Effective Detection and Prevention of Ddos Based on Big Data-Mapreduce

Effective Detection and Prevention of Ddos Based on Big Data-Mapreduce

Dr. Koppula Srinivas Rao

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Sumathi Rani Manukonda

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to Jawaharlal Nehru Technological University, Hyderabad

Effective Detection and Prevention of Ddos Based on Big Data-Mapreduce

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Abstract

Distributed Denial of Service (DDoS) attacks is large-scale cooperative attacks launched from a large number of compromised hosts called Zombies are a major threat to Internet services. As the serious damage caused by DDoS attacks increases, the rapid detection and the proper response mechanisms are urgent. However, existing security methodologies do not provide effective defense against these attacks, or the defense capability of some mechanisms is only limited to specific DDoS attacks. Therefore, keeping this problem in view author presents various significant areas where data mining techniques seem to be a strong candidate for detecting and preventing DDoS attack. The new proposed methodology can perform detecting and preventing DDoS attack using MapReduce concepts in Big Data.Thus the methodology can implement for both detecting and preventing methodologies.

References

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

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No ethics committee approval was required for this article type.

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Not applicable for this article.

How to Cite This Article

Dr. Koppula Srinivas Rao. 2015. \u201cEffective Detection and Prevention of Ddos Based on Big Data-Mapreduce\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 15 (GJCST Volume 15 Issue C6).

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GJCST Volume 15 Issue C6

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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Classification

GJCST-C Classification C.2.4 E.2

Submission ReceivedDecember 6, 2014
Peer Review Double Blind
Handling Editor
Accepted January 3, 2015
Published January 15, 2015

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v1.2

Issue date

August 27, 2015

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Article Matrices

Total Score: 107

Country: India

Subject: Global Journal of Computer Science and Technology - C: Software & Data Engineering

Authors: Sumathi Rani Manukonda, Dr. Koppula Srinivas Rao (PhD/Dr. count: 1)

View Count (all-time): 299

Total Views (Real + Logic): 8156

Total Downloads (simulated): 1998

Publish Date: 2015 08, Thu

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Total Views: 8156

Total Downloads: 1998

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