An FPGA Based Tracking Implementation for Parkinson's Patients.

This paper presents a study on the optimization of the tracking system designed for patients with Parkinson's disease tested at a day hospital center. The work performed significantly improves the efficiency of the computer vision based system in terms of energy consumption and hardware requirements. More specifically, it optimizes the performances of the background subtraction by segmenting every frame previously characterized by a Gaussian mixture model (GMM).

Compiler optimizations as a countermeasure against side-channel analysis in MSP430-based devices.

Ambient Intelligence (AmI) requires devices everywhere, dynamic and massively distributed networks of low-cost nodes that, among other data, manage private information or control restricted operations. MSP430, a 16-bit microcontroller, is used in WSN platforms, as the TelosB. Physical access to devices cannot be restricted, so attackers consider them a target of their malicious attacks in order to obtain access to the network.

Improving Security for SCADA Sensor Networks with Reputation Systems and Self-Organizing Maps.

The reliable operation of modern infrastructures depends on computerized systems and Supervisory Control and Data Acquisition (SCADA) systems, which are also based on the data obtained from sensor networks. The inherent limitations of the sensor devices make them extremely vulnerable to cyberwarfare/cyberterrorism attacks. In this paper, we propose a reputation system enhanced with distributed agents, based on unsupervised learning algorithms (self-organizing maps), in order to achieve fault tolerance and enhanced resistance to previously unknown attacks.