Calculating and Aggregating Direct Trust and Reputation in Organic Computing Systems

The growing complexity of current computer systems requires a high amount of administration, which poses an increasingly challenging task for manual administration. The Autonomic and Organic Computing Initiatives have introduced so called self-x properties, including self-configuration, self-optimization, self-healing, and self-protection, to allow administration to become autonomous. Although research in this area revealed promising results, it expects all participants to further the system goal, i.e, their benevolence is assumed. In open systems, where arbitrary participants can join the systems, this benevolence assumption must be dropped, since such a participant may act maliciously and try to exploit the system. This introduces a not yet considered uncertainty, which needs to be addressed. In human society, trust relations are used to lower the uncertainty of transactions with unknown interaction partners. Trust is based on past experiences with someone, as well as recommendations of trusted third parties. In this work trust metrics for direct trust, reputation, confidence, and an aggregation of them are presented. While the presented metrics were primarily designed to improve the self-x properties of OC systems they can also be used by applications in Multi-Agent-Systems to evaluate the behavior of other agents. Direct trust is calculated by the Delayed-Ack metric, that assesses the reliability of nodes in Organic Computing systems. The other metrics are general enough to be used with all kinds of contexts and facets to cover any kind of trust requirements of a system, as long as corresponding direct trust values exist. These metrics include reputation (Neighbor-Trust), confidence, and an aggregation of them. Evaluations based on an Automated Design Space Exploration are conducted to find the best configurations for each metric, especially to identify the importance of direct trust, reputation, and confidence for the total trust value. They illustrate, that reputation, i.e., the recommendations of others, is an important aspect to evaluate the trustworthiness of an interaction partner. In addition, it is shown that a gradual change of priority from reputation to direct trust is preferable instead of a sudden switch when enough confidence in the correctness of ones own experiences is accumulated. All evaluations focus on systems with volatile behavior, i.e., system participants change their behavior over time. In such a system, the ability to adapt fast to behavior changes has turned out to be the most important parameter.