Collaborative Countermeasure Against Network Traffic Analyses Based on Packet Aggregation

Network traffic analysis attacks represent a significant threat to information security and user privacy. Leveraging machine learning, these attacks can infer sensitive information even when encryption and anonymization techniques are in place. This paper proposes TravelingTogether, a novel framework that leverages packet aggregation from multiple source hosts to defend users against network traffic analysis. TravelingTogether works at the network level, providing transparent and seamless protection to any hosts connected to the network. We evaluate our defense across different scenarios through a comprehensive set of experiments, demonstrating its effectiveness in thwarting website fingerprinting attacks as a representative use case, and its efficiency in terms of low time and bandwidth overhead.