NICRLGJul 10, 2024

Characterizing Encrypted Application Traffic through Cellular Radio Interface Protocol

arXiv:2407.07361v22 citationsh-index: 27
Originality Incremental advance
AI Analysis

This reveals a privacy vulnerability in 5G networks that could allow attackers to fingerprint encrypted applications, posing a threat to user anonymity.

The paper demonstrates that 5G radio communication can be used as a side channel to infer users' applications in real-time by observing physical and MAC layer interactions, achieving precise differentiation across categories like online shopping and video streaming.

Modern applications are end-to-end encrypted to prevent data from being read or secretly modified. 5G tech nology provides ubiquitous access to these applications without compromising the application-specific performance and latency goals. In this paper, we empirically demonstrate that 5G radio communication becomes the side channel to precisely infer the user's applications in real-time. The key idea lies in observing the 5G physical and MAC layer interactions over time that reveal the application's behavior. The MAC layer receives the data from the application and requests the network to assign the radio resource blocks. The network assigns the radio resources as per application requirements, such as priority, Quality of Service (QoS) needs, amount of data to be transmitted, and buffer size. The adversary can passively observe the radio resources to fingerprint the applications. We empirically demonstrate this attack by considering four different categories of applications: online shopping, voice/video conferencing, video streaming, and Over-The-Top (OTT) media platforms. Finally, we have also demonstrated that an attacker can differentiate various types of applications in real-time within each category.

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