Earticle

초록

영어

MapReduce, a large-scale data processing paradigm, is gaining popularity. However, like other distributed computing frameworks, MapReduce suffers from the integrity assurance vulnerability: malicious workers in the MapReduce cluster could tamper with its computation result and thereby render the overall computation result inaccurate. Existing solutions are effective in defeating the malicious behavior of non-collusive workers, but are less effective in detecting collusive workers. In this paper, we propose the Verification-based Integrity Assurance Framework (VIAF). By using task replication and probabilistic result verification, VIAF can detect both non-collusive and collusive workers, even if the malicious workers dominate the environment. We have implemented VIAF on Hadoop, an open source MapReduce implementation. Our theoretical analysis and experimental result show that VIAF can achieve high job accuracy while imposing moderate performance overhead.

목차

Abstract
 1. Introduction
 2. System Assumption and Attacker Model
  2.1. System Assumptions
  2.2. Attacker Model
 3. System Design and Analysis
  3.1. System Design
  3.2. Theoretical Analysis
 4. Implementation and Evaluation
  4.1. Implementation Details
  4.2. Collusive Worker Model
  4.3. Experiment and Result Analysis
 5. Related Work
 6. Conclusion
 Acknowledgements
 References

키워드

저자

• Yongzhi Wang [ Floridia International University ]
• Jinpeng Wei [ Floridia International University ]
• Yucong Duan [ Hainan University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Grid and Distributed Computing

• 간기

  격월간

• pISSN

  2005-4262

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605