“IoT Botnet Attack Detection Using Big Data...

“IoT Botnet Attack Detection Using Big Data Analytics”

Author Name : Sridharsni S, Rohan Chopra, Rutuja Patil, Jatavallabhula Sai Jagadeeshwar, Dominic Thirshatha Thirukumar, Dhamini Devaraj

ABSTRACT Botnets are becoming one of the most severe threats to the Internet and network security. The increasing potential of detecting suspicious Internet activities oriented the attackers to a different and complicated line of attack. Bots are zombie computers, vaguely controlled by a malicious body, and are used for attacks, spam, phishing and information retrieval. Internet of Things (IoT) devices has been the primary force behind the biggest distributed denial of service (DDoS) botnet attacks for some time. It’s a threat that has never really diminished, as numerous IoT device manufacturers continue to ship products that cannot be properly secured. . Many security weaknesses still exist on the IoT devices because most of them have not enough memory and computational resources for robust security mechanisms. Moreover, Many existing rule-based detection systems can be circumvented by attackers. Botnet research is mostly performed to detect and prevent bot activities. Detecting a botnet often needs advanced analyzing capabilities which are related to the selected data for analysis track and the characteristics of issues performed. In this project, we will apply different algorithms for botnet prediction using big data and Spark.