Mobile devices, such as smartphones, tablets, smart TVs, and others have become increasingly popular since they provide essential functionality in our everyday life. However, mobile devices present greater security and privacy issues to users in terms of both mobile platform vulnerabilities and the vast advancements in sophistication of malicious software. By installing malicious software, mobile devices can be infected with worms, Trojan horses or other virus families, which can compromise the user's security, privacy, or even gain complete control over the device. In this research, we present an analysis of contemporary mobile platform threats and give an in-depth overview of threat environment and security mechanisms built into state-of-the-art mobile operating systems. Specifically, we have the following three research objectives to achieve: Our first research objective is to present a comprehensive discussion on the three competing modern mobile platforms: iOS, Android, and BlackBerry. Moreover, we discuss the common vulnerabilities of the mobile platforms and the existing security models of these operating systems to protect mobile devices. Our second research objective is to present a threat model of each mobile platform. Specifically, we first discuss the factors that motivate attackers to breach mobile security. We also present the attack vectors and the modern exploitation techniques used by attackers to breach the security of a mobile device by inserting malicious codes. In addition, we discuss some common types of malwares particularly designed for mobile devices such as mobile Trojans/worms and other viruses. Our third research objective is to present state-of-the-art security defense mechanisms to protect mobile platforms and devices along with a brief discussion on future trends in mobile security and its applications.
|Original language||English (US)|
|Title of host publication||Security, Privacy and Reliability in Computer Communications and Networks|
|Number of pages||35|
|State||Published - Feb 1 2017|
All Science Journal Classification (ASJC) codes
- Computer Science(all)