Detection and Avoidance of Live DDoS Attack on Cloud Environment |
Author(s): |
| Prof. Rahul Desai , JSPMs BSIOTR wagholi,Pune; Kiran Sunil Salve, JSPMs BSIOTR wagholi,Pune; Asif Yunus Sayyad, JSPMs BSIOTR wagholi,Pune; Maruti Suresh Surwase, JSPMs BSIOTR wagholi,Pune; Akash Mahadeo Kunbithop, JSPMs BSIOTR wagholi,Pune |
Keywords: |
| Attack, Hadoop, Security, DDos, Mapreduce |
Abstract |
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Many systems use servers to manage and store their data, sometimes the servers are slowed down because of multiple user requests. Most of which are attackers or unauthorized users and some are genuine users. In computing, a denial-of-service (DoS) attack is an attempt to make a machine or network resource unavailable to its intended users. A distributed denial-of-service (DDoS) is where the attack source is more than one, often thousands of unique IP addresses. Flooding is one of the typical DDoS attacks that exploit normal TCP connections between a client and a target web server. In this project we are trying to devise a DDoS anomaly detection method on Hadoop that implements a Map Reduce-based detection algorithm against the Flooding attacks. |
Other Details |
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Paper ID: IJSRDV5I120249 Published in: Volume : 5, Issue : 12 Publication Date: 01/03/2018 Page(s): 425-427 |
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