Jianfeng Li (The Hong Kong Polytechnic University), Shuohan Wu (The Hong Kong Polytechnic University), Hao Zhou (The Hong Kong Polytechnic University), Xiapu Luo (The Hong Kong Polytechnic University), Ting Wang (Penn State), Yangyang Liu (The Hong Kong Polytechnic University), Xiaobo Ma (Xi'an Jiaotong University)

Mobile apps have profoundly reshaped modern lifestyles in different aspects. Several concerns are naturally raised about the privacy risk of mobile apps. Despite the prevalence of encrypted communication, app fingerprinting (AF) attacks still pose a serious threat to users’ online privacy. However, existing AF attacks are usually hampered by four challenging issues, namely i) hidden destination, ii) invisible boundary, iii) app multiplexing, and iv) open-world recognition, when they are applied to wireless traffic. None of existing AF attacks can address all these challenges. In this paper, we advance a novel AF attack, dubbed PACKETPRINT, to recognize user activities associated with the app of interest from encrypted wireless traffic and tackle the above challenges by proposing two novel models, i.e., sequential XGBoost and hierarchical bag-of- words model. We conduct extensive experiments to evaluate the proposed attack in a series of challenging scenarios, including i) open-world setting, ii) packet loss and network congestion, iii) simultaneous use of different apps, and iv) cross-dataset recognition. The experimental results show that PACKETPRINT can accurately recognize user activities associated with the apps of interest. It achieves the average F1-score 0.884 for open-world app recognition and the average F1-score 0.959 for in-app user action recognition.

View More Papers

FakeGuard: Exploring Haptic Response to Mitigate the Vulnerability in...

Aditya Singh Rathore (University at Buffalo, SUNY), Yijie Shen (Zhejiang University), Chenhan Xu (University at Buffalo, SUNY), Jacob Snyderman (University at Buffalo, SUNY), Jinsong Han (Zhejiang University), Fan Zhang (Zhejiang University), Zhengxiong Li (University of Colorado Denver), Feng Lin (Zhejiang University), Wenyao Xu (University at Buffalo, SUNY), Kui Ren (Zhejiang University)

Read More

Demo: A Simulator for Cooperative and Automated Driving Security

Mohammed Lamine Bouchouia (Telecom Paris - Institut Polytechnique de Paris), Jean-Philippe Monteuuis (Qualcomm), Houda Labiod (Telecom Paris - Institut Polytechnique de Paris), Ons Jelassi, Wafa Ben Jaballah (Thales) and Jonathan Petit (Telecom Paris - Institut Polytechnique de Paris)

Read More

Privacy in Urban Sensing with Instrumented Fleets, Using Air...

Ismi Abidi (IIT Delhi), Ishan Nangia (MPI-SWS), Paarijaat Aditya (Nokia Bell Labs), Rijurekha Sen (IIT Delhi)

Read More

FitM: Binary-Only Coverage-GuidedFuzzing for Stateful Network Protocols

Dominik Maier, Otto Bittner, Marc Munier, Julian Beier (TU Berlin)

Read More