With the advent of networking applications collecting user data on a massive scale, the privacy of individual users appears to be a major concern. The main challenge is the design of a solution that allows the data analyzer to compute global statistics over the set of individual inputs that are protected by some confidentiality mechanism. Joye et al. [7] recently suggested a solution that allow...

We argue that there will be an increasing future need for the design and implementation of declarative languages that can aggregate trust evidence and therefore inform the decision making of IT systems at run-time. We first present requirements for such languages. Then we discuss an instance of such a language, Peal, which extends an early prototype Peal that was researched by others in collabo...

I nternet applications have evolved from centralized and private computing platforms to distributed and collaborative networked computing systems. Collaboration is a fundamental Internet computing capability, and collaborative computing represents a significant step toward the continued promotion of openness and social intelligence as Internet systems and applications evolve. However, trust and...

Trust and distrust are two increasingly important metrics in social networks, reflecting users’ attitudes and relationships towards each other. In this paper, we study the indirect derivation of these metrics’ values for users that do not know each other, but are connected through the network. In particular, we study bilattice-based aggregation approaches and investigate how they can be improve...

This paper considers a distributed system of software agents who cooperate in helping their users to find services, provided by different agents. The agents need to ensure that the service providers they select are trustworthy. Because the agents are autonomous and there is no central trusted authority, the agents help each other determine the trustworthiness of the service providers they are i...

Data aggregation in wireless sensor networks (WSN) is a rapidly emerging research area. It can greatly help conserve the scarce energy resources by eliminating redundant data thus achieving a longer network lifetime. However, securing data aggregation in WSN is made even more challenging, by the fact that the sensor nodes and aggregators deployed in hostile environments are exposed to various s...

Fake news detection has become a significant topic based on the fast-spreading and detrimental effects of such news. Many methods deep neural networks learn clues from claim content message propagation structure or temporal information, which have been widely recognized. However, firstly, models ignore fact that information quality is uneven in propagation, makes semantic representations unreli...