Ratna Babu Chekka

Work place: Dept. of Computer Science and Engineering, R.V.R & J.C College of Engineering, Guntur, India

E-mail: chekka.ratnababu@gmail.com


Research Interests: Computer systems and computational processes, Image Compression, Image Manipulation, Computer Networks, Information Security, Network Architecture, Network Security, Image Processing, Information-Theoretic Security


Ratna Babu Chekka received his B.Tech and M.Tech in Computer Science and Engineering from   R.V.R. & J.C.College of Engineering, Guntur. At present he is pursuing Ph.D. from Acharaya Nagarjuna University, Guntur. He is currently working as Associate Professor in the Department of Computer Science and Engineering at R.V.R. & J.C. College of Engineering, Guntur. He has 10 years of teaching experience. His research areas of interest include Cryptography & Network Security, Information Security, Computer Networks and Image Processing.

Author Articles
A Hybrid Algorithm for Privacy Preserving in Data Mining

By Sridhar Mandapati Raveendra Babu Bhogapathi Ratna Babu Chekka

DOI: https://doi.org/10.5815/ijisa.2013.08.06, Pub. Date: 8 Jul. 2013

With the proliferation of information available in the internet and databases, the privacy-preserving data mining is extensively used to maintain the privacy of the underlying data. Various methods of the state art are available in the literature for privacy-preserving. Evolutionary Algorithms (EAs) provide effective solutions for various real-world optimization problems. Evolutionary Algorithms are efficiently employed in business practice. In privacy-preserving domain, the existing EA solutions are restricted to specific problems such as cost function evaluation. In this work, it is proposed to implement a Hybrid Evolutionary Algorithm using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Both GA and PSO in the proposed system work with the same population. In the proposed framework, k-anonymity is accomplished by generalization of the original dataset. The hybrid optimization is used to search for optimal generalized feature set.

[...] Read more.
Other Articles