Detection of attacks in the Internet of Things with the feature selection approach based on the whale optimization algorithm and learning by majority voting
Abstract:Penetration into the Internet of Things network is a challenge in the security of new-generation networks and smart cities. In most cases, malware is distributed in the Internet of Things and smart objects are infected by malware. Objects infected with malware or viruses, which are called botnets, perform attacks such as DDoS against network services. DDoS attacks make network services inaccessible to users. A suitable approach to detect attacks based on malware and botnet is to use intelligent and distributed… Show more
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