The integrity of messages in vehicular ad-hoc networks has been extensively studied by the research community, resulting in the IEEE&#126;1609.2 standard, which provides typical integrity guarantees. However, the correctness of message contents is still one of the main challenges of applying dependable and secure vehicular ad-hoc networks. One important use case is the validity of position information contained in messages: position verification mechanisms have been proposed in the literature to provide this functionality. A more general approach to validate such information is by applying misbehavior detection mechanisms. In this paper, we consider misbehavior detection by enhancing two position verification mechanisms and fusing their results in a generalized framework using subjective logic. We conduct extensive simulations using VEINS to study the impact of traffic density, as well as several types of attackers and fractions of attackers on our mechanisms. The obtained results show the proposed framework can validate position information as effectively as existing approaches in the literature, without tailoring the framework specifically for this use case.
Subjective logic @cite_6 is a framework for probabilistic information fusion, which is capable of representing not just a probabilistic truth value, but also a measure of uncertainty. It is similar to the more well-known Dempster-Shafer Theory, with the advantage that it integrates uncertainty directly, rather than adding it as a separate component. This has the advantage that fusion becomes easier. Subjective logic expresses the truth value of a statement through so-called opinions @math , which consist of a belief, disbelief, uncertainty and base rate. An intuitive interpretation is that belief is the probability that the statement is true, disbelief is the probability that it is false, and uncertainty represents the confidence in this evaluation. The base rate expresses the probability in the absence of evidence, which in this paper is assumed to be @math . An opinion can be converted into a prediction by computing the expectation, @math . Opinions are usually held by subjects about objects: for example, several detection mechanisms (subjects) can have different opinions about an object (a new packet). Subjective logic provides operators to fuse the opinions of these detectors with certain constraints.
@cite_6
2110689325
We first describe a metric for uncertain probabilities called opinion, and subsequently a set of logical operators that can be used for logical reasoning with uncertain propositions. This framework which is called subjective logic uses elements from the Dempster-Shafer belief theory and we show that it is compatible with binary logic and probability calculus.