Effective Detection and Prevention of Ddos Based on Big Data-Mapreduce
Keywords:
ddos attacks, data mining-big data, mapreduce
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.
Downloads
- Article PDF
- TEI XML Kaleidoscope (download in zip)* (Beta by AI)
- Lens* NISO JATS XML (Beta by AI)
- HTML Kaleidoscope* (Beta by AI)
- DBK XML Kaleidoscope (download in zip)* (Beta by AI)
- LaTeX pdf Kaleidoscope* (Beta by AI)
- EPUB Kaleidoscope* (Beta by AI)
- MD Kaleidoscope* (Beta by AI)
- FO Kaleidoscope* (Beta by AI)
- BIB Kaleidoscope* (Beta by AI)
- LaTeX Kaleidoscope* (Beta by AI)
How to Cite
Published
2015-03-15
Issue
Section
License
Copyright (c) 2015 Authors and Global Journals Private Limited
This work is licensed under a Creative Commons Attribution 4.0 International License.