A Survey on Security for Mobile Devices

By M. L. Polla, Fabio Martinelli, Daniele Sgandurra. IEEE Communications Surveys and Tutorials, 2013

560 citations recorded by the source corpus.

Nowadays, mobile devices are an important part of our everyday lives since they enable us to access a large variety of ubiquitous services. In recent years, the availability of these ubiquitous and mobile services has significantly increased due to the different form of connectivity provided by mobile devices, such as GSM, GPRS, Bluetooth and Wi-Fi. In the same trend, the number and typologies of vulnerabilities exploiting these services and communication channels have increased as well. Therefore, smartphones may now represent an ideal target for malware writers. As the number of vulnerabilities and, hence, of attacks increase, there has been a corresponding rise of security solutions proposed by researchers. Due to the fact that this research field is immature and still unexplored in depth, with this paper we aim to provide a structured and comprehensive overview of the research on security solutions for mobile devices. This paper surveys the state of the art on threats, vulnerabilities and security solutions over the period 2004-2011, by focusing on high-level attacks, such those to user applications. We group existing approaches aimed at protecting mobile devices against these classes of attacks into different categories, based upon the detection principles, architectures, collected data and operating systems, especially focusing on IDS-based models and tools. With this categorization we aim to provide an easy and concise view of the underlying model adopted by each approach.

Subfields: Artificial Intelligence, Computer Networks and Communications, Signal Processing

View Paper: https://www.semanticscholar.org/paper/6906431861dff300461e595f756c13c95a9507cb

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Citations in the corpus

Static analysis of android apps: A systematic literature review (2017, background): “Similarly, [185] and [186] present state-of-the-art reviews with considering multiple mobile platforms.”
Android HIV: A Study of Repackaging Malware for Evading Machine-Learning Detection (2018, unknown): “surveys for typical methods [13], [18], [28].”
A Survey on Wireless Body Area Networks: Technologies and Design Challenges (2014, background): “Surveys on solutions to increase WBAN reliability, security and availability is given in [8] and [9].”
Android Security: A Survey of Issues, Malware Penetration, and Defenses (2015, background): “art considering the popular mobile OS platforms [31], [32].”
The Evolution of Android Malware and Android Analysis Techniques (2017, background): “Built-in support for background SMS to premium numbers was also found in 45–50% [La Polla et al. 2013; Felt et al. 2011] of the samples, and user information harvesting, a top security issue in 2011 [Felt et al. 2011], is still a current issue with 51% of malware samples exhibiting this behavior…”