A performance-sensitive malware detection system using deep learning on mobile devices

• Main Authors: FENG, Ruitao, CHEN, Sen, XIE, Xiaofei, MENG, Guozhu, LIN, Shang-Wei, LIU, Yang
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Malware; Androids; Humanoid robots; Feature extraction; Mobile handsets; Performance evaluation; Security; Android malware; malware detection; deep neural network; mobile platform; performance; OS and Networks; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/6937; https://ink.library.smu.edu.sg/context/sis_research/article/7940/viewcontent/2005.04970__1_.pdf
• Institution: Singapore Management University

Currently, Android malware detection is mostly performed on server side against the increasing number of malware. Powerful computing resource provides more exhaustive protection for app markets than maintaining detection by a single user. However, apart from the applications (apps) provided by the o...