SpotMal: A hybrid malware detection framework with privacy protection for BYOD

Abstract

The proliferation of mobile devices coupled with their increased computing capabilities has made them perfectly fit in the business environment. Bring Your Own Device (BYOD) is the phenomenon where individuals bring their own portable devices for connectivity and use in the workplace. BYODs introduce several benefits such as increased productivity and employee motivation but also a range of security challenges. Hackers have developed multifaceted malware targeting these BYODs. Research has been done on mobile malware detection however, because of their resource-constraint, the adoption of PC-based malware detection methods such as signature and behavior-based detection techniques has proved to be challenging. Users have cited privacy concerns when these virus detection techniques are remotely applied on the BYOD for example cloud-based detection since these devices are used for both personal and work data storage. This paper examines the threat of mobile malware to organizations that have adopted BYOD and current solutions to this threat. Additionally, a hybrid malware detection framework with privacy protection for BYOD and smart-work environments is proposed to detect malware without compromising the privacy and confidentiality of personal sensitive data.

DOI: 10.1145/2815782.2815812

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@inproceedings{Gudo2015SpotMalAH, title={SpotMal: A hybrid malware detection framework with privacy protection for BYOD}, author={Munyaradzi Gudo and Keshnee Padayachee}, booktitle={SAICSIT}, year={2015} }