# A Trust Management and Misbehaviour Detection Mechanism for Multi-Agent Systems and its Application to Intelligent Transportation Systems

## TL;DR

This paper introduces a trust management mechanism based on subjective logic for multi-agent systems, enhancing data reliability and misbehavior detection, with successful application to intelligent transportation systems in simulation.

## Contribution

It proposes a novel subjective logic-based trust mechanism that fuses data, detects, and isolates malicious agents in multi-agent systems, specifically applied to intelligent transportation systems.

## Key findings

- Mechanism scales well with system size
- Efficient detection and isolation of misbehaving agents
- Successful simulation results in ITS context

## Abstract

Cooperative information shared among a multi-agent system (MAS) can be useful to agents to efficiently fulfill their missions. Relying on wrong information, however, can have severe consequences. While classical approaches only consider measurement uncertainty, reliability information on the incoming data can be useful for decision making. In this work, a subjective logic based mechanism is proposed that amends reliability information to the data shared among the MAS. If multiple agents report the same event, their information is fused. In order to maintain high reliability, the mechanism detects and isolates misbehaving agents. Therefore, an attacker model is specified that includes faulty as well as malicious agents. The mechanism is applied to Intelligent Transportation Systems (ITS) and it is shown in simulation that the approach scales well with the size of the MAS and that it is able to efficiently detected and isolated misbehaving agents. Keywords: Multi-agent systems, Fault Detection, Sensor/data fusion, Control Applications