STANlite - A database engine for secure data processing at rack-scale level
Sartakov VA, Weichbrodt N, Krieter S, Leich T, Kapitza R (2018)
Publication Type: Conference contribution
Publication year: 2018
Publisher: Institute of Electrical and Electronics Engineers Inc.
Pages Range: 23-33
Conference Proceedings Title: Proceedings - 2018 IEEE International Conference on Cloud Engineering, IC2E 2018
Event location: Orlando, FL
ISBN: 9781538650080
Abstract
Intel's novel Software Guard eXtensions (SGX) enable secure and trusted execution of services, thereby paving the way to outsource sensitive data processing to external data centers. While SGX promises trusted execution close to native speed, frequent I/O operations and memory usage beyond a hardware-dependent threshold of currently 92 MiB result in substantial performance degradation. For memory-intensive workloads such as key-value stores and databases these penalties can be prohibitively high. We present STANlite - an in-memory database engine for SGX-enabled secure data processing in rack-scale environments. STANlite performs efficient user-level paging, whenever a database workload requires more space than the performance-friendly in-memory state size. Furthermore, STANlite smartly combines the properties of Remote Direct Memory Access (RDMA) and SGX to reduce the overhead of network-based I/O operations. While SGX usually provides confidentiality and integrity at the same time, STANlite enables a purely integrity preserving data management mode for additional performance. Finally, STANlite features a small trusted computing base and is memory-efficient, as it extends SQLite, a database for embedded use. We evaluated STANlite in terms of query response time. It outperforms a vanilla SGX-based SQLite version by 1.79x for microbenchmarks and 2.44x for TPC-C.
Authors with CRIS profile
Involved external institutions
Otto-von-Guericke-Universität Magdeburg
Germany (DE)
Hochschule Harz
Germany (DE)
Technische Universität Braunschweig
Germany (DE)
Germany (DE)
Hochschule Harz
Germany (DE)
Technische Universität Braunschweig
Germany (DE)
How to cite
APA:
Sartakov, V.A., Weichbrodt, N., Krieter, S., Leich, T., & Kapitza, R. (2018). STANlite - A database engine for secure data processing at rack-scale level. In Jie Li, Abhishek Chandra, Tian Guo, Ying Cai (Eds.), Proceedings - 2018 IEEE International Conference on Cloud Engineering, IC2E 2018 (pp. 23-33). Orlando, FL, US: Institute of Electrical and Electronics Engineers Inc..
MLA:
Sartakov, Vasily A., et al. "STANlite - A database engine for secure data processing at rack-scale level." Proceedings of the 2018 IEEE International Conference on Cloud Engineering, IC2E 2018, Orlando, FL Ed. Jie Li, Abhishek Chandra, Tian Guo, Ying Cai, Institute of Electrical and Electronics Engineers Inc., 2018. 23-33.
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