Bruno Augusti Mozzaquatro

Applying Pervasive Computing in an Architecture for Homecare Environments

Every year the queues in publics and privates hospitals grows due to, among others, the increasing of the world population and the delay in the patients attendance. This is a serious problem faced by administrators of hospitals whose believe that it is increasingly difficult to offer quality service to those who search for it. One of the ways to decrease these queues is through the development of homecare systems that ensure the patient to receive the clinic treatment directly in his house. These kind of systems would help to decrease the queues and consequently, would improve the attendance of those who goes to the hospitals looking for assistance. Considering this, we present in this paper the modelling of an architecture for pervasive systems to be applied in homecare environments. The pervasive systems developed from this modelling aim to improve the services provided by healthcare professionals in the treatment of patients that are located in their houses. The architecture uses concepts of pervasive computing to provide access to information anytime and wherever the user is, once a homecare environment has a high level of dynamicity of the involved. The knowledge representation of the environment needed in the modelling of the architecture is made through ontologies due to the possibility of reuse of the information stored, as well as the interoperability of information among different computational devices.

URL query string anomaly sensor designed with the bidimensional Haar wavelet transform

In this paper, the 2D Haar wavelet transform is the proposed analysis technique for HTTP traffic data. Web attacks are detected by two threshold operations applied to the wavelet coefficients of the 2D transform: one based on their median and the other on the best approximation method. The two proposed algorithms are validated through an extensive number of simulations, including comparisons with well-established techniques, confirming the effectiveness of the designed sensor.

OntoHealth: a system to process ontologies applied to health pervasive environment

In the last years ontologies are being used in the development of pervasive computing applications. It is habitual their use for facilitating the interoperability among context-aware applications and the entities that may enter in the context at any time. This paper presents OntoHealth: a system to process ontologies applied to health pervasive environment. The main idea is that a hospital could be seen as this pervasive environment, where someone, through ubiquitous computing, engages a range of computational devices and systems simultaneously, in the course of ordinary activities, and may not necessarily even be aware that they are doing so. With the proposed ontology and the tool for its processing, the medical tasks can be shared by all components of this pervasive environment.

An approach to automatic customization of user interfaces for mobile devices in pervasive environments

This paper presents the PIDIM architecture in order to assist in the customization of user interfaces for mobile devices in pervasive environments. This architecture uses concepts of Pervasive Computing and represents data on the users profile, so that adaptation of the interfaces is entirely focused on the end user. The knowledge representation about the user profile is done through ontologies due to the possibility of reuse of stored information. In order to validate and demonstrate the flow of operation of the proposed approach is presented a case study, which has as scenario the adaptation of user interfaces when it is in motion.

DoS attack detection using a two dimensional wavelet transform

The analysis of network traffic is a key area for the management of fault-tolerant systems, since anomalies in network traffic can affect the availability and quality of service (QoS). This work proposes an intrusion detection tool based on the two-dimensional wavelet transform to quickly and effectively detect anomalies in computer networks generated by denial of service (DoS). Experiments were performed using two databases: a synthetic (DARPA) and another one from data collected at the Federal University of Santa Maria (UFSM), allowing analysis of the intrusion detection tool under different scenarios. The wavelets considered for the tests were all from the orthonormal family of Daubechies: Haar (Db1), Db2, Db4 and Db8 (with 1, 2, 4 and 8 null vanishing moments respectively). For the DARPA database we obtained a detection rate up to 100% and 95% for the UFSM database.