How to trust a few among many

Abstract

The presence of numerous and disparate information sources available to support decision-making calls for efficient methods of harnessing their potential. Information sources may be unreliable, and misleading reports can affect decisions. Existing trust and reputation mechanisms typically rely on reports from as many sources as possible to mitigate the influence of misleading reports on decisions. In the real world, however, it is often the case that querying information sources can be costly in terms of energy, bandwidth, delay overheads, and other constraints. We present a model of source selection and fusion in resource-constrained environments, where there is uncertainty regarding the trustworthiness of sources. We exploit diversity among sources to stratify them into homogeneous subgroups to both minimise redundant sampling and mitigate the effect of certain biases. Through controlled experiments, we demonstrate that a diversity-based approach is robust to biases introduced due to dependencies among source reports, performs significantly better than existing approaches when sampling budget is limited and equally as good with an unlimited budget.

A constructive airborne‐ground matrix algorithm for modern telecommunication systems

“…Situation awareness should be notified every 2–5 min about the surrounding environment to guide the mobile force to safety. In the real‐world scenario, queuing information from various sources can often be costly regarding bandwidth, energy, delay overhead, and other communication constraints [14]. Thus, the network connectivity should be stable at all costs.…”

Budget Limited Trust-Aware Decision Making

“…They do not, however, consider the process of acquiring witness information, or the costs associated with this. In other recent research, strategies for acquiring witness information within cost constraints have been explored that are robust to biases in reports due to effects such as hearsay evidence [8]. This research focusses exclusively on the trust assessment and information fusion problem, however, eschewing the question of deciding who to trust.…”