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Anomaly Detection for Internet of Things Cyberattacks

Computers, Materials & Continua 2022年第7期72卷 261-279页

作者： manal alanazi Ahamed Aljuhani College of Computing and Information Technology University of TabukTabuk71491Saudi Arabia

The Internet of Things(IoT)has been deployed in diverse critical sectors with the aim of improving quality of service and facilitating human *** IoT revolution has redefined digital services in different domains by improving efficiency,productivity,and *** service providers have adapted IoT systems or plan to integrate them as integral parts of their systems’operation;however,IoT security issues remain a significant *** minimize the risk of cyberattacks on IoT networks,anomaly detection based on machine learning can be an effective security solution to overcome a wide range of IoT *** various detection techniques have been proposed in the literature,existing detection methods address limited cyberattacks and utilize outdated datasets for *** this paper,we propose an intelligent,effective,and lightweight detection approach to detect several IoT *** proposed model includes a collaborative feature selection method that selects the best distinctive features and eliminates unnecessary features to build an effective and efficient detection *** the detection phase,we also proposed an ensemble of learning techniques to improve classification for predicting several different types of IoT *** experimental results show that our proposed method can effectively and efficiently predict several IoT attacks with a higher accuracy rate of 99.984%,a precision rate of 99.982%,a recall rate of 99.984%,and an F1-score of 99.983%.

关键词： Anomaly detection anomaly-based IDS cybersecurity feature selection Internet of Things(IoT) intrusion detection

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