Data Disclosure Under Perfect Sample Privacy
نویسندگان
چکیده
منابع مشابه
Disclosure Prevention in Privacy-preserving Data Publishing
The advancement of information technologies has enabled various organizations (e.g., census agencies, hospitals) to collect large volumes of sensitive personal data (e.g., census data, medical records. Data in its original form, however, typically contains sensitive information about individuals, and publishing such data will violate individual privacy. The current practice in data publishing r...
متن کاملA Privacy Measure for Data Disclosure
Closeness is described as a privacy measure and its advantages are illustrated through examples and experiments on a real dataset. In this Paper the closeness can be verified by giving different values for N and T. Government agencies and other organizations often need to publish micro data, e. g. , medical data or census data, for research and other purposes. Typically, such data are stored in...
متن کاملStatistical Disclosure Control for Data Privacy Preservation
With the phenomenal change in a way data are collected, stored and disseminated among various data analyst there is an urgent need of protecting the privacy of data. As when individual data get disseminated among various users, there is a high risk of revelation of sensitive data related to any individual, which may violate various legal and ethical issues. Statistical Disclosure Control (SDC) ...
متن کاملTransparency and Disclosure Risk in Data Privacy
k-Anonymity and differential privacy can be considered examples of Boolean definitions of disclosure risk. In contrast, record linkage and uniqueness are examples of quantitative measures of risk. Record linkage is a powerful approach because it can model different types of scenarios in which an adversary attacks a protected database with some information and background knowledge. Transparency ...
متن کاملPerfect Matching Disclosure Attacks
Traffic analysis is the best known approach to uncover relationships amongst users of anonymous communication systems, such as mix networks. Surprisingly, all previously published techniques require very specific user behavior to break the anonymity provided by mixes. At the same time, it is also well known that none of the considered user models reflects realistic behavior which casts some dou...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Information Forensics and Security
سال: 2020
ISSN: 1556-6013,1556-6021
DOI: 10.1109/tifs.2019.2954652