The week's pick
Random Articles
Reseach Article
The Prototype for Implementation of Security Issue in Big Data Application using Hadoop Server
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 145 - Number 13 |
| Year of Publication: 2016 |
| Authors: Shalini Singh, Meena Sharma |
10.5120/ijca2016910844
|
Shalini Singh, Meena Sharma . The Prototype for Implementation of Security Issue in Big Data Application using Hadoop Server. International Journal of Computer Applications. 145, 13 ( Jul 2016), 9-13. DOI=10.5120/ijca2016910844
Abstract
A large amount of data can be referred as BigData. A vast size of data requires special kind of methodology to process and store. BigData research consortium team developed a distributed server known as Hadoop Server, to divide and partition large data into multiple pieces for fast and efficient processing. Hadoop is an open source solution developed by Google Corporation for large data processing. It supports variety of components and distributed file system. MapReduce, Pig, Hive are the components used for efficient development of software, together with Hadoop Distributed File System which is responsible for storing and processing large data with multiple nodes. The complete study observes that advance level of processing is required for large data scale, thereby to accomplish level of concert. In order to circumvent problem of privacy leakage and access maintenance, an elucidated security model has been developed for BigData application. This paper describes the security issue along with its solution. The proposed solution is implemented with Hadoop server in single node and multinode environment.
References
- Interactions with Big Data Analytics, Danyel Fisher Microsoft Research | danyelf@microsoft. com.
- https://hadoop.apache.org/docs/r1.2.1/mapred_tutorial.html#Overview
- MongoDB: The Definitive Guide,2013, by Kristina Chodorow
- The Hadoop Distributed File System Konstantin Shvachko, Hairong Kuang, Sanjay Radia, Robert Chansler Yahoo! Sunnyvale, California USA {Shv, Hairong, SRadia, Chansler}@Yahoo-Inc.com
- A Solution For Privacy Protection In MapReduce Quang Tran,Hiroyuki Sato Graduate School of Engineering, The University of Tokyo.
- M. Terrovitis, N. Mamoulis, and P. Kalnis, “Privacy-preserving anonymization of set-valued data,” Proc. VLDB Endow., vol. 1, no. 1, pp. 115–125, Aug. 2008.
- M. Terrovitis, N. Mamoulis, and P. Kalnis, “Local and global recoding methods for anonymizing set-valued data,” The VLDB Journal, vol. 20, no. 1, pp. 83–106, Feb. 2011.
- Y. He and J. F. Naughton, “Anonymization of set-valued data via topdown, local generalization,” Proc. VLDB Endow., vol. 2, no. 1, pp. 934– 945, Aug. 2009.
- J. Cao, P. Karras, C. Ra¨ıssi, and K.-L. Tan, “ρ-uncertainty: inferenceprooftransactionanonymization,” Proceedings of the VLDB Endowment, vol. 3, no. 1-2, pp. 1033–1044, 2010.
- Y. Xu, K. Wang, A. W.-C. Fu, and P. S. Yu, “Anonymizing transaction databases for publication,” in Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ser. KDD ’08, 2008, pp. 767–775.
- G. Loukides, A. Gkoulalas-Divanis, and J. Shao, “Anonymizing transaction data to eliminate sensitive inferences,” in Proceedings of the 21st International Conference on Database and Expert Systems Applications: Part I, ser. DEXA’10, 2010, pp. 400–415.
- X. Zhang, L. Yang, C. Liu, and J. Chen, “A scalable two-phase topdown specialization approach for data anonymization using MapReduce on cloud,” Parallel and Distributed Systems, IEEE Transactions on, vol. 25, no. 2, pp. 363–373, Feb 2014.
- T. Iwuchukwu and J. F. Naughton, “K-anonymization as spatial indexing: Toward scalable and incremental anonymization,” in Proceedings of the 33rd International Conference on Very Large Data Bases, ser. VLDB ’07, 2007, pp. 746–757.
- K. LeFevre, D. J. DeWitt, and R. Ramakrishnan, “Workloadaware anonymization techniques for large-scale datasets,” ACM Trans. Database Syst., vol. 33, no. 3, pp. 17:1–17:47, Sep. 2008.
- G. Loukides, A. Gkoulalas-Divanis, and J. Shao, “Efficient and flexible anonymization of transaction data,” Knowledge and information systems, vol. 36, no. 1, pp. 153–210, 2013.
- Wang.et.al, Federated MapReduce to Transparently Run Applications on Multicluster Environment,2014 IEEE International Congress on Big Data
- Travis Mayberry, Erik-Oliver Blass, Agnes Hui Chan, “PIRMAP: Efficient Private Information Retrieval for MapReduce”, Proceedings of Financial Cryptography and Data Security (FC’13), pp. 371—385, Okinawa, Japan
- Access Control for Sensitive Data in Hadoop Yenumula B. Reddy Department of Computer Science Grambling State University, USA
- Yenumula B Reddy “Access Control Mechanisms in Big Data Processing” Department of Computer Science Grambling State University, Grambling, LA 71245, USA.
- C. Dwork, “Differential privacy” in Encyclopedia of Cryptography and Security Springer 2011.
- Foodmart Dataset, https://technet.microsoft.com/en-us/library .
- Jim Kurose, Keith Ross Addison-Wesley, “Security Principle”, March 2012.
- Huseyin Ulusoy, Murat Kantarcioglu, ErmanPattuk, Kevin Hamlen, et al. , 2014”Fine grained Access Control in MapReduce ”.
- Neelam Memon,Grigorious Loukides, Jianhua Shao, et. al., 2014, “A Parallel Method for Scalable Anonymization of Transaction Data” School of Computer Science & Informatics Cardiff University, UK.
- Weidong Shi, TaeweonSuh, et. al., IEEE 2014,”A FPGA cloud for Privacy Preservation computation ”
- Xianfeng Yang and Liming Lian,et. al., 2014, “A New Data Mining Algorithm based on MapReduce and Hadoop,” Xinxiang University, Xinxiang Henan, P.R.CHINA
- B.C.M. Fung, K. Wang and P.S. Yu, “Anonymizing Classification Data for Privacy Preservation,” IEEE Transactions on Knowledge and Data Engineering, vol. 19, no. 5, pp. 711-725, 2007.
- M. V. Dijk, C. Gentry, S. Halevi, and V. Vaikuntanathan, Fully homomorphic encryption over the integers, presented at the 29th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Riviera, French, 2010.
Index Terms
Keywords