Flexible data anonymization using ARX—Current status and challenges ahead
The race for innovation has turned into a race for data. Rapid developments of new
technologies, especially in the field of artificial intelligence, are accompanied by new ways …
technologies, especially in the field of artificial intelligence, are accompanied by new ways …
[KİTAP][B] Data leakage detection/prevention solutions
Abstract According to the Forrester Wave report [Raschke, 2008], most early DLP solutions
focused on finding sensitive data as they left the organizational network by monitoring data …
focused on finding sensitive data as they left the organizational network by monitoring data …
On syntactic anonymity and differential privacy
Recently, there has been a growing debate over approaches for handling and analyzing
private data. Research has identified issues with syntactic anonymity models. Differential …
private data. Research has identified issues with syntactic anonymity models. Differential …
Enhancing data utility in differential privacy via microaggregation-based -anonymity
It is not uncommon in the data anonymization literature to oppose the “old” k k-anonymity
model to the “new” differential privacy model, which offers more robust privacy guarantees …
model to the “new” differential privacy model, which offers more robust privacy guarantees …
A Clustering Approach for the l‐Diversity Model in Privacy Preserving Data Mining Using Fractional Calculus‐Bacterial Foraging Optimization Algorithm
In privacy preserving data mining, the l‐diversity and k‐anonymity models are the most
widely used for preserving the sensitive private information of an individual. Out of these two …
widely used for preserving the sensitive private information of an individual. Out of these two …
[HTML][HTML] k-Anonymity in practice: How generalisation and suppression affect machine learning classifiers
The protection of private information is a crucial issue in data-driven research and business
contexts. Typically, techniques like anonymisation or (selective) deletion are introduced in …
contexts. Typically, techniques like anonymisation or (selective) deletion are introduced in …
Anonymization of centralized and distributed social networks by sequential clustering
T Tassa, DJ Cohen - IEEE Transactions on Knowledge and …, 2011 - ieeexplore.ieee.org
We study the problem of privacy-preservation in social networks. We consider the distributed
setting in which the network data is split between several data holders. The goal is to arrive …
setting in which the network data is split between several data holders. The goal is to arrive …
Identity obfuscation in graphs through the information theoretic lens
Analyzing the structure of social networks is of interest in a wide range of disciplines.
Unfortunately, sharing social-network datasets is often restrained by privacy considerations …
Unfortunately, sharing social-network datasets is often restrained by privacy considerations …
Anonymization in online social networks based on enhanced equi-cardinal clustering
Recent trends show that the popularity of online social networks (OSNs) has been
increasing rapidly. From daily communication sites to online communities, an average …
increasing rapidly. From daily communication sites to online communities, an average …
Privacy technology to support data sharing for comparative effectiveness research: a systematic review
Objective: Effective data sharing is critical for comparative effectiveness research (CER), but
there are significant concerns about inappropriate disclosure of patient data. These …
there are significant concerns about inappropriate disclosure of patient data. These …