Privacy Preserving Optics Clustering

Kondra, Janardhan Reddy (2016) Privacy Preserving Optics Clustering. MTech thesis.

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Abstract

OPTICS is a well-known density-based clustering algorithm which uses DBSCAN theme without producing a clustering of a data set openly, but as a substitute, it creates an augmented ordering of that particular database which represents its density-based clustering structure. This resulted cluster-ordering comprises information which is similar to the density based clustering’s conforming to a wide range of parameter settings. The same algorithm can be applied in the field of privacy-preserving data mining, where extracting the useful information from data which is distributed over a network requires preservation of privacy of individuals’ information. The problem of getting the clusters of a distributed database is considered as an example of this algorithm, where two parties want to know their cluster numbers on combined database without revealing one party information to other party. This issue can be seen as a particular example of secure multi-party computation and such sort of issues can be solved with the assistance of proposed protocols in our work along with some standard protocols.

Item Type:Thesis (MTech)
Uncontrolled Keywords:Density based clustering; Privacy preserving; OPTICS; Distributed data; Secure multi-party computation.
Subjects:Engineering and Technology > Computer and Information Science > Information Security
Divisions: Engineering and Technology > Department of Computer Science
ID Code:8539
Deposited By:Mr. Sanat Kumar Behera
Deposited On:29 Aug 2017 21:11
Last Modified:29 Aug 2017 21:11
Supervisor(s):Korra, Sathya Babu

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