Targeted Privacy Attacks by Fingerprinting Mobile Apps in LTE Radio Layer

Jaejong Baek, Pradeep Kumar Duraisamy Soundrapandian, Sukwha Kyung, Ruoyu Wang, Yan Shoshitaishvili, Adam Doupé, Gail-Joon Ahn

Abstract: We investigate the feasibility of targeted privacy attacks using only information available in physical channels of LTE mobile networks and propose three privacy attacks to demonstrate this feasibility: mobile-app fingerprinting attack, history attack, and correlation attack. These attacks can reveal the geolocation of targeted mobile devices, the victim's app usage patterns, and even the relationship between two users within the same LTE network cell. An attacker also may launch these attacks stealthily by capturing radio signals transmitted over the air, using only a passive sniffer as equipment. To ensure the impact of these attacks on mobile users' privacy, we perform evaluations in both laboratory and real-world settings, demonstrating their practicality and dependability. Furthermore, we argue that these attacks can target not only 4G/LTE but also the evolving 5G standards.