A security framework in G-Hadoop for big data computing across distributed cloud data centres. MapReduce is regarded as an adequate programming model for large-scale data-intensive applications. The Hadoop framework is a well-known MapReduce implementation that runs the MapReduce tasks on a cluster system. G-Hadoop is an extension of the Hadoop MapReduce framework with the functionality of allowing the MapReduce tasks to run on multiple clusters. However, G-Hadoop simply reuses the user authentication and job submission mechanism of Hadoop, which is designed for a single cluster. This work proposes a new security model for G-Hadoop. The security model is based on several security solutions such as public key cryptography and the SSL protocol, and is dedicatedly designed for distributed environments. This security framework simplifies the users authentication and job submission process of the current G-Hadoop implementation with a single-sign-on approach. In addition, the designed security framework provides a number of different security mechanisms to protect the G-Hadoop system from traditional attacks.

References in zbMATH (referenced in 12 articles )

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  1. Convolbo, Moïse W.; Chou, Jerry; Hsu, Ching-Hsien; Chung, Yeh Ching: GEODIS: towards the optimization of data locality-aware job scheduling in geo-distributed data centers (2018)
  2. Lefticaru, Raluca; Macías-Ramos, Luis F.; Niculescu, Ionuţ Mihai; Mierlă, Laurenţiu: Agent-based simulation of kernel P systems with division rules using FLAME (2017)
  3. Derbeko, Philip; Dolev, Shlomi; Gudes, Ehud; Sharma, Shantanu: Security and privacy aspects in MapReduce on clouds: a survey (2016)
  4. Ma, Yan; Chen, Lajiao; Liu, Peng; Lu, Ke: Parallel programing templates for remote sensing image processing on GPU architectures: design and implementation (2016) ioport
  5. Pop, Florin; Dobre, Ciprian; Comaneci, Dragos; Kolodziej, Joanna: Adaptive scheduling algorithm for media-optimized traffic management in software defined networks (2016)
  6. Qi, Lianyong; Dou, Wanchun; Chen, Jinjun: Weighted principal component analysis-based service selection method for multimedia services in cloud (2016)
  7. Song, Biao; Hassan, Mohammad Mehedi; Alamri, Atif; Alelaiwi, Abdulhameed; Tian, Yuan; Pathan, Mukaddim; Almogren, Ahmad: A two-stage approach for task and resource management in multimedia cloud environment (2016)
  8. Xu, Zheng; Mei, Lin; Liu, Yunhuai; Hu, Chuanping; Chen, Lan: Semantic enhanced cloud environment for surveillance data management using video structural description (2016)
  9. Yang, Chao-Tung; Shih, Wen-Chung; Huang, Chih-Lin; Jiang, Fuu-Cheng; Chu, William Cheng-Chung: On construction of a distributed data storage system in cloud (2016) ioport
  10. Zhao, Jiaqi; Tao, Jie; Streit, Achim: Enabling collaborative MapReduce on the cloud with a single-sign-on mechanism (2016) ioport
  11. Bul’ajoul, Waleed; James, Anne; Pannu, Mandeep: Improving network intrusion detection system performance through quality of service configuration and parallel technology (2015) ioport
  12. Zhao, Jiaqi; Wang, Lizhe; Tao, Jie; Chen, Jinjun; Sun, Weiye; Ranjan, Rajiv; Kołodziej, Joanna; Streit, Achim; Georgakopoulos, Dimitrios: A security framework in G-Hadoop for big data computing across distributed cloud data centres (2014)