Abstract
Spurred by financial scandals and privacy concerns, governments worldwide have moved to ensure confidence in digital records by regulating their retention and deletion. These requirements have led to a huge market for compliance storage servers, which ensure that data are not shredded or altered before the end of their mandatory retention period. These servers preserve unstructured and semi-structured data at a file-level granularity: email, spreadsheets, reports, instant messages. In this paper, we extend this level of protection to structured data residing in relational databases. We propose a compliant DBMS architecture and two refinements that illustrate the additional security that one can gain with only a slight performance penalty, with almost no modifications to the DBMS kernel. We evaluate our proposed architecture through experiments with TPC-C on a high-performance DBMS, and show that the runtime overhead for transaction processing is approximately 10% in typical configurations.
Original language | English (US) |
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Title of host publication | Proceedings - International Conference on Data Engineering |
Pages | 162-173 |
Number of pages | 12 |
DOIs | |
State | Published - 2009 |
Event | 25th IEEE International Conference on Data Engineering, ICDE 2009 - Shanghai, China Duration: Mar 29 2009 → Apr 2 2009 |
Other
Other | 25th IEEE International Conference on Data Engineering, ICDE 2009 |
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Country | China |
City | Shanghai |
Period | 3/29/09 → 4/2/09 |
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ASJC Scopus subject areas
- Information Systems
- Signal Processing
- Software
Cite this
An architecture for regulatory compliant database management. / Mitra, Soumyadeb; Winslett, Marianne; Snodgrass, Richard Thomas; Yaduvanshi, Shashank; Ambokar, Sumedh.
Proceedings - International Conference on Data Engineering. 2009. p. 162-173 4812400.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - An architecture for regulatory compliant database management
AU - Mitra, Soumyadeb
AU - Winslett, Marianne
AU - Snodgrass, Richard Thomas
AU - Yaduvanshi, Shashank
AU - Ambokar, Sumedh
PY - 2009
Y1 - 2009
N2 - Spurred by financial scandals and privacy concerns, governments worldwide have moved to ensure confidence in digital records by regulating their retention and deletion. These requirements have led to a huge market for compliance storage servers, which ensure that data are not shredded or altered before the end of their mandatory retention period. These servers preserve unstructured and semi-structured data at a file-level granularity: email, spreadsheets, reports, instant messages. In this paper, we extend this level of protection to structured data residing in relational databases. We propose a compliant DBMS architecture and two refinements that illustrate the additional security that one can gain with only a slight performance penalty, with almost no modifications to the DBMS kernel. We evaluate our proposed architecture through experiments with TPC-C on a high-performance DBMS, and show that the runtime overhead for transaction processing is approximately 10% in typical configurations.
AB - Spurred by financial scandals and privacy concerns, governments worldwide have moved to ensure confidence in digital records by regulating their retention and deletion. These requirements have led to a huge market for compliance storage servers, which ensure that data are not shredded or altered before the end of their mandatory retention period. These servers preserve unstructured and semi-structured data at a file-level granularity: email, spreadsheets, reports, instant messages. In this paper, we extend this level of protection to structured data residing in relational databases. We propose a compliant DBMS architecture and two refinements that illustrate the additional security that one can gain with only a slight performance penalty, with almost no modifications to the DBMS kernel. We evaluate our proposed architecture through experiments with TPC-C on a high-performance DBMS, and show that the runtime overhead for transaction processing is approximately 10% in typical configurations.
UR - http://www.scopus.com/inward/record.url?scp=67649646394&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=67649646394&partnerID=8YFLogxK
U2 - 10.1109/ICDE.2009.69
DO - 10.1109/ICDE.2009.69
M3 - Conference contribution
AN - SCOPUS:67649646394
SN - 9780769535456
SP - 162
EP - 173
BT - Proceedings - International Conference on Data Engineering
ER -