CRFeb 12, 2018

Personal Mobile Malware Guard PMMG: a mobile malware detection technique based on user's preferences

arXiv:1802.04328v14 citations
Originality Synthesis-oriented
AI Analysis

This addresses mobile security and privacy for personal device users, but it appears incremental as it builds on user feedback without introducing a major new approach.

The paper tackles the problem of mobile malware detection by proposing a technique called Personal Mobile Malware Guard (PMMG) that classifies malware based on user feedback and controls app permissions according to user preferences, with performance analysis showing it is theoretically feasible to implement on mobile devices.

Mobile malware has increased rapidly last 10 years. This rapid increase is due to the rapid enhancement of mobile technology and their power to do most work for their users. Since mobile devices are personal devices, then a special action must be taken towards preserving privacy and security of the mobile data. Malware refers to all types of software applications with malicious behavior. In this paper, we propose a malware detection technique called Personal Mobile Malware Guard ? PMMG- that classifies malwares based on the mobile user feedback. PMMG controls permissions of different applications and their behavior according to the user needs. These preferences are built incrementally on a personal basis according to the feedback of the user. Performance analysis showed that it is theoretically feasible to build PMMG tool and use it on mobile devices.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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