Mitziu Echeverria (The University of Iowa), Zeeshan Ahmed (The University of Iowa), Bincheng Wang (The University of Iowa), M. Fareed Arif (The University of Iowa), Syed Rafiul Hussain (Pennsylvania State University), Omar Chowdhury (The University of Iowa)

End-user-devices in the current cellular ecosystem are prone to many different vulnerabilities across different generations and protocol layers. Fixing these vulnerabilities retrospectively can be expensive, challenging, or just infeasible. A pragmatic approach for dealing with such a diverse set of vulnerabilities would be to identify attack attempts at runtime on the device side, and thwart them with mitigating and corrective actions. Towards this goal, in the paper we propose a general and extendable approach called PHOENIX for identifying n-day cellular network control-plane vulnerabilities as well as dangerous practices of network operators from the device vantage point. PHOENIX monitors the device-side cellular network traffic for performing signature-based unexpected behavior detection through lightweight runtime verification techniques. Signatures in PHOENIX can be manually-crafted by a cellular network security expert or can be automatically synthesized using an optional component of PHOENIX , which reduces the signature synthesis problem to the language learning from the informant problem. Based on the corrective actions that are available to PHOENIX when an undesired behavior is detected, different instantiations of PHOENIX are possible: a full-fledged defense when deployed inside a baseband processor; a user warning system when deployed as a mobile application; a probe for identifying attacks in the wild. One such instantiation of PHOENIX was able to identify all 15 representative n-day vulnerabilities and unsafe practices of 4G LTE networks considered in our evaluation with a high packet processing speed (∼68000 packets/second) while inducing only a moderate amount of energy overhead (∼4mW).

View More Papers

Screen Gleaning: A Screen Reading TEMPEST Attack on Mobile...

Zhuoran Liu (Radboud university), Niels Samwel (Radboud University), Léo Weissbart (Radboud University), Zhengyu Zhao (Radboud University), Dirk Lauret (Radboud University), Lejla Batina (Radboud University), Martha Larson (Radboud University)

Read More

Detecting DolphinAttacks Based on Microphone Array

Guoming Zhang, Xiaoyu Ji (Zhejiang University)

Read More

From WHOIS to WHOWAS: A Large-Scale Measurement Study of...

Chaoyi Lu (Tsinghua University; Beijing National Research Center for Information Science and Technology), Baojun Liu (Tsinghua University; Beijing National Research Center for Information Science and Technology; Qi An Xin Group), Yiming Zhang (Tsinghua University; Beijing National Research Center for Information Science and Technology), Zhou Li (University of California, Irvine), Fenglu Zhang (Tsinghua University), Haixin Duan…

Read More

Digital Technologies in Pandemic: The Good, the Bad and...

Moderator: Ahmad-Reza Sadeghi, TU Darmstadt, Germany Panelists: Mario Guglielmetti, Legal Officer, European Data Protection Supervisor* Jaap-Henk Hoepman, Radbaud University, The Netherlands Alexandra Dmitrienko, University of Würzburg, Germany, Farinaz Koushanfar, UCSD, USA *attending in his personal capacity

Read More