Enhancing PacketFlowAI: Upgrading My Packet Classification Algorithm with Hyperdimensional Computing
Introduction
Network security is one of the most pressing issues in today’s digital landscape. The ability to classify and detect malicious network traffic in real-time is crucial to prevent cyber attacks. PacketFlowAI is an open-source project I designed for packet classification, offering an automated approach to monitoring and analysing network traffic to detect security threats such as DDoS, malware, port scanning and phishing attacks.
While the traditional machine learning models I used in PacketFlowAI have been effective they have limitations in terms of scalability, robustness to noise and their computational efficiency. To address these challenges I’ve upgraded PacketFlowAI using Hyperdimensional Computing (HDC) — a computing paradigm inspired by brain-like processing of information. This blog post provides a comprehensive overview of the mathematical foundations, architecture and practical implementation of HDC in PacketFlowAI.
