Results 261 to 270 of about 12,445,360 (313)

On Distributed k-Anonymization

Fundamenta Informaticae, 2009
When a database owner needs to disclose her data, she can k-anonymize her data to protect the involved individuals' privacy. However, if the data is distributed between two owners, then it is an open question whether the two owners can jointly k-anonymize the union of their data, such that the information suppressed in one owner's data is not revealed
openaire   +2 more sources

Suppressed K-Anonymity Multi-Factor Authentication Based Schmidt-Samoa Cryptography for privacy preserved data access in cloud computing

Computer Communications, 2020
Security and privacy-preservation is a significant problem to be solved in the cloud when accessing data services. The existing authentication technique verifies the client identity using single authentication factor. But, the performance of conventional
K. Prabha, P. VidhyaSaraswathi
semanticscholar   +1 more source

Differentially Private K-Anonymity

2014 12th International Conference on Frontiers of Information Technology, 2014
Research in privacy preserving data publication can be broadly categorized in two classes. Syntactic privacy definitions have been under the cursor of the research community for the past many years. A lot of research is primarily dedicated to developing algorithms and notions for syntactic privacy that thwart the re-identification attacks.
Adeel Anjum, Adnan Anjum
openaire   +1 more source

k-anonymous message transmission

Proceedings of the 10th ACM conference on Computer and communications security, 2003
Informally, a communication protocol is sender k - anonymous if it can guarantee that an adversary, trying to determine the sender of a particular message, can only narrow down its search to a set of k suspects. Receiver k-anonymity places a similar guarantee on the receiver: an adversary, at best, can only narrow down the possible receivers to a set ...
Luis von Ahn, Andrew Bortz, Nicholas J. Hopper   +2 more
openaire   +1 more source

Protecting Trajectory From Semantic Attack Considering ${k}$ -Anonymity, ${l}$ -Diversity, and ${t}$ -Closeness

IEEE Transactions on Network and Service Management, 2019
Nowadays, human trajectories are widely collected and utilized for scientific research and business purpose. However, publishing trajectory data without proper handling might cause severe privacy leakage. A large body of works is dedicated to merging one’
Zhen Tu, Kai Zhao, Fengli Xu, Yong Li, L. Su, Depeng Jin   +5 more
semanticscholar   +1 more source

K-Anonymity inspired adversarial attack and multiple one-class classification defense

Neural Networks, 2020
A novel adversarial attack methodology for fooling deep neural network classifiers in image classification tasks is proposed, along with a novel defense mechanism to counter such attacks.
V. Mygdalis, A. Tefas, I. Pitas
semanticscholar   +1 more source

Towards optimal k-anonymization

Data & Knowledge Engineering, 2008
When releasing microdata for research purposes, one needs to preserve the privacy of respondents while maximizing data utility. An approach that has been studied extensively in recent years is to use anonymization techniques such as generalization and suppression to ensure that the released data table satisfies the k-anonymity property.
Tiancheng Li, Ninghui Li
openaire   +1 more source

Evolutionary Algorithms For k-Anonymity In Social Networks Based On Clustering Approach

Computer/law journal, 2020
The usage of social networks shows a growing trend in recent years. Due to a large number of online social networking users, there is a lot of data within these networks.
Navid Yazdanjue, M. Fathian, Babak Amiri
semanticscholar   +1 more source

Secure Distributed k-Anonymous Pattern Mining

Sixth International Conference on Data Mining (ICDM'06), 2006
Privacy-Preserving Data Mining is an important area that studies privacy issues of data mining. When the goal is to share data mining results, two privacy-related problems may arise. The first one is how to compute the data-mining results among several parties without sharing the data. Cryptography-based primitives are the basic tool used to develop ad-
JIANG W, ATZORI, MAURIZIO
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Clustering-Based k-Anonymity

2012
Privacy is one of major concerns when data containing sensitive information needs to be released for ad hoc analysis, which has attracted wide research interest on privacy-preserving data publishing in the past few years. One approach of strategy to anonymize data is generalization.
Xianmang He, HuaHui Chen, Yefang Chen, Yihong Dong, Peng Wang, Zhenhua Huang   +5 more
openaire   +1 more source