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- W4313444917 abstract "In diverse areas, the wireless sensor network (WSN) has an important role to play and has its application in various domains. Even though WSN has become very popular in recent times but is also vulnerable to several security threats. The Denial of Service (DoS) attacks and their variant, Distributed Denial of Services (DDoS) attacks are the most commonly observed attacks in WSN. The DoS attacks can hamper the normal functioning of a WSN by repeatedly flooding the communication channel of a sensor node with request messages by attackers to deprive the network of essential services and applications. Therefore, robust techniques to detect DoS attacks in WSNs need to be developed and investigated. Attack detection schemes using machine learning techniques will be a highly promising area of research. A review of several DoS attack detection schemes in WSN using machine learning has been reviewed and presented in the paper." @default.
- W4313444917 created "2023-01-06" @default.
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- W4313444917 date "2023-01-01" @default.
- W4313444917 modified "2023-10-16" @default.
- W4313444917 title "Machine Learning-Based DoS Attack Detection Techniques in Wireless Sensor Network: A Review" @default.
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- W4313444917 doi "https://doi.org/10.1007/978-981-19-2358-6_53" @default.
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