Electronic commerce plays an important role in the US economy. However, current electronic commerce applications such as online auction systems are not trustworthy due to a lack of effective trust management mechanisms. A trustworthy online auction system requires a dynamic trust management system that can detect abnormal bidding activities in real-time, notify the involved users, and cancel the corresponding auction immediately.
This project investigates an agent-based approach for dynamic trust management in online auctions. The approach supports real-time monitoring, analyzing, and detection of abnormal bidding behaviors in online auction systems so the trustworthiness of such systems can be ensured. Specific problems to be addressed in this project include 1) investigating efficient formal methods, such as model checking techniques, for analysis of real-time auction data; 2) defining a real-time trust model that supports trust re-evaluation; and 3) formulating intelligent agents that support reasoning with uncertainty and incomplete information. The research activities will result in a loosely coupled agent-based trust management (ATM) module in online auction systems. The project will have favorable broader impacts on trustworthy computing research, education, as well as industrial applications. The results from this project can help to develop trustworthy systems in electronic commerce, and will contribute to boost the US economy by providing a safe and trusted environment for Internet-based trading.
