INSERM/Reacting, the French Ebola Task Force, and Institut de Recherche pour le Développement.

Decentralized applications are composed of distributed entities that directly interact with each other and make local autonomous decisions in the absence of a centralized coordinating authority. Such decentralized applications, where entities can join and leave the system at any time, are particularly susceptible to the attacks of malicious entities. Each entity therefore requires protective measures to safeguard itself against these entities. Trust management solutions serve to provide effective protective measures against such malicious attacks. Trust relationships help an entity model and evaluate its confidence in other entities towards securing itself. Trust management is, thus, both an essential and intrinsic ingredient of decentralized applications. However, research in trust management has not focused on how trust models can be composed into a decentralized architecture. The PACE architectural style, described previously [21], provides structured and detailed guidance on the assimilation of trust models into a decentralized entity's architecture. In this paper, we describe our experiments with incorporating four different reputation-based trust models into a decentralized application using the PACE architectural style. Our observations lead us to conclude that PACE not only provides an effective and easy way to integrate trust management into decentralized applications, but also facilitates reuse while supporting different types of trust models. Additionally, PACE serves as a suitable platform to aid the evaluation and comparison of trust models in a fixed setting towards providing a way to choose an appropriate model for the setting.

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Abstract. Middleware for pervasive spaces has to meet conflicting requirements. It has to both maximize the utility of the information exposed and ensure that this information does not violate users' privacy. In order to resolve these conflicts, we propose a framework grounded in utility theory where users dynamically control the level of disclosure about their information. We begin by providing appropriate definitions of privacy and utility for the type of applications that would support collaborative work in an office environment-current definitions of privacy and anonymity do not apply in this context. We propose a distributed solution that, given a user's background knowledge, maximizes the utility of the information being disclosed to information recipients while meeting the privacy requirements of users. We implement our solution in the context of a real pervasive space middleware and provide experiments that demonstrate its behaviour.

ObjectivesDisruption in HIV care provision may enhance the development and spread of drug resistance due to inadequate antiretroviral therapy. This study thus determined the prevalence of HIV-1 transmitted drug resistance (TDR) in settings of decentralized therapy and care in Senegal and, the Ebola outbreak in Guinea. Antiretroviral-naïve patients were enrolled following a modified WHO TDR Threshold Survey method, implemented in Senegal (January–March 2015) and Guinea (August–September 2015). Plasma and dried blood spots specimens, respectively from Senegalese (n = 69) and Guinean (n = 50) patients, were collected for direct sequencing of HIV-1 pol genes. The Stanford Calibrated Population Resistance program v6.0 was used for Surveillance Drug Resistance Mutations (SDRMs).ResultsGenotyping was successful from 54/69 (78.2%) and 31/50 (62.0%) isolates. In Senegal, TDR prevalence was 0% (mean duration since HIV diagnosis 4.08 ± 3.53 years). In Guinea, two patients exhibited SDRMs M184V (NRTI), T215F (TAM) and, G190A (NNRTI), respectively. TDR prevalence at this second site, however, could not be ascertained because of low sample size. Phylogenetic inference confirmed CRF02_AG predominance in Senegal (62.96%) and Guinea (77.42%). TDR prevalence in Senegal remains extremely low suggesting improved control measures. Continuous surveillance in both settings is mandatory and, should be done closest to diagnosis/transmission time and with larger sample size.