| Title | SecureMR: Secure Mapreduce Computation Using Homomorphic Encryption and Program Partitioning |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Dong, Yao, Milanova, Ana, Dolby, Julian |
| Conference Name | Proceedings of the 5th Annual Symposium and Bootcamp on Hot Topics in the Science of Security |
| Publisher | ACM |
| Conference Location | New York, NY, USA |
| ISBN Number | 978-1-4503-6455-3 |
| Keywords | cloud computing, homomorphic encryption, human factors, MapReduce, Metrics, pubcrawl, Resiliency, Scalability |
| Abstract | In cloud computing customers upload data and computation to cloud providers. As they upload their data to the cloud provider, they typically give up data confidentiality. We develop SecureMR, a system that analyzes and transforms MapReduce programs to operate over encrypted data. SecureMR makes use of partially homomorphic encryption and a trusted client. We evaluate SecureMR on a set of complex computation-intensive MapReduce benchmarks. |
| URL | http://doi.acm.org/10.1145/3190619.3190638 |
| DOI | 10.1145/3190619.3190638 |
| Citation Key | dong_securemr:_2018 |
SecureMR: Secure Mapreduce Computation Using Homomorphic Encryption and Program Partitioning