Developed a neural network-based intrusion detection system (IDS) using network traffic data captured via Wireshark. Engineered features from raw packets and implemented classification models for detecting malicious patterns. Conducted adversarial testing by manually crafting and injecting malicious packets to evaluate the system’s robustness and detection accuracy. Co-authored a research paper, which got accepted at the 2nd International AIMV (AI, IoT & Machine Vision) Conference, 2025 (Under-process).