHIP EXPERIENCE SEECS 13-Nov-2024 - 15-Jun-2025 Participated in the conceptualization and design of the generalized rule-driven network traffic filtering mechanism. Conducted rigorous testing of the proposed solution, meticulously collecting and analyzing data to derive results. Played a role in the drafting and refinement of the research paper, documenting the methodology, findings, and conclusions. ONT Lab SEECS 01-Jun-2025 - 01-Sep-2025 Worked with network simulation tools, including Mininet and Mininet-Optical for software-defined and optical network experimentation. Designed and simulated multiple optical network topologies, analyzing connectivity, routing behavior, and performance characteristics. FINAL YEAR PROJECT Development of a DDoS Network Traffic Dataset for Deep Learning-Based Prediction and Prevention of Attacks This project addresses the critical gap by conducting a thorough analysis of existing DDoS datasets to highlight their limitations and then developing a new dataset that includes diverse DDoS attack traffic and corresponding normal traffic. The dataset will be used to train and evaluate deep learning models capable of accurately detecting and predicting DDoS attacks. The goal is to enhance the reliability and early detection capabilities of intrusion detection systems using real-world-like, labeled traffic data suitable for deep learning applications. TECHNICAL EXPERTISE Cybersecurity & Network Security Research experience in DDoS detection, network traffic analysis, and attack mitigation using real-world datasets. Familiar with packet inspection, traffic filtering, and Linux-based networking environments. Machine Learning for Security Applied machine learning techniques for the generation of network traffic for improving quality of dataset. Experienced in data preprocessing, feature engineering, model evaluation, and cross-validation on security datasets. Generative AI & AI-Driven Security Explored generative AI and deep learning approaches for synthesizing and analyzing network traffic data. Interested in

Final-year Computer Science student with interdisciplinary experience in cybersecurity, machine learning, and generative AI, focused on DDoS detection using real-world network traffic datasets. Seeking an entry-level or research-oriented role to apply AI-driven threat detection, network security, and data analysis skills in real-world cyber defense environments.