Research on Book Circulation Information Publishing Based on Anonymity Techniques

Reader privacy protection as the key problem in library field is winning more and more attentions now. The requirement of business information security publishing is further enhanced by library information sharing and cooperation works. This paper aims at book circulation information publishing problem and analyses the data sheet structure of the circulation information in detail. Based on the practical requirements of data analysis, it also gives out a book circulation information anonymous publishing model based on demand. Implemented with ETL, this the issues privacy technology initially to process raw data set. Then it brings anonymity technique into further data process to achieve the goal of security data publishing. This paper also proposes an improving anonymity algorithm based on practical data features and data application requirement. Finally, we propose a further research direction of privacy protecting in digital library by analyzing the existing question.

[1]  Philip S. Yu,et al.  Top-down specialization for information and privacy preservation , 2005, 21st International Conference on Data Engineering (ICDE'05).

[2]  Ashwin Machanavajjhala,et al.  l-Diversity: Privacy Beyond k-Anonymity , 2006, ICDE.

[3]  Ninghui Li,et al.  t-Closeness: Privacy Beyond k-Anonymity and l-Diversity , 2007, 2007 IEEE 23rd International Conference on Data Engineering.

[4]  Pierangela Samarati,et al.  Protecting privacy when disclosing information: k-anonymity and its enforcement through generalization and suppression , 1998 .

[5]  Ming Liu,et al.  A Personalized (a,k)-Anonymity Model , 2008, 2008 The Ninth International Conference on Web-Age Information Management.

[6]  David J. DeWitt,et al.  Incognito: efficient full-domain K-anonymity , 2005, SIGMOD '05.

[7]  Latanya Sweeney,et al.  Achieving k-Anonymity Privacy Protection Using Generalization and Suppression , 2002, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[8]  Yufei Tao,et al.  M-invariance: towards privacy preserving re-publication of dynamic datasets , 2007, SIGMOD '07.

[9]  David J. DeWitt,et al.  Mondrian Multidimensional K-Anonymity , 2006, 22nd International Conference on Data Engineering (ICDE'06).