The adoption of socio- and bio-inspired algorithms for trust models in wireless sensor networks: A survey

摘要

The security of a wireless sensor network is greatly increased with increasing levels of trustworthiness of nodes on the network. There are a number of trust models proposed that use various trust evaluation methods. The paper categorises trust evaluation methods for wireless sensor networks into socio-inspired, bio-inspired, and analytical methods. Biologically inspired methods and socio constructs are rarely used in the design of trust schemes as opposed to analytical methods (probability, agent based, fuzzy, etc). The paper discusses existing bio- and socio-inspired-based trust schemes implemented for wireless sensor networks, viz quality-based distance vector protocol, enhanced bio-inspired trust and reputation model for wireless sensor network, bio-inspired trust routing protocol, machine learning-based bio-inspired trust and reputation model, socio-psychological trust and reputation model, and finally reputation framework for sensor network. The contributions, trust evaluation methods and limitations of recent trust models (i.e. analytical based, biological and socio-inspired models) are discussed in this paper. The pros and cons of analytical, socio, and biologically inspired algorithms for computing are outlined to easily ascertain the relevance of adopting either biological or socio-inspired approaches for solving trust-related problems in wireless sensor networks.