Analysis of DDoS Attacks using Datamining

Recent technological advancements have ushered in an era characterized by the continuous generation, processing, and sharing of huge amounts of data globally. This has significantly enhanced communication and connectivity through various devices such as Personal Computers, mobile phones, apps, and w...

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Bibliographic Details
Published in:	2023 6th International Conference on Advances in Science and Technology (ICAST) pp. 552 - 557
Main Authors:	Kinny, Seadon, Maman, Bijith B, Mhapsekar, Walter, Waghmare, Sarthak, Kiruthika, M
Format:	Conference Proceeding
Language:	English
Published:	IEEE 08-12-2023
Subjects:	analysis Computer crime datamining DDoS Denial-of-service attack Floods networks Servers Software defined networking Strain Surges traffic
Online Access:	Get full text
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Summary:	Recent technological advancements have ushered in an era characterized by the continuous generation, processing, and sharing of huge amounts of data globally. This has significantly enhanced communication and connectivity through various devices such as Personal Computers, mobile phones, apps, and websites. With the escalating number of users, the corresponding increase in data production has resulted in a surge in internet traffic, giving rise to numerous challenges. One prominent challenge is the threat of Distributed Denial of Service (DDoS) attacks, wherein malicious actors can disturb the normal flow of traffic to a targeted server, service, or network by inundating it with a deluge of Internet traffic. In this paper a system is proposed that employs data mining techniques to analyze packet header files and identify DDoS attacks, specifically focusing on SYN flood attacks.
DOI:	10.1109/ICAST59062.2023.10454909