Detection of Distributed Denial of Service Attack in an Internet of Things Environment -A Review
I. Varalakshmi, M. Thenmozhi, R. Sasi
Abstract
Internet of Things (IoT) is a dominant platform in the last decade ; the devices are connected and communicated through sensors/actuators in IoT network. IoT makes the users life simpler and smarter. In IoT network securing the data is a challenging one for the researchers. Communication takes place in decentralization nature and data’s shared among millions of devices , makes the hackers to attack the network /data easily by injecting various bots , virus , ransomware , DoS, Mirai botnet , DDoS etc., This paper provides a detailed review on challenges , issues , techniques and protocols that are applied to detect and Distributed Denial of Service (DDoS ) attacks in the IoT environment. DDoS attack is a severe attack caused so far in the world , that crashes many servers, blocks network traffic and reduce its speed drastically by deluging surplus TCP, UDP flooding SYN attack. In DDoS attack, the attacker binds a number of internet dependent devices into a group called botnet and then for an assured period of time makes synchronized requests to a server , crashing the server and making it disregard to legitimate user ’s request. Various technologies like Machine Learning , Deep Learning , Block chain and Cyber security which have been applied by the researchers for handling DDoS attack has been reviewed in this paper.