# A Secure Clustering Protocol with Fuzzy Trust Evaluation and Outlier Detection for Industrial Wireless Sensor Networks

arXiv: https://arxiv.org/abs/2207.09936 · HTML: https://mlsanity.com/paper/2207.09936/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 29 references that are in the map.
- First posted on arXiv 20 Jul 2022.

## Builds on (most cited first, 1 of 1)

- [Recommendations on Designing Practical Interval Type-2 Fuzzy Systems](https://mlsanity.com/paper/1907.01697/) (2019)

## Built on by (most cited first, 2 of 2)

- [Generative Adversarial Learning for Trusted and Secure Clustering in Industrial Wireless Sensor Networks](https://mlsanity.com/paper/2210.07707/) (2022)
- [Generative Adversarial Learning for Intelligent Trust Management in 6G Wireless Networks](https://mlsanity.com/paper/2208.01221/) (2022)

## Abstract (arXiv)

Security is one of the major concerns in Industrial Wireless Sensor Networks (IWSNs). To assure the security in clustered IWSNs, this paper presents a secure clustering protocol with fuzzy trust evaluation and outlier detection (SCFTO). Firstly, to deal with the transmission uncertainty in an open wireless medium, an interval type-2 fuzzy logic controller is adopted to estimate the trusts. And then a density based outlier detection mechanism is introduced to acquire an adaptive trust threshold used to isolate the malicious nodes from being cluster heads. Finally, a fuzzy based cluster heads election method is proposed to achieve a balance between energy saving and security assurance, so that a normal sensor node with more residual energy or less confidence on other nodes has higher probability to be the cluster head. Extensive experiments verify that our secure clustering protocol can effectively defend the network against attacks from internal malicious or compromised nodes.