Privacy-preserving data mining has attracted the attention of a large number of researchers.
Many data perturbation methods have been proposed to ensure individual privacy. Such …

While an important factor in depth perception, the occlusion effect in 3D environments also
has a detrimental impact on tasks involving discovery, access, and spatial relation of objects …

Privacy preserving in data publishing has become one of the most important research topics
in data security field and it has become a serious concern in publication of personal data in …

We propose an efficient framework for enabling secure multi-party numerical computations
in a Peer-to-Peer network. This problem arises in a range of applications such as …

Privacy preserving becomes an important issue in the development of various data mining
techni'ques. In this paper, we have discussed various techniques to preserve privacy while …

E-commerce companies utilize collaborative filtering approaches to provide
recommendation in order to attract customers. Consumer participation through supplying …

We propose an efficient framework for enabling secure multi-party numerical computations
in a Peer-to-Peer network. This problem arises in a range of applications such as …

Data perturbation is a sanitization method that helps restrict the disclosure of sensitive
information from published data. We present an attack on the privacy of the published data …

Sequential patterns mining from data is a well stated data mining problem. It has a number
of applications such as DNA sequencing, signal processing, speech analysis etc. In this …

Growing concerns amongst the competitors for maintaining the privacy of their customer's
information has increased in recent years. Multiple parties desire to collaborate to conduct …