Title: Security situation prediction of artificial intelligence network based on wireless sensor

Authors: Wenxi Han

Addresses: Yunnan Power Grid Power Dispatching and Control Center, Dianchi Road, Xishan District, Kunming City, Yunnan Province, China

Abstract: The security situational prediction aims to assess the present state of network security, forecast its future development trends, inform individuals to implement appropriate defensive measures and secure the network environment by analysing and extracting wireless sensor network (WSN) data. This study proposed a multilayer perceptron feed forward neural network model in WSN (MPFNN-WSN) that relies on accurate forecasting and mitigating security prediction of AI networks. The study offers multilayer perceptron networks for attack detection and network security prediction systems for hacker identification and threat level. This new AI-powered wireless measurement system has revolutionised data analysis by adding new computing and analysing capabilities to existing innovations. According to experiments that compared it to state-of-the-art evolutionary methods, the strategy considerably reduced root-mean-squared errors (RMSEs) and accuracy for different test sets. Results are better with the proposed method when contrasted with the industry standard.

Keywords: artificial intelligence; wireless sensor networks; WSNs; deep fuzzy neural networks; security prediction; root-mean-squared error; RMSE.

DOI: 10.1504/IJIIDS.2025.145495

International Journal of Intelligent Information and Database Systems, 2025 Vol.17 No.2, pp.217 - 235

Received: 15 May 2024
Accepted: 15 Aug 2024
Published online: 01 Apr 2025 *

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