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Differentially Private Na ̈ive Bayes Classification

Jaideep Vaidya, Basit Shafiq, Anirban Basu, Yuan Hong

Privacy-preserving collaborative filtering on the cloud -- practical implementation experiences

Anirban Basu, Jaideep Vaidya, Hiroaki Kikuchi, Theo Dimitrakos

Reflections on Measuring the Trust Empowerment Potential of a Digital Environment

Natasha Dwyer, Anirban Basu, Stephen Marsh

Security Enhancement with Foreground Trust, Comfort, and Ten Commandments for Real People

Stephen Marsh, Anirban Basu, Natasha Dwyer

A concordance framework for building trust evidences

Anirban Basu, Natasha Dwyer, Stephen Naicken

Feasibility of a privacy preserving collaborative filtering scheme on the Google App Engine -- a performance case-study

Anirban Basu, Jaideep Vaidya, Theo Dimitrakos, Hiroaki Kikuchi

Perturbation based privacy preserving Slope One predictors for collaborative filtering

Anirban Basu, Jaideep Vaidya, Hiroaki Kikuchi

Rendering unto Cæ sar the Things that are Cæ sar's: Complex Trust Models and Human Understanding

Stephen Marsh, Anirban Basu, Natasha Dwyer

Scalable Privacy-Preserving Data Mining with Asynchronously Partitioned Datasets

In the Näive Bayes classification problem using a vertically partitioned dataset, the conventional scheme to preserve privacy of each …

Hiroaki Kikuchi, Daisuke Kagawa, Anirban Basu, Kazuhiko Ishii, Masayuki Terada, Sadayuki Hongo

Practical privacy preserving collaborative filtering on the Google App Engine

Anirban Basu, Jaideep Vaidya, Hiroaki Kikuchi, Theo Dimitrakos