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Wed 11 Nov 2020 01:33 - 01:34 at Virtual room 1 - Mobile

Learning-based classification dominates malware detectors for Android. However, due to the evolution of the Android ecosystem, existing such techniques are limited by their reliance on new malware samples, which may not be timely available, and constant retraining, which are often costly. A practical detector needs not only to be accurate on particular datasets but, more critically, to be able to sustain its capabilities over time without frequent retraining. We propose and study the sustainability problem for learning-based app classifiers. We define sustainability metrics and compare them among five state-of-the-art malware detectors. We further developed DroidSpan, a novel classification system based on a new behavioral profile that capture sensitive access distribution. We evaluated the sustainability of DroidSpan versus the five detectors on longitudinal datasets across eight years, which include 13,627 benign apps and 12,755 malware. We showed that DroidSpan significantly outperformed these baselines in sustainability at reasonable costs, by 6–32% for same-period detection and 21–37% for over-time detection. The main takeaway, which also explains the superiority of DroidSpan, is that the use of features consistently differentiating malware from benign apps over time is essential for sustainable learning-based malware detection, and that these features can be learned from app evolution studies.

Wed 11 Nov
Times are displayed in time zone: (UTC) Coordinated Universal Time change

01:30 - 01:32
Talk
Automated Construction of Energy Test Oracles for Android
Research Papers
Reyhaneh JabbarvandUniversity of Illinois, Urbana-Champain, Forough MehralianUniversity of California at Irvine, USA, Sam MalekUniversity of California at Irvine, USA
DOI Pre-print
01:33 - 01:34
Talk
Assessing and improving malware detection sustainability through app evolution studies
Journal First
Haipeng CaiWashington State University, USA
01:35 - 01:36
Talk
MutAPK 2.0: A Tool for Reducing Mutation Testing Effort of Android Apps
Tool Demos
Camilo Escobar-VelásquezUniversidad de los Andes, Diego RiverosUniversity of Los Andes, Colombia, Mario Linares-VásquezUniversidad de los Andes
DOI Pre-print
01:37 - 01:38
Talk
UIScreens: Extracting User Interface Screens from Mobile Programming Video Tutorials
Tool Demos
Mohammad AlahmadiFlorida State University, Ahmad TayebFlorida State University, USA, Abdulkarim KhormiFlorida State University, USA - Jazan University, KSA, Esteban ParraFlorida State University, Sonia HaiducFlorida State University
DOI
01:39 - 01:40
Talk
Where2Change: Change Request Localization for App Reviews
Journal First
Tao ZhangMacau University of Science and Technology (MUST), Jiachi ChenMonash University, Xian Zhan, Xiapu LuoHong Kong Polytechnic University, China, David LoSingapore Management University, He JiangSchool of Software, Dalian University of Technology
01:41 - 02:00
Talk
Conversations on Mobile 1
Paper Presentations
Camilo Escobar-VelásquezUniversidad de los Andes, Haipeng CaiWashington State University, USA, Jieshan ChenAustralian National University, Australia, Reyhaneh JabbarvandUniversity of Illinois, Urbana-Champain, Tao ZhangMacau University of Science and Technology (MUST), M: Yixue ZhaoUniversity of Southern California, USA