Distributed sensing systems, especially Wireless Sensor Networks (WSNs), are highly vulnerable to compromise. Trust and reputation management systems have been proven to be effective in solving many security issues in WSNs. Trust initialization is however challenging, as there are no historical interactions to provide information to help reach valid conclusions during the initialization phase of the reputation management system. An automated evaluation technique to estimate the initial reputation of nodes within a system is needed, using assessment techniques to evaluate each component on its inherent trustworthiness or risk, with respect to the system. To address these issues, IAI and its collaborator, Argon ST, have been awarded a contract entitled, “Bayesian-based Trust Initialization for Reputation Management in Wireless Sensor Networks.” An effective Trust Initialization Mechanism (T-INIT) based on Bayesian Fusion for evaluating the initial trustworthy of WSNs. Existing trust initialization strategy will be improved by taking a set of context parameters into consideration. The final target is to build an advanced trust initialization strategy, which is integrated with existing reputation and trust management systems, so that the warm-up period can be successfully minimized. This will take full advantage of the trust and reputation management system and reduce the time that the system is vulnerable. This technology also has commercial applications in large-scale networked devices for ubiquitous computing applications that use reputation services to identify and isolate misbehaving nodes.