Packet Level

Packet-level analysis focuses on examining individual network packets to extract features for various applications, primarily network security and communication optimization. Current research emphasizes using machine learning, particularly deep learning models like recurrent autoencoders and graph neural networks, often combined with large language models for improved interpretability and real-time processing. This detailed analysis is crucial for enhancing intrusion detection systems, improving encrypted traffic classification, and optimizing the efficiency and resilience of communication systems, particularly in the face of packet loss or adversarial attacks.