This chapter reviews the evolution of the traditional internet into the Internet of Things (IoT). The characteristics and application of the IoT are also reviewed, together with its security concerns in terms of distributed denial of service attacks. The chapter further investigates the state-of-the-art in data mining techniques for Distributed Denial of Service (DDoS) attacks targeting the various infrastructures. The chapter explores the characteristics and pervasiveness of DDoS attacks. It also explores the motives, mechanisms and techniques used to execute a DDoS attack. The chapter further investigates the current data mining techniques that are used to combat and detect these attacks, their advantages and disadvantages are explored. Future direction of the research is also provided.
Reference:
Machaka, P. and Nelwamondo, F. 2016. Data mining techniques for distributed denial of service attacks detection in the internet of things: A research survey. In: Data Mining Trends and Applications in Criminal Science and Investigations. IGI Global: Hershey, Pennsylvania
Machaka, P., & Nelwamondo, F. V. (2016). Data mining techniques for distributed denial of service attacks detection in the internet of things: A research survey., Wokflow;17455 IGI Global. http://hdl.handle.net/10204/8919
Machaka, P, and Fulufhelo V Nelwamondo. "Data mining techniques for distributed denial of service attacks detection in the internet of things: A research survey" In WOKFLOW;17455, n.p.: IGI Global. 2016. http://hdl.handle.net/10204/8919.
Machaka P, Nelwamondo FV. Data mining techniques for distributed denial of service attacks detection in the internet of things: A research survey.. Wokflow;17455. [place unknown]: IGI Global; 2016. [cited yyyy month dd]. http://hdl.handle.net/10204/8919.
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