Mobile malware and mobile network attacks are becoming a significant threat that accompanies the increasing popularity of smart phones and tablets. Thus in this paper we present our research vision that aims to develop a network-based security solution combining analytical modelling, simulation and learning, together with billing and control-plane data, to detect anomalies and attacks, and eliminate or mitigate their effects, as part of the EU FP7 NEMESYS project. These ideas are supplemented with a careful review of the state-of-the-art regarding anomaly detection techniques that mobile network operators may use to protect their infrastructure and secure users against malware.
@article{arxiv.1305.4210,
title = {Mobile Network Anomaly Detection and Mitigation: The NEMESYS Approach},
author = {Omer H. Abdelrahman and Erol Gelenbe and Gökçe Görbil and Boris Oklander},
journal= {arXiv preprint arXiv:1305.4210},
year = {2013}
}
Comments
To Appear in the Proceedings of the 28th International Symposium on Computer and Information Sciences (ISCIS 2013), Springer LNEE