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ASE 2019
Sun 10 - Fri 15 November 2019 San Diego, California, United States
Tue 12 Nov 2019 15:00 - 15:20 at Hillcrest - Mobile 2 Chair(s): Myra Cohen

Malware scanning of an app market is expected to be scalable and effective. However, existing approaches use either syntax-based features which can be evaded by transformation attacks or semantic-based features which are usually extracted by performing expensive program analysis. Therefore, in this paper, we propose a lightweight graph-based approach to perform Android malware detection. Instead of traditional heavyweight static analysis, we treat function call graphs of apps as social networks and perform social-network-based centrality analysis to represent the semantic features of the graphs. Our key insight is that centrality provides a succinct and fault- tolerant representation of graph semantics, especially for graphs with certain amount of inaccurate information (e.g., inaccurate call graphs). We implement a prototype system, MalScan, and evaluate it on datasets of 15,285 benign samples and 15,430 malware samples. Experimental results show that MalScan is capable of detecting Android malware with up to 98% accuracy under one second which is more than 100 times faster than two state-of-the-art approaches, namely MaMaDroid and Drebin. We also demonstrate the feasibility of MalScan on market-wide malware scanning by performing a statistical study on over 3 million apps. Finally, in a corpus of dataset collected from Google-Play app market, MalScan is able to identify 18 zero-day malware including malware samples that can evade detection of existing tools.

Tue 12 Nov

13:40 - 15:20: Papers - Mobile 2 at Hillcrest
Chair(s): Myra CohenIowa State University
ase-2019-papers13:40 - 14:00
A Qualitative Analysis of Android Taint-Analysis Results
Linghui LuoPaderborn University, Eric BoddenHeinz Nixdorf Institut, Paderborn University and Fraunhofer IEM, Johannes SpäthFraunhofer IEM
ase-2019-papers14:00 - 14:20
Goal-Driven Exploration for Android Applications
Duling LaiUniversity of British Columbia, Julia RubinUniversity of British Columbia
ase-2019-papers14:20 - 14:40
RANDR: Record and Replay for Android Applications via Targeted Runtime Instrumentation
Onur SahinBoston University, Assel AliyevaBoston University, Hariharan MathavanBoston University, Ayse CoskunBoston University, Manuel EgeleBoston University, USA
ase-2019-Journal-First-Presentations14:40 - 15:00
Specifying Callback Control Flow of Mobile Apps Using Finite Automata
Danilo Dominguez PerezIowa State University, Wei LeIowa State University
Link to publication
ase-2019-papers15:00 - 15:20
MalScan: Fast Market-Wide Mobile Malware Scanning by Social-Network Centrality Analysis
Yueming WuHuazhong University of Science and Technology, Xiaodi LiUniversity of Texas at Dallas, Deqing ZouHuazhong University of Science and Technology, Wei YangUniversity of Texas at Dallas, Xin ZhangHuazhong University of Science and Technology, Hai JinHuazhong University of Science and Technology