Abstract
When analyzing sensitive data in a cloud-deployed Hadoop stack, data-in-transit security needs to be enabled, especially in the underlying storage tier. This, however, will affect the performance of the system and may partially offset the cost benefits of the cloud. In this paper, we discuss two strategies for securing HBase deployments in the cloud. For both, we present benchmarking results which show performance impacts that significantly exceed the suggested 10% from the official documentation. These results demonstrate (i) that security configurations should follow a rational decision process based on benchmarking results and (ii) that the security architecture of HBase/HDFS should be redesigned with an emphasis on performance.
Originalsprache | Englisch |
---|---|
Titel | 2016 IEEE International Conference on Big Data (Big Data) |
Herausgeber (Verlag) | IEEE |
Seiten | 548-554 |
Seitenumfang | 7 |
ISBN (Print) | 978-1-4673-9006-4 |
DOIs | |
Publikationsstatus | Veröffentlicht - 8 Dez. 2016 |
Veranstaltung | 2016 IEEE International Conference on Big Data (Big Data) - Washington, DC, USA Dauer: 5 Dez. 2016 → 8 Dez. 2016 |
Konferenz
Konferenz | 2016 IEEE International Conference on Big Data (Big Data) |
---|---|
Zeitraum | 5/12/16 → 8/12/16 |
Schlagwörter
- Cloud computing
- Servers
- Big data
- Encryption
- Virtual private networks
- Benchmark testing
Systematik der Wissenschaftszweige 2012
- 102 Informatik