Federated Blockchain Model for Cyber Intrusion Analysis in Smart Grid Networks
نویسندگان
چکیده
Smart internet of things (IoT) devices are used to manage domestic and industrial energy needs using sustainable renewable sources. Due cyber infiltration a lack transparency, the traditional transaction process is inefficient, unsafe expensive. grid systems now efficient, safe transparent owing development blockchain (BC) technology its smart contract (SC) solution. In this study, federated learning extreme gradient boosting (FL-XGB) framework has been developed along with BC learn intrusion inside system. FL best suited for decentralized BC-enabled system adapt models trustworthy reliable transactions. Many features attributes Third International Knowledge Discovery Data mining Tools Competition (KDD Cup 1999) dataset have in study perform experimental analysis. The likelihood intrusions network mathematically stated. participant nodes run based FL-Smart Contract algorithms detect intrusions. provided aggregated results from experiment that was 99% accurate predicting intrusion. experimentally determined block storage gain retrieval were 97.5% 95.4% respectively. evaluated, data indicated there 1.2% illegal access. Moreover, system’s accuracy, intrusions, legal access processing times considered comparison. proposed outperformed contemporary research-developed targeted same application. Therefore, provides guaranteed secure grids.
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ژورنال
عنوان ژورنال: Intelligent Automation and Soft Computing
سال: 2023
ISSN: ['2326-005X', '1079-8587']
DOI: https://doi.org/10.32604/iasc.2023.034381