Implementation of Internet of Things (IoT) Testbed with Distributed Denial of Services (DDoS) Attack Using Cyber Security
Keywords:Cyber security, Machine learning, intrusion detection system, malicious attack
Network security and data security are the greatest worries these days. Each association concludes their future business process in light of the past and everyday transactional data. This data may comprise of consumer's confidential data, which should be kept secure. Networks assume significant parts in current life, and cyber security has turned into an imperative exploration region. An Intrusion Detection System (IDS) which is a significant cyber security procedure, screens the condition of programming and equipment running in the network. Most methods utilized in the present IDS can't manage the dynamic and complex nature of cyber-attacks on computer networks. To tackle the above issues, numerous specialists have focused on developing IDSs that gain by machine learning strategies. Machine learning strategies can consequently find the fundamental distinctions between ordinary data and strange data with high precision. In addition, machine learning techniques have solid generalizability, so they are likewise ready to distinguish malicious attacks.
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Copyright (c) 2022 Divya Bheema Naik, Neha Gantagowdanahalli Ramegowda, Nisha Suresh, Pooja Raju, Tanushree Rajshekar
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