Privacy-Preserving Parametric Inference: A Case for Robust Statistics
نویسندگان
چکیده
منابع مشابه
A centralized privacy-preserving framework for online social networks
There are some critical privacy concerns in the current online social networks (OSNs). Users' information is disclosed to different entities that they were not supposed to access. Furthermore, the notion of friendship is inadequate in OSNs since the degree of social relationships between users dynamically changes over the time. Additionally, users may define similar privacy settings for their f...
متن کاملFault-Tolerant Privacy-Preserving Statistics
Real-time statistics on smart meter consumption data must preserve consumer privacy and tolerate smart meter failures. Existing protocols for this private distributed aggregation model suffer from various drawbacks that disqualify them for application in the smart energy grid. Either they are not fault-tolerant or if they are, then they require bidirectional communication or their accuracy decr...
متن کاملInference Control for Privacy-Preserving Genome Matching
Privacy is of the utmost importance in genomic matching. Therefore a number of privacy-preserving protocols have been presented using secure computation. Nevertheless, none of these protocols prevents inferences from the result. Goodrich has shown that this resulting information is sufficient for an effective attack on genome databases. In this paper we present an approach that can detect and m...
متن کاملA Robust Privacy-Preserving Recommendation Algorithm
Privacy-preserving collaborative filtering schemes are key recommender system technologies for e-commerce field. They focus on alleviating information overload problem by providing personalized recommendations without deeply jeopardizing customers’ privacy. Like their non-private versions, privacy-preserving recommendation methods might be easily subjected to profile injection attacks for manip...
متن کاملExperimental Analysis of Privacy-Preserving Statistics Computation
The recent investigation of privacy-preserving data mining and other kinds of privacy-preserving distributed computation has been motivated by the growing concern about the privacy of individuals when their data is stored, aggregated, and mined for information. Building on the study of selective private function evaluation and the efforts towards practical algorithms for privacy-preserving data...
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: Journal of the American Statistical Association
سال: 2020
ISSN: 0162-1459,1537-274X
DOI: 10.1080/01621459.2019.1700130