Information Accountability Framework for a Trusted Health Care System

Trusted health care outcomes are patient centric. Requirements to ensure both the quality and sharing of patients’ health records are a key for better clinical decision making. In the context of maintaining quality health, the sharing of data and information between professionals and patients is paramount. This information sharing is a challenge and costly if patients’ trust and institutional accountability are not established. Establishment of an Information Accountability Framework (IAF) is one of the approaches in this paper. The concept behind the IAF requirements are: transparent responsibilities, relevance of the information being used, and the establishment and evidence of accountability that all lead to the desired outcome of a Trusted Health Care System. Upon completion of this IAF framework the trust component between the public and professionals will be constructed. Preservation of the confidentiality and integrity of patients’ information will lead to trusted health care outcomes

A Survey on Wireless Sensor Network Security

Wireless sensor networks (WSNs) have recently attracted a lot of interest in the research community due their wide range of applications. Due to distributed nature of these networks and their deployment in remote areas, these networks are vulnerable to numerous security threats that can adversely affect their proper functioning. This problem is more critical if the network is deployed for some mission-critical applications such as in a tactical battlefield. Random failure of nodes is also very likely in real-life deployment scenarios. Due to resource constraints in the sensor nodes, traditional security mechanisms with large overhead of computation and communication are infeasible in WSNs. Security in sensor networks is, therefore, a particularly challenging task. This paper discusses the current state of the art in security mechanisms for WSNs. Various types of attacks are discussed and their countermeasures presented. A brief discussion on the future direction of research in WSN security is also included.Comment: 24 pages, 4 figures, 2 table

A Formal Framework for Modeling Trust and Reputation in Collective Adaptive Systems

Trust and reputation models for distributed, collaborative systems have been studied and applied in several domains, in order to stimulate cooperation while preventing selfish and malicious behaviors. Nonetheless, such models have received less attention in the process of specifying and analyzing formally the functionalities of the systems mentioned above. The objective of this paper is to define a process algebraic framework for the modeling of systems that use (i) trust and reputation to govern the interactions among nodes, and (ii) communication models characterized by a high level of adaptiveness and flexibility. Hence, we propose a formalism for verifying, through model checking techniques, the robustness of these systems with respect to the typical attacks conducted against webs of trust.Comment: In Proceedings FORECAST 2016, arXiv:1607.0200

Privacy Implications of In-Network Aggregation Mechanisms for VANETs

Research on vehicular ad hoc networks (VANETs) is active and ongoing. Proposed applications range from safety applications, and traffic efficiency applications to entertainment applications. Common to many applications is the need to disseminate possibly privacy-sensitive information, such as location and speed information, over larger distances. In-network aggregation is a promising technology that can help to make such privacy-sensitive information only available in the direct vicinity of vehicles instead of communicating it over larger areas. Further away, only aggregated information that is not privacy-relevant anymore will be known. At the same time, aggregation mechanisms help to cope with the limited available wireless bandwidth. However, the exact privacy properties of aggregation mechanisms have still not been thoroughly researched. In this paper, we propose a metric to measure privacy enhancements provided by in-network aggregation and use it to compare existing schemes