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

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Dr. Koppula Srinivas Rao
Dr. Koppula Srinivas Rao
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Sumathi Rani Manukonda
Sumathi Rani Manukonda
α to σ Jawaharlal Nehru Technological University, Hyderabad

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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

10 Cites in Article
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  2. Rui Zhong,Guangxue Yue (2010). DDoS Detection System Based on Data Mining.
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  4. J Brutlag (2000). Aberrant Behavior Detection in Time Series for Network Monitoring.
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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

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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Issue Cover
GJCST Volume 15 Issue C6
Pg. 21- 25
Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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GJCST-C Classification: C.2.4 E.2
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v1.2

Issue date

August 27, 2015

Language
en
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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.

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

Sumathi Rani Manukonda
Sumathi Rani Manukonda Jawaharlal Nehru Technological University, Hyderabad
Dr. Koppula Srinivas Rao
Dr. Koppula Srinivas Rao Jawaharlal Nehru Technological University, Hyderabad

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