Results 71 to 80 of about 7,115,390 (197)
k-Anonymous Decision Tree Induction [PDF]
, 2006 In this paper we explore an approach to privacy preserving data mining that relies on the k-anonymity model. The k-anonymity model guarantees that no private information in a table can be linked to a group of less than k individuals. We suggest extended definitions of k-anonymity that allow the k-anonymity of a data mining model to be determined. Using
Arik Friedman +2 more
openaire +1 more source
k-Degree Anonymity Model for Social Network Data Publishing
Advances in Electrical and Computer Engineering, 2017 Publicly accessible platform for social networking has gained special attraction because of its easy data sharing. Data generated on such social network is analyzed for various activities like marketing, social psychology, etc.
MACWAN, K. R., PATEL, S. J.
doaj +1 more source
, 2007 To protect respondents’ identity when releasing microdata, data holders often remove or encrypt explicit identifiers, such as names and social security numbers. De-identifying data, however, provide no guarantee of anonymity. Released information often
S. Foresti +3 more
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Achieving k-anonymity using full domain generalization [PDF]
, 2014 Preserving privacy while publishing data has emerged as key research area in data security and has become a primary issue in publishing person specific sensitive information.
Pal, A K
core
Providing K-Anonymity in location based services
, 2010 The offering of anonymity in relational databases has attracted a great deal of attention in the database community during the last decade [4]. Among the different solution approaches that have been proposed to tackle this problem, K-anonymity has ...
Aris Gkoulalas-Divanis +5 more
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ANALYSIS OF MULTILAYER-ENCRYPTION ANONYMITY NETWORKS
, 2017 The main goal of multilayer-encryption anonymity networks is to provide a certain level of privacy to their users. At the same time, such networks could be misused to perform harmful network activities.
Shahbar, Khalid
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Overview on K-anonymity Model for Overlapped Attributes
, 2014 K-anonymity model is mostly used technique of privacy preserving data publishing. In K-anonymity model data is converted into anonymous state. So, that adversary can’t be able to disclose sensitive information about the user.
, Bhakti Maheshwarkar, Assi. Prof. Pawan Patidar, Dr. M K Rawat
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k-anonymity in Resource Allocation for Vehicle-to-Everything (V2X) Systems
Journal of Telecommunications and Information TechnologySixth generation (6G) vehicle-to-everything (V2X) systems face numerous security threats, including Sybil and denial-of-service (DoS) cyber-attacks.
Andres Vejar +2 more
doaj +1 more source
12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'06)
, 2006 Privacy preservation is an important issue in the release of data for mining purposes. The k-anonymity model has been introduced for protecting individual identification.
Wong, Raymond Chi-Wing +3 more
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Probabilistic k-anonymity through microaggregation and data swapping
, 2012 k-Anonymity is a privacy property used to limit the risk of re-identification in a microdata set. A data set satisfying k-anonymity consists of groups of k records which are indistinguishable as far as their quasi-identifier attributes are concerned ...
Domingo Ferrer, Josep +3 more
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