Dr B Devipriya

R.V.S. Polytechnic College, Dindigul Lecturer 06/11/2006
to 31/7/2007 9 Mths
R.V.S. College of Engg & Tech., Dindigul
Anna University Lecturer 1/8/2007 to 25/04/2008 9 Mths
GuruNanak College(Evening) in BCA dept Asst. Professor 10/8/2008 to 31/1//2012 3 Yrs 5 Mths
IGNOU Academic Counselor 2009 to2011 2 Yrs
GuruNanak College (Shift-II) in BSc Computer Science Asst. Professor 03/07/2014 to 30/04/2018
3 Yrs 10 Mths
Vel’s Institute of Science, Technology and Advanced Studies Asst Professor 01/02/2019 to till now 2 years 7 months

EDUCATION

2016-2020 Ph. D Computer Science Computer Science
2010-2011 Prist University, Chennai M.Phil.
2003-2006 R.V.S. College of Engg & Tech., Dindigul
Anna University M.C.A
2000-2003 GTN Arts College, Dindigul
Madurai Kamaraj University B.Sc. Physics

RESEARCH INTERESTS

Data Mining, Machine Learning

Scopus Publications

Securing data transmission against multi cell MIMO Eavesdropper in 5G wireless networks using moSPR
S Nirupama, R Harini, K Akshaya, B Devipriya, Sahaya Beni Prathiba, and Gunasekaran Raja
IEEE
The next generation network (5G) promises to offer a wide spectrum of advantages like massive user connections and high mobility. Massive user connection is achieved by incorporating Multiple Input Multiple Output (MIMO). Securing 5G wireless networks is of greater concern because they are developed with the intention of providing exponentially increasing wireless services where a trillion of legitimate users will be involved. Data transmission in 5G networks has been exposed to various security threats such as eavesdropping, jamming, Denial of Service (DoS) attack and Man-In-The-Middle (MITM) attack. The above mentioned threats have the ability of affecting the performance of 5G wireless networks since 5G is a major support system for new use cases. Some of the existing mechanisms employed to deal with the security threats are Physical Layer Security (PLS) and cryptography. PLS is preferred since its primary focus is on physical and Media Access Control (MAC) layer where variations in security between wireless and wired networks occur. The existing PLS approach for security against single cell MIMO eavesdropper is Original Symbol Phase Rotated (OSPR) secure transmission scheme where one base station serves the user terminals in a single cell. Our paper implements OSPR for a multi cell MIMO where multiple base stations serve multiple user terminals located in different cells. This architecture will be referred to as Multi cell MIMO Eavesdropping (MME). The efficiency of multi cell OSPR will be compared with Artificial Noise (AN) generation. The extent to which OSPR gives protection against MIMO eavesdropper is measured in terms of Symbol Error Rate (SER). As SER increases, security of data transmission increases. The efficiency of multi cell OSPR over AN is expected to be 8% and it will be verified in simulation using MATLAB.


Evaluation of sentiment data using classifier model in rapid miner tool
Devipriya B, , Dr Kalpana Y, and
Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
Evaluation of internet and the usage of internet as websites which is for penetrating to gain a specific requirements, like group communication as social networks (such as face book, twitter,etc.,) ,blogs for opinions, online portals (such as iGoogle, MSN) for communication, experience as reviews, suggestions as opinions, combination of reviews and opinions as recommendations, ratings and feedbacks which is identified and elevating in almost all the field now-a-days. The writers of online portal, review, opinion and recommendation in any social media take measures as beneficial factor for the improvement of businesses, organization, governments and mostly individuals. When this content boost up the study of content and the need of data mining, text mining techniques and sentiment analysis is inescapable. Natural language processing and text analysis techniques are used in sentiment analysis to recognize and extract information from the text [1]. This paper provides a result of sentiment analysis with the intellectual tool named Rapid Miner to show the sentiment comments about the contents in the online traders.


A survey on recommender system based on machine learning concepts and semantic analysis

Publications

1. B Devipriya, J Priscilla Sasi, “Extracting Positive and Negative Association Rules”, 6th International Conference on Transition from Interia to Implementation-I4, Volume 1, Special Issue-1, September 2014. ISSN 23484705 (Conference).
2. B Devipriya, Dr Y Kalpana, “A Novel Approach in Collaborative E-commerce Scenarios with a detailed study of commercial concerns in Today’s era”, International conference on Recent Trends in Science and Management (ICRTSM’18), November 2018, ISBN no: 9788193221358 (Conference).
3. B Devipriya, Dr Y Kalpana,” Confrontation and Dissection on E-Retailing Sales Chart using Process Mining Tools”, “, International Journal of Innovative Research in Applied Sciences and Engineering (IJIRASE), Volume1, Issue 10, Apr-2018, ISSN: 2456-8910 (UGC).
4. B Devipriya, Dr Y Kalpana, Confrontation on Health Insurance Claim Process using Process Mining Tools”, International Journal of Management, Technology and Engineering, Volume 9, Issue 3, Mar-2019, ISSN :2249-7455 (Conference/Journal).
5. Dr Y Kalpana, A.Ashik Mohamed, B Devipriya “GEO-Positioning and Tagging using Collective Saptial Keyword Query”, CIKITUSI Journal for Multidisciplinary Research, Volume 6, Issue 5, May-2019, ISSN: 0975-6876 (UGC) .
6. B Devipriya, Dr Y Kalpana,” A Survey on Recommender System based on Machine Learning Concepts and Semantic Analysis”, Journal of Advance Research in Dynamical & Control Systems, Vol. 11, 07-Special Issue, July 2019, ISSN 1943-023X (Scopus).
7. B Devipriya, Dr