A Novel and Efficient Method for Protecting Internet Usage from Unauthorized Access Using Map Reduce
Автор: P. Srinivasa Rao, K. Thammi Reddy, MHM. Krishna Prasad
Журнал: International Journal of Information Technology and Computer Science(IJITCS) @ijitcs
Статья в выпуске: 3 Vol. 5, 2013 года.
Бесплатный доступ
The massive increases in data have paved a path for distributed computing, which in turn can reduce the data processing time. Though there are various approaches in distributed computing, Hadoop is one of the most efficient among the existing ones. Hadoop consists of different elements out of which Map Reduce is a scalable tool that enables to process a huge data in parallel. We proposed a Novel and Efficient User Profile Characterization under distributed environment. In this frame work the network anomalies are detected by using Hadoop Map Reduce technique. The experimental results clearly show that the proposed technique shows better performance.
Mapreduce, Hadoop, Distributed Computing
Короткий адрес: https://sciup.org/15011837
IDR: 15011837
Список литературы A Novel and Efficient Method for Protecting Internet Usage from Unauthorized Access Using Map Reduce
- Kyong-Ha Lee, Hyunsik Choi, Bongki Moon “Parallel data processing with MapReduce: A Survey” December 2011.
- Ping ZHOU, Jingsheng LEI, Wenjun YE“Large-Scale Data Sets Clustering Based on Map Reduce and Hadoop”, Binary information Press, 1553-9105, December 2011.
- “Hadoop”, http://hadoop.apache.org
- B. Kiran Kumar, A. Bhaskar “Identifying Network Anomalies Using Clustering Technique in Weblog Data” ,ijca,Volume 2 No.3, June 2012.
- Kai Shuang1, Yin Y ang “X-RIME: HADOOP-BASED LARGE-SCALE SOCIAL NETWORK ANALYSIS” Proceedings of IC-BNMT20 10
- Kulsoom Abdullah, Chris Lee, Gregory Conti, John A.Copeland. “Visualizing Network Data for Intrusion Detection“, Proceedings of the IEEE 2002.
- DougCutting,“HadoopOverview”, http://research.yahoo.com/node/2116
- Jeffy Dean,Sanjay Ghemawat. MapReduce, “Simplified Data Processing on Large Clusters”, OSDI04: Sixth Symposium on Operating System Design and Implemention, Ssn Francisco,CA,December, 2004.
- Jeff Dean. “Handling Large Dataset at Google: Current System and Future Direction”, http://labs.google.com/people/jeff
- HUANG Lan*, WANG Xiao-wei, ZHAI Yan-dong, YANG Bin “Extraction of User Profile Based on the Hadoop Framework” IEEE 2009.
- Spiros Papadimitriou Jimeng Sun “DisCo: Distributed Co-clustering with Map-Reduce A Case Study Towards Petabyte-Scale End-to-End Mining” ICDM.2008.142.IEEE 2008.
- LIU Ni-na, “Research on the Web Mining and Personalized Search Engine”. Master degree theses of Zhejiang University,2005.
- Ken Mann “ and provided Distributed computing with Linux and Hadoop. “Freelance March 2011.
- Arun C Murhtygiven “ Next Generation of Apache Hadoop Map Reduce-The Scheduler where he explained background knowledge of resource utilization by Hadoop.” Freelance March 2011.
- Kashyap Santoki “indexing and searching on a Hadoop Distributed File System from which knowledge of Hadoop HDFS can be undersood.” July 2010.
- Rajiv Gupta “Efficiently Querying Archived Data using Hadoop”,CIKM’10,ACM978-5/10.
- Michael Cardosa “Exploring MapReduce Efficiency with Highly-Distributed Data”.MapReduce’11,ACM, USA June 2011.
- Jiong Xie “improving MapReduce Performance through Data placement in Hetrogeneous Hadoop Clusters”.IEEE 2010.
