Title :
MDoctor: A Mobile Malware Prognosis Application
Author :
Lagerspetz, Eemil ; Hien Thi Thu Truong ; Tarkoma, Sasu ; Asokan, N.
Author_Institution :
Univ. of Helsinki, Helsinki, Finland
fDate :
June 30 2014-July 3 2014
Abstract :
Mobile malware is on the rise as the global number of smartphone users grows exponentially. Traditional malware detection and scanning tools only detect malware when devices are actually infected. In previous work, we saw that the presence of applications that occur often with known malware can indicate not only infection status but also potential risk of infection. In this paper, we present Doctor - a malware prognosis application based on crowd sourced data. Doctor includes a server component and an easy-to-use Android client application. Doctor visualizes the health of the device as a pie chart, slices representing applications. Each slice is split into four sections, corresponding to different lightweight indicators of infection. Sections of each slice are colored from green to red. The greater the amount of red, the greater the risk of infection. This front-end application provides users a new function for malware prognosis which is currently missing in existing mobile anti-malware tools.
Keywords :
Android (operating system); invasive software; mobile computing; smart phones; Android client application; MDoctor; malware detection; mobile antimalware tool; mobile malware prognosis application; pie chart; scanning tool; server component; Androids; Batteries; Humanoid robots; Malware; Mobile communication; Prognostics and health management; Servers; Android; mobile malware; prognosis;
Conference_Titel :
Distributed Computing Systems Workshops (ICDCSW), 2014 IEEE 34th International Conference on
Conference_Location :
Madrid
Print_ISBN :
978-1-4799-4182-7
DOI :
10.1109/ICDCSW.2014.36