Anastasios Drosou

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This paper introduces activity-related behavioural features that can be automatically extracted from a computer system, with the aim to increase the effectiveness of automatic stress detection. The proposed features are based on processing of appropriate video and accelerometer recordings taken from the monitored subjects. For the purposes of the present(More)
Keywords: Activity detection Biometrics Behavioral biometrics Activity related authentication HMM Anthropometric profile Attributed graph matching Motion analysis Body tracking a b s t r a c t This paper presents a novel framework for unobtrusive biometric authentication based on the spatiotem-poral analysis of human activities. Initially, the subject's(More)
This paper presents the nondestructive stratigraphy determination through the use of UV/VIS/nIR spectroscopy. The UV/VIS/nIR backscattered light through a multilayered structure, such as the paint layers of artworks, is simulated. The device used to produce and measure the backscattered light, is the Perkin-Elmer Lambda 900 UV/VIS/nIR spectrophotometer(More)
his paper presents a novel framework for dynamic activity-related user authentication utilizing dynamic and static anthropometric information. The recognition of the performed activity is based on Radon transforms that are applied on spatiotemporal motion templates. User authentication is performed exploiting the behavioural variations between different(More)
Unobtrusive Authentication Using ACTIvity-Related and Soft BIOmetrics (ACTIBIO) is an EU Specific Targeted Research Project (STREP) where new types of biometrics are combined with state-of-the-art unobtrusive technologies in order to enhance security in a wide spectrum of applications. The project aims to develop a modular, robust, multimodal biometrics(More)
Mobile devices are evolving and becoming increasingly popular over the last few years. This growth, however, has exposed mobile devices to a large number of security threats. Malware installed in smartphones can be used for a variety of malicious purposes, including stealing personal data, sending spam SMSs, and launching Denial of Service (DoS) attacks(More)
This letter presents a novel probabilistic framework for augmenting the recognition performance of biometric systems with information from continuous soft biometric (SB) traits. In particular, by modelling the systematic error induced by the estimation of the SB traits, a modified efficient recognition probability can be extracted including information(More)