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The topic of this scientific work is enabling privacy-preserving SQL-log analysis. Our goal is to find out an anonymization method, which aims to protect the privacy of SQL-log, meanwhile it has as less effect on the query plans as possible. Our experimental database and queries come from the famous TPC-H benchmark, in which we have the well constructed schema of original tables and all the 22 queries are designed to test as many aspects of the database as possible. We use existing DBMSs (Oracle and MySQL) to carry out our approach and test the performance of the anonymization method in the two DBMSs. As final results, our original anonymization method has successfully anonymized 95.45% of the queries in MySQL, which have always the same query plans. Experiments within Oracle need to be adjusted 3 times to improve the ratio of well anonymized query statements from 50% to 89.47%.
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Enabling privacy-preserving SQL-log analysis
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AV Akademikerverlag Mai 2017, 2017
ISBN 10: 3330517972
ISBN 13: 9783330517974
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The topic of this scientific work is enabling privacy-preserving SQL-log analysis. Our goal is to find out an anonymization method, which aims to protect the privacy of SQL-log, meanwhile it has as less effect on the query plans as possible. Our experimental database and queries come from the famous TPC-H benchmark, in which we have the well constructed schema of original tables and all the 22 queries are designed to test as many aspects of the database as possible. We use existing DBMSs (Oracle and MySQL) to carry out our approach and test the performance of the anonymization method in the two DBMSs. As final results, our original anonymization method has successfully anonymized 95.45% of the queries in MySQL, which have always the same query plans. Experiments within Oracle need to be adjusted 3 times to improve the ratio of well anonymized query statements from 50% to 89.47%. 104 pp. Englisch. Seller Inventory # 9783330517974
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Enabling privacy-preserving SQL-log analysis: in MySQL and Oracle
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Enabling privacy-preserving SQL-log analysis : in MySQL and Oracle
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The topic of this scientific work is enabling privacy-preserving SQL-log analysis. Our goal is to find out an anonymization method, which aims to protect the privacy of SQL-log, meanwhile it has as less effect on the query plans as possible. Our experimental database and queries come from the famous TPC-H benchmark, in which we have the well constructed schema of original tables and all the 22 queries are designed to test as many aspects of the database as possible. We use existing DBMSs (Oracle and MySQL) to carry out our approach and test the performance of the anonymization method in the two DBMSs. As final results, our original anonymization method has successfully anonymized 95.45% of the queries in MySQL, which have always the same query plans. Experiments within Oracle need to be adjusted 3 times to improve the ratio of well anonymized query statements from 50% to 89.47%. Seller Inventory # 9783330517974
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Enabling privacy-preserving SQL-log analysis: in MySQL and Oracle
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Enabling privacy-preserving SQL-log analysis
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Fang HongjieThe author studied Computer Science and Technology at the Beijing University of Posts and Telecommunications, has a Master in Informatics from Karlsruhe Institute of Technology and is now a PHD Student at the University o. Seller Inventory # 151238603
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Enabling privacy-preserving SQL-log analysis: in MySQL and Oracle
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Enabling privacy-preserving SQL-log analysis: in MySQL and Oracle
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Enabling privacy-preserving SQL-log analysis
Published by
AV Akademikerverlag Mai 2017, 2017
ISBN 10: 3330517972
ISBN 13: 9783330517974
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The topic of this scientific work is enabling privacy-preserving SQL-log analysis. Our goal is to find out an anonymization method, which aims to protect the privacy of SQL-log, meanwhile it has as less effect on the query plans as possible. Our experimental database and queries come from the famous TPC-H benchmark, in which we have the well constructed schema of original tables and all the 22 queries are designed to test as many aspects of the database as possible. We use existing DBMSs (Oracle and MySQL) to carry out our approach and test the performance of the anonymization method in the two DBMSs. As final results, our original anonymization method has successfully anonymized 95.45% of the queries in MySQL, which have always the same query plans. Experiments within Oracle need to be adjusted 3 times to improve the ratio of well anonymized query statements from 50% to 89.47%.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 104 pp. Englisch. Seller Inventory # 9783330517974
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Enabling privacy-preserving SQL-log analysis | in MySQL and Oracle
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Taschenbuch. Condition: Neu. Enabling privacy-preserving SQL-log analysis | in MySQL and Oracle | Hongjie Fang | Taschenbuch | 104 S. | Englisch | 2017 | AV Akademikerverlag | EAN 9783330517974 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 109127308
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Enabling privacy-preserving SQL-log analysis: in MySQL and Oracle
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