Characterizing malicious Android apps by mining topic-specific data flow signatures

• Main Authors: YANG, Xinli, LO, David, LI, Li, XIA, Xin, BISSYANDE, Tegawendé F., KLEIN, Jacques
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Malware characterization; Topic-specific; Data flow signature; Empirical study; Information Security; Numerical Analysis and Scientific Computing; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/3675; https://ink.library.smu.edu.sg/context/sis_research/article/4677/viewcontent/1_s20_S095058491730366X_main.pdf
• Institution: Singapore Management University

Context: State-of-the-art works on automated detection of Android malware have leveraged app descriptions to spot anomalies w.r.t the functionality implemented, or have used data flow information as a feature to discriminate malicious from benign apps. Although these works have yielded promising per...