Mobile network anomaly detection and mitigation: The NEMESYS approach

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

Discovering parameter setting in 3G networks via active measurements

The behavior and performance of a UMTS network are governed by a number of parameter settings that are configured by the network operator, e.g., timeouts. In this letter we show that the actual value of such parameters can be inferred by a conceptually simple set of end-to-end measurements, without any cooperation with the network operator. In principle, such information can be used by researchers to define realistic network scenarios, e.g., for their simulations. Moreover, it can be used by a malicious attacker to fine-tune a large scale attack against the Radio Access Network, e.g., a paging attack

Handwritten processing for Pre Diagnosis of Alzheimer disease

Based on neuromuscular transfer function of the handwriting system, in this paper a non invasive pre diagnosis system for Alzheimer disease alert is proposed. It is well known in fact, that writing originates from spike trains produced within the Central Nervous System (CNS) and more specifically, inside the 4-th and the 6-th regions of the Bradman's map and then transmitted through the first and second order axons to the spinal cord to control the muscles involved in the handwriting as the arm, the forearm, the hand and the pen or pencil utilized for the writing. More specifically, in this work is proposed a new method, not invasive, for early diagnosis of degenerative disability, it can be also useful for monitoring activities related to the progression of neuromuscular disease in order to evaluate the changing related also to the efficiency of the therapies used. Benefit can be obtained not only for the medical field but also for the pharmaceutical developments. Specifically in the paper, the results of some experiments have been focused by considering a certain number of persons some of which affect by Alzheimer disease

HFSP: Size-based scheduling for Hadoop

none5siSize-based scheduling with aging has, for long, been recognized as an effective approach to guarantee fairness and near-optimal system response times. We present HFSP, a scheduler introducing this technique to a real, multi-server, complex and widely used system such as Hadoop. Size-based scheduling requires a priori job size information, which is not available in Hadoop: HFSP builds such knowledge by estimating it on-line during job execution. Our experiments, which are based on realistic workloads generated via a standard benchmarking suite, pinpoint at a significant decrease in system response times with respect to the widely used Hadoop Fair scheduler, and show that HFSP is largely tolerant to job size estimation errors. © 2013 IEEE.mixedPastorelli M.; Barbuzzi A.; Carra D.; Dell'Amico M.; Michiardi P.Pastorelli, M.; Barbuzzi, A.; Carra, D.; Dell'Amico, M.; Michiardi, P

Writing Generation Model for Health Care neuromuscular System

In this paper the use of handwriting artifacts for health investigation is addressed. For the purpose, the paper first presents the Delta-Log and Sigma-Lognormal models to investigate on the handwriting generation processes carried out by the neuromuscular system. Successively, a computational system for handwriting analysis is presented and some considerations are exploited about the use of the model to investigate insurgence and monitoring of some neuromuscular diseases. The experimental results show the validity of the proposed approach and highlight some directions for further research

Writing Generation Model for Health Care Neuromuscolar System Investigation

In this paper the use of handwriting artifacts for health investigation is addressed. For the purpose, the paper first presents the Delta-Log and Sigma-Lognormal models to investigate on the handwriting generation processes carried out by the neuromuscular system. Successively, a computational system for handwriting analysis is presented and some considerations are exploited about the use of the model to investigate insurgence and monitoring of some neuromuscular diseases. The experimental results show the validity of the proposed approach and highlight some directions for further research