Please use this identifier to cite or link to this item: https://doi.org/10.1145/1989323.1989374
Title: We challenge you to certify your updates
Authors: Chen, S. 
Dong, X.L.
Lakshmanan, L.V.S.
Srivastava, D.
Keywords: certificate
data quality
update
Issue Date: 2011
Source: Chen, S.,Dong, X.L.,Lakshmanan, L.V.S.,Srivastava, D. (2011). We challenge you to certify your updates. Proceedings of the ACM SIGMOD International Conference on Management of Data : 481-492. ScholarBank@NUS Repository. https://doi.org/10.1145/1989323.1989374
Abstract: Correctness of data residing in a database is vital. While integrity constraint enforcement can often ensure data consistency, it is inadequate to protect against updates that involve careless, unintentional errors, e.g., whether a specified update to an employee's record was for the intended employee. We propose a novel approach that is complementary to existing integrity enforcement techniques, to guard against such erroneous updates. Our approach is based on (a) updaters providing an update certificate with each database update, and (b) the database system verifying the correctness of the update certificate provided before performing the update. We formalize a certificate as a (challenge, response) pair, and characterize good certificates as those that are easy for updaters to provide and, when correct, give the system enough confidence that the update was indeed intended. We present algorithms that efficiently enumerate good challenges, without exhaustively exploring the search space of all challenges. We experimentally demonstrate that (i) databases have many good challenges, (ii) these challenges can be efficiently identified, (iii) certificates can be quickly verified for correctness, (iv) under natural models of an updater's knowledge of the database, update certificates catch a high percentage of the erroneous updates without imposing undue burden on the updaters performing correct updates, and (v) our techniques are robust across a wide range of challenge parameter settings. © 2011 ACM.
Source Title: Proceedings of the ACM SIGMOD International Conference on Management of Data
URI: http://scholarbank.nus.edu.sg/handle/10635/40554
ISBN: 9781450306614
ISSN: 07308078
DOI: 10.1145/1989323.1989374
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