Reputation-Based Trust for a Cooperative, Agent-Based Backup Protection Scheme for Power Networks

This thesis research explores integrating a reputation-based trust mechanism with an agent-based backup protection system to improve the performance of traditional backup relay methods that are currently in use in power transmission systems. Integrating agent technology into relay protection schemes has been previously proposed to clear faults more rapidly and to add precision by enabling the use of adaptive protection methods. A distributed, cooperative trust system such as that used in peer-to-peer file sharing networks has the potential to add an additional layer of defense in a protection system designed to operate with greater autonomy. This trust component enables agents in the system to make assessments using additional, behavioral-based analysis of cooperating protection agents. Simulation results illustrate the improved decision-making capability achieved by incorporating this cooperative trust method when experiencing abnormal or malicious communications. The integration of this additional trust component provides an added push for implementing the proposed agent-based protection schemes to help mitigate the impact from wide-area disturbances and the cascading blackouts that often follow. As the push for electric grid modernization continues, an agent-based trust system including this type of behavioral-based analysis will also benefit other smart components connecting critical grid control and monitoring information systems

SMART: A Subspace based Malicious Peers Detection algorithm for P2P Systems

In recent years, reputation management schemes have been proposed as promising solutions to alleviate the blindness during peer selection in distributed P2P environment where malicious peers coexist with honest ones. They indeed provide incentives for peers to contribute more resources to the system and thus promote the whole system performance. But few of them have been implemented practically since they still suffer from various security threats, such as collusion, Sybil attack and so on. Therefore, how to detect malicious peers plays a critical role in the successful work of these mechanisms, and it will also be our focus in this paper. Firstly, we define malicious peers and show their influence on the system performance. Secondly, based on Multiscale Principal Component Analysis (MSPCA) and control chart, a Subspace based MAlicious peeRs deTecting algorithm (SMART) is brought forward. SMART first reconstructs the original reputation matrix based on subspace method, and then finds malicious peers out based on Shewhart control chart. Finally, simulation results indicate that SMART can detect malicious peers efficiently and accurately

A game theoretic model for digital identity and trust in online communities

Digital identity and trust management mechanisms play an important role on the Internet. They help users make decisions on trustworthiness of digital identities in online communities or ecommerce environments, which have significant security consequences. This work aims to contribute to construction of an analytical foundation for digital identity and trust by adopting a quantitative approach. A game theoretic model is developed to quantify community effects and other factors in trust decisions. The model captures factors such as peer pressure and personality traits. The existence and uniqueness of a Nash equilibrium solution is studied and shown for the trust game defined. In addition, synchronous and asynchronous update algorithms are shown to converge to the Nash equilibrium solution. A numerical analysis is provided for a number of scenarios that illustrate the interplay between user behavior and community effects