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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. 

Android applications are extremely popular, as they are widely used for banking, social media, e-commerce, etc. Such applications typically leverage a series of Permissions, which serve as a convenient abstraction for mediating access to security-sensitive functionality within the Android Ecosystem, e.g., sending data over the Internet. However, several malicious applications have recently deployed attacks such as data leaks and spurious credit card charges by abusing the Permissions granted initially to them by unaware users in good faith. To alleviate this pressing concern, we present DyPolDroid, a dynamic and semi-automated security framework that builds upon Android Enterprise, a device-management framework for organizations, to allow for users and administrators to design and enforce so-called Counter-Policies, a convenient user-friendly abstraction to restrict the sets of Permissions granted to potential malicious applications, thus effectively protecting against serious attacks without requiring advanced security and technical expertise. Additionally, as a part of our experimental procedures, we introduce Laverna, a fully operational application that uses permissions to provide benign functionality at the same time it also abuses them for malicious purposes. To fully support the reproducibility of our results, and to encourage future work, the source code of both DyPolDroid and Laverna is publicly available as open-source.