원문정보
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
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