Automated Machine Learning Enabled Cybersecurity Threat Detection in Internet of Things Environment

Recently, Internet of Things (IoT) devices produces massive quantity data from distinct sources that get transmitted over public networks. Cybersecurity becomes a challenging issue in the IoT environment where existence cyber threats needs to be resolved. The development automated tools for threat detection and classification using machine learning (ML) artificial intelligence (AI) become essential accomplish security environment. It is needed minimize issues related gadgets effectively. Therefore, this article introduces new Mayfly optimization (MFO) with regularized extreme (RELM) model, named MFO-RELM Threat Detection presented technique accomplishes effectual identification cybersecurity exist For accomplishing this, model pre-processes actual into meaningful format. In addition, RELM receives pre-processed carries out process. order boost performance MFO algorithm has been employed it. validation tested standard datasets results highlighted better outcomes under aspects.