Júlio da Silva Dias

COLLEGA middleware for the management of participatory Mobile Health Communities

Recent advancements in wireless technologies and the widespread availability of smartphones equipped with several physical and virtual sensors are leading to the emergence of novel mobile healthcare scenarios where patients with critical physical/behavioral conditions can be provided with anywhere and anytime care assistance even while on the move. Crowdsensing, through the massive use of smartphone sensors further enhances the potential of supporting participatory management of emergency scenarios. This paper presents a macro process modelling of crowdsourced-based participatory emergency scenarios and, accordingly, proposes a crowdsensing-based middleware called COLLEGA that provides comprehensive management functionalities for supporting prompt assistance in case of a medical emergency. In particular, through participatory and opportunistic sensing, the COLLEGA framework allows dynamic formation of ad-hoc assistance groups formed by passing-by users capable of assisting mobile patients in need of help while waiting for professional caregivers and provides support for understanding the emergency situation and effectively planning and executing assistance actions.

Privacy information in a positive credit system

A positive credit history and rating help consumers with good payment history to get lower interest rates, greater flexibility for credit, as well as loans with longer payment terms. In order to establish credit profiles, there is a need to get information (e.g. spending patterns) from the consumers and from the companies that are selling related goods. The problem is how to share private information about customers and companies without compromising the secrecy and confidentiality of such information. In this work, we propose a cryptographic protocol to share sensitive information while preserving the privacy of the customer as well as the information of the commercial institution. Furthermore, we analyse the proposed protocol by using Petri nets to verify the absence of livelocks, deadlocks, and other anomalies in the protocol.

Sharing Privacy Information in Credit Analysis Environment

Credit analysis is used by financial companies to grant credit to customers. The analysis is expensive, bureaucratic, and requires the collection of customer personal information. However, shopping malls are selling goods in several installments and need a simple, fast, and cheap process to grant credit to their customers. One way to improve the efficiency of this process is to facilitate the sharing of private information from customers and stores. The challenge here is how to share private information without disclosing the identity of its owner. Here we propose a protocol to share information while preserving the privacy of the customer as well as the information of the commercial institution.