000 | 04237nam a22005655i 4500 | ||
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001 | 978-0-387-70992-5 | ||
003 | DE-He213 | ||
005 | 20161121230712.0 | ||
007 | cr nn 008mamaa | ||
008 | 100301s2008 xxu| s |||| 0|eng d | ||
020 |
_a9780387709925 _9978-0-387-70992-5 |
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024 | 7 |
_a10.1007/978-0-387-70992-5 _2doi |
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050 | 4 | _aQA76.9.A25 | |
072 | 7 |
_aUR _2bicssc |
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072 | 7 |
_aUTN _2bicssc |
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_aCOM053000 _2bisacsh |
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082 | 0 | 4 |
_a005.8 _223 |
245 | 1 | 0 |
_aPrivacy-Preserving Data Mining _h[electronic resource] : _bModels and Algorithms / _cedited by Charu C. Aggarwal, Philip S. Yu. |
264 | 1 |
_aBoston, MA : _bSpringer US, _c2008. |
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300 |
_aXXII, 514 p. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aAdvances in Database Systems, _x1386-2944 ; _v34 |
|
505 | 0 | _aAn Introduction to Privacy-Preserving Data Mining -- A General Survey of Privacy-Preserving Data Mining Models and Algorithms -- A Survey of Inference Control Methods for Privacy-Preserving Data Mining -- Measures of Anonymity -- k-Anonymous Data Mining: A Survey -- A Survey of Randomization Methods for Privacy-Preserving Data Mining -- A Survey of Multiplicative Perturbation for Privacy-Preserving Data Mining -- A Survey of Quantification of Privacy Preserving Data Mining Algorithms -- A Survey of Utility-based Privacy-Preserving Data Transformation Methods -- Mining Association Rules under Privacy Constraints -- A Survey of Association Rule Hiding Methods for Privacy -- A Survey of Statistical Approaches to Preserving Confidentiality of Contingency Table Entries -- A Survey of Privacy-Preserving Methods Across Horizontally Partitioned Data -- A Survey of Privacy-Preserving Methods Across Vertically Partitioned Data -- A Survey of Attack Techniques on Privacy-Preserving Data Perturbation Methods -- Private Data Analysis via Output Perturbation -- A Survey of Query Auditing Techniques for Data Privacy -- Privacy and the Dimensionality Curse -- Personalized Privacy Preservation -- Privacy-Preserving Data Stream Classification. | |
520 | _aAdvances in hardware technology have increased the capability to store and record personal data about consumers and individuals. This has caused concerns that personal data may be used for a variety of intrusive or malicious purposes. Privacy Preserving Data Mining: Models and Algorithms proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. These techniques generally fall into the following categories: data modification techniques, cryptographic methods and protocols for data sharing, statistical techniques for disclosure and inference control, query auditing methods, randomization and perturbation-based techniques. This edited volume also contains surveys by distinguished researchers in the privacy field. Each survey includes the key research content as well as future research directions of a particular topic in privacy. Privacy Preserving Data Mining: Models and Algorithms is designed for researchers, professors, and advanced-level students in computer science. This book is also suitable for practitioners in industry. . | ||
650 | 0 | _aComputer science. | |
650 | 0 | _aComputer security. | |
650 | 0 | _aData encryption (Computer science). | |
650 | 0 | _aDatabase management. | |
650 | 0 | _aData mining. | |
650 | 0 | _aInformation storage and retrieval. | |
650 | 1 | 4 | _aComputer Science. |
650 | 2 | 4 | _aSystems and Data Security. |
650 | 2 | 4 | _aData Mining and Knowledge Discovery. |
650 | 2 | 4 | _aData Encryption. |
650 | 2 | 4 | _aDatabase Management. |
650 | 2 | 4 | _aInformation Storage and Retrieval. |
650 | 2 | 4 | _aInformation Systems Applications (incl. Internet). |
700 | 1 |
_aAggarwal, Charu C. _eeditor. |
|
700 | 1 |
_aYu, Philip S. _eeditor. |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9780387709918 |
830 | 0 |
_aAdvances in Database Systems, _x1386-2944 ; _v34 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-0-387-70992-5 |
912 | _aZDB-2-SCS | ||
950 | _aComputer Science (Springer-11645) | ||
999 |
_c502698 _d502698 |