Malicious traffic analysis on mobile devices: a hardware solution Online publication date: Sun, 26-Apr-2015
by Mario Barbareschi; Antonino Mazzeo; Antonino Vespoli
International Journal of Big Data Intelligence (IJBDI), Vol. 2, No. 2, 2015
Abstract: The security of smartphone devices is increasingly jeopardised by viruses, intrusion attempts and trojans, which most of them come from the internet traffic. Since the involved traffic is huge and has a complex nature, those threats are difficult to discover and immunise. The mobile devices cannot adopt classical approaches to improve security, such as the traffic analysis, because they are mobile, so resource is constrained and without a power supply. As indeed, most widespread mobile operating systems, such as Android, do not provide any software routine to accomplish this analysis. Recently, in the literature, machine learning approaches have been adopted for the traffic analysis and they exploit a hardware implementation to guarantee high packets throughput and low energy consumption. In order to show the feasibility of the approach, in terms of throughput, latency and energy consumption, in this paper we propose a hybrid computing architecture which enables the communication between the Android OS and a traffic analysis hardware accelerator, coexisting on the same chip. At this aim, the proposed architecture is hosted by new FPGA chip family, the Xilinx's Zynq, a SoPC based on dual-core ARM.
Online publication date: Sun, 26-Apr-2015
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