We address the publication of a large academic information dataset while ensuring privacy. We evaluate anonymization techniques achieving the intended protection, while retaining the utility of the anonymized data. The published data can help to infer behaviors and study interaction patterns in an academic population. These could subsequently be used to improve the planning of campus life, such...

The presence of private information belonging to individuals in data heaps called "Big Data" causes the privacy person be endangered against disclosure attacks. To protect personal big data, it is ensured that anonymous created, stored, and shared systems with anonymization methods. However, de-identified cannot reinstatement. aim this study create a new method provides instant disidentificatio...

Data is the currency of the digital economy, but increasing data collection by companies and sharing with third parties threatens privacy. “Anonymization” is the usual answer to privacy concerns, typically implemented via removal of “personally identifiable information.” Sweeney’s work on reidentification of Massachusetts hospital records showed that naive deidentification via PII removal can b...

A Behavior-based Approach Towards Statistics-Preserving Network Trace

The sharing of network traces is an important prerequisite for the development and evaluation of efficient anomaly detection mechanisms. Unfortunately, privacy concerns and data protection laws prevent network operators from sharing these data. Anonymization is a promising solution in this context; however, it is unclear if the sanitization of data preserves the traffic characteristics or intro...

C ensorship and the increased tracking of users on l i ne h a ve b e c ome important topics. Numerous governments censor computerand network-based communications to keep their citizens from freely getting news from or transmitting information to the outside world. Dissidents and everyday Internet users—as well as criminals and others who want their online identities to be secret—have turned to ...

Query log anonymization has become an important challenge nowadays. A query log contains the search history of the users, as well as the selected results and their position in the ranking. These data are used to provide a personalized re-ranking of results and trend studies. However, query logs can disclose sensitive information of the users. Hence, query logs must be submitted to an anonymizat...

In the medical field, we are amassing phenomenal amounts of data. This data is imperative in discovering patterns and trends to help improve healthcare. Yet the researchers cannot rejoice as the data cannot be easily shared, because health data custodians have the understandable ethical and legal responsibility to maintain the privacy of individuals. Many techniques of anonymization have been p...

Privacy-Preserving Data Publishing (PPDP) has become a critical issue for companies and organizations that would release their data. k-Anonymization was proposed as a first generalization model to guarantee against identity disclosure of individual records in a data set. Point access methods (PAMs) are not well studied for the problem of data anonymization. In this article, we propose yet anoth...

The proposed graphical user interface (GUI) for microdata protection serves as an easyto-handle tool for users who want to use the sdcMicro package for statistical disclosure control but are not familiar with the native R command line interface. In addition to that, interactions between objects that result from the anonymization process are provided within this GUI. This allows an automated rec...