Qualification: 
M.Tech, BE
Email: 
b_sreevidya@blr.amrita.edu

MS. Sreevidya B. currently serves as Assistant Professor in the Department of Computer Science and Engineering, Amrita School of Engineering, Bengaluru. She is currently pursuing her Ph. D. in Amrita Vishwa Vidyapeetham. She is with Amrita Vishwa Vidyapeetham for more than 13 years now. She completed her Bachelor’s and Master’s in Computer Science and Engineering from Visveswaraiah Technological University, Bengaluru. Her research interests include Data Security and Energy Optimization of nodes in Wireless Sensor Networks. Her interest also spans in the area of Data Mining.

Education

  • Currently pursuing Ph.D.
  • 2018: M.Tech. in Computer Science and Engineering
    From: Visvesvaraya Technological University (VTU), Karnataka
  • 2005: B.Tech. in Computer Science and Engineering
    From: Visvesvaraya Technological University (VTU), Karnataka

Professional Appointments

Year

Affiliation

2006 till date

Amrita School of Engineering, Bengaluru Campus, AVV (Deemed University)

Major Research Interests

  • Wireless Sensor Networks, Data Security, Data Mining

Publications

Publication Type: Journal Article

Year of Publication Title

2020

B. Sreevidya, Singh, M. Pratap, and Sangeeta, D. K., “HARDWARE SETUP FOR VLC BASED VEHICLE TO VEHICLE COMMUNICATION UNDER FOG WEATHER CONDITION”, International Journal of Advanced Science and Technology, 2020.

2018

A. M.S.K., Dr. Amrita Thakur, Dr. Deepa Gupta, and B. Sreevidya, “Time series analysis of air pollution in bengaluru using ARIMA model”, Advances in Intelligent Systems and Computing, vol. 696, pp. 413-426, 2018.[Abstract]


Air pollution control measures in India are still in its infancy, while the country is developing at a faster rate. Development is known to affect the air quality of a place adversely. The key to manage the air quality of a place is proper planning, and for that, robust forecasting system based on continuous monitoring is required. Bengaluru is a city which has grown in size and population in the past decades. This rapid growth has affected its environmental quality. The present work deals with development of air quality prediction model based on Autoregressive Integrated Moving Average (ARIMA). For this, pollution data of NO2, PM10 and SO2 from January 2013 to March 2016, 14 pollution monitoring stations has been used. The results show that data which satisfies the stationary condition can be used as an accurate prediction model. NO2 residential and RSPM residential satisfy this condition. © Springer Nature Singapore Pte Ltd. 2018.

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2015

B. Sreevidya, “An enhanced and productive technique for privacy preserving mining of association rules from horizontal distributed database”, International Journal of Applied Engineering Research, vol. 10, pp. 39126-39130, 2015.[Abstract]


The past two decades has seen a dramatic increase in the amount of information or data being stored in electronic format. This accumulation of data has taken place at an explosive rate. It has been estimated that the amount of information in the world doubles every 20 months and the size and number of databases are increasing even faster. The increase in use of electronic data gathering devices such as point-of-sale or remote sensing devices has contributed to this explosion of available data. Data confidentiality is a major concern in database systems especially when are huge amounts of data to be processed, so we try to implement a system where we could preserve security and maintain data confidentiality. Further there is a huge trend today towards distributed databases which make data mining very easy, reliable and efficient. In our paper we implement Fast Distributed Mining of Apriori algorithm for mining this huge transactional dataset. With the help of this algorithm we find the frequent item sets that are consumed in all transaction. Finding this frequent item sets in very important. By knowing this frequent item sets one can understand the interest of consumers and focus in profiting his business by mining association rules from them. In other words association rules can be used for decision making. © Research India Publications.

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Publication Type: Book Chapter

Year of Publication Title

2020

Sasikala T, Rajesh M, and B. Sreevidya, “Prediction of Academic Performance of Alcoholic Students Using Data Mining Techniques”, in Cognitive Informatics and Soft Computing, vol. 1040, P. Kumar Mallick, Balas, V. Emilia, Bhoi, A. Kumar, and Chae, G. - S., Eds. Singapore: Springer Singapore, 2020, pp. 141-148.[Abstract]


Alcohol consumption by students has become a serious issue nowadays. Addiction to alcohol leads to the poor academic performance of students. This paper describes few algorithms that help to improve the efficiency of academic performance of students addicted to alcohol. In the paper, we are using one of the popular Data Mining technique–-``Prediction'' and finding out the best algorithm among other algorithms. Our project is to analyze the academic excellence of the college professionals by making use of WEKA toolkit and R Studio. We implement this project by making use of alcohol consumption by student datasets provided by kaggle website. It is composed of 395 tuples and 33 attributes. A classification model is built by making use of Naïve Bayes and ID3. Comparison of accuracy is done between R and WEKA. The prediction is performed in order to find out whether a student can be promoted or demoted in the next academic year when previous year marks are considered.

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2020

Rajesh M and B. Sreevidya, “Vulnerability Analysis of Real-Time Operating Systems for Wireless Sensor Networks”, in Advanced Computing and Intelligent Engineering, vol. 1089, B. Pati, Panigrahi, C. Rani, Buyya, R., and Li, K. - C., Eds. Singapore: Springer Singapore, 2020, pp. 449-460.[Abstract]


The faultless operation of systems which are safety-critical like the anti-lock braking system (ABS), fuel control system (especially during cruise control), traction control system, etc., is equally dependent on both the logical as well as the temporal correctness of the output generated, and hence, systems like these can be called as the real-time systems (RTS), specifically, hard real-time systems. In this paper, various security issues relevant to such automotive systems have been studied and tested. Based on the observations made, a feasibility study is done on using OSEK/VDX for wireless sensor network applications

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2019

B. Sreevidya and Rajesh M, “Design and Performance Evaluation of an Efficient Multiple Access Protocol for Virtual Cellular Networks”, in Lecture Notes on Data Engineering and Communications Technologies, vol. 15, 2019, pp. 295-304.

2018

M. S. K. Abhilash, Thakur, A., Gupta, D., and B. Sreevidya, “Time series analysis of air pollution in Bengaluru using ARIMA model”, in Ambient Communications and Computer Systems, 2018, pp. 413-426.

2018

B. Sreevidya, Rajesh M, and Mamatha, T. M., “Design and development of an enhanced security scheme using RSA for preventing false data injection in wireless sensor networks”, in Advances in Intelligent Systems and Computing, vol. 696, , Ed. Springer Verlag, 2018, pp. 225-236.[Abstract]


Wireless sensor networks are largely used in mission-critical applications such as border surveillance, intrusion detection, remote patient monitoring. These applications demand the data to be secured while processing as well as communicating. Data security during the processing phase is a largely researched area, and there exists enough number of techniques to achieve it. On the other hand, techniques to achieve data security during communication phase even though exist in multiple numbers, most of the techniques demand high processing capacity. This requirement leads to high energy consumption which is a challenge in the context of wireless sensor networks. So a technique which will provide data security during communication phase in a wireless sensor network-based application with minimal energy consumption will be a very good solution. The proposed scheme is to prevent false data injection in which malicious or compromised nodes inject false data into the WSN which will influence the decision making of the system. The proposed system provides an enhanced security scheme for preventing false data injection attack in WSN with an efficient reactive routing method. The proposed system addresses two parameters: authenticity of the nodes and the integrity of the data. The proposed system is simulated using Network Simulator 2 (NS2), and the results indicate that the scheme performs better than the existing schemes which provide either integrity of data or authentication of the sender. © Springer Nature Singapore Pte Ltd. 2018.

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Publication Type: Conference Proceedings

Year of Publication Title

2019

Rajesh M, B. Sreevidya, and Sasikala T, “Performance Analysis of Various Anonymization Techniques for Privacy Preservation of Sensitive Data”, Lecture Notes on Data Engineering and Communications Technologies, vol. 26. pp. 687-693, 2019.

2018

B. Sreevidya and Rajesh M, “False Data Injection Prevention in Wireless Sensor Networks using Node-level Trust Value Computation”, 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI). 2018.

2017

B. Sreevidya and Rajesh M, “Enhanced Energy Optimized Cluster Based On Demand Routing Protocol for Wireless Sensor Networks”, 6th International Conference on Advances in Computing, Communications & Informatics (ICACCI’17). IEEE, Manipal University, Karnataka , 2017.[Abstract]


Wireless sensor networks (WSN) are widely used various applications such as disaster management, search and rescue operation, wild life monitoring, remote patient monitoring, structural health monitoring etc. It provides bridge between the real physical and virtual worlds. In many scenarios, the coverage area of the WSN will be very large and a multi-hop adhoc network needs to be maintained for the connectivity and data transfer among the nodes. The major part of the energy consumption of each node is used for data transfer among nodes. This paper proposes a energy efficient routing scheme. The scenario which is considered is a wireless sensor network which is a collection of clusters and data transfer happens with the help of cluster head (CH) rather than the collective effort of every node in the network. In such a cluster based WSN, it is advantageous to have a routing protocol which uses the information about clusters to decide upon route formation. This paper proposes a novel Cluster Based Routing Protocol for a WSN which optimizes the energy consumption on data transfer and thus increasing the lifetime of the WSN network. To conclude the advantages of the proposed scheme, comparison is carried out between the performance of AODV and CBRP protocols.

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2017

D. Paliwal and B. Sreevidya, “Design and development of an intelligent web application for direct consumer to consumer trading over internet”, Proceedings of the International Conference on Inventive Communication and Computational Technologies, ICICCT 2017. Institute of Electrical and Electronics Engineers Inc., pp. 56-58, 2017.[Abstract]


The sudden change in information technology has provided facility of trading in the Internet. There are several platforms available for trading but there is no suitable platform available for direct consumer-to-consumer trading mainly for students studying in a university so that they are able to purchase, sell their goods and make use of various services within the university. So this helps students by providing the facility of easy exchange within a small social network. The mostly used websites for example Snapdeal, Ebay, Flipcart are very global hence does not facilitate the trade and exchange of goods directly among the customers in a small community like campus environment. In this project an innovative approach is used by performing sequence of steps which are recording user profile, performing content and collaborative filtering, and user transactions and applies association rule mining on the buying transactions. Finally the intersection is performed between association manning results and collaborating mining results which provides the recommendations for the customer.

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Courses Taught

  • Problem Solving and Algorithmic Thinking
  • Computer Programming
  • Object Oriented Programming
  • Database Management Systems
  • Operating Systems
  • Software Engineering
  • Software Project Management
  • Software Testing
  • Data Mining
  • Computer Networks

Student Guidance

Undergraduate Students

Sl. No. Name of the Student(s) Topic Status – Ongoing/Completed Year of Completion
1 Mihir Koundinya Raghu Vamsi Ganesh Phanindra Thania Vivek Performance Analysis of Machine Learning Algorithm for prediction of Disease based on Patient Data Completed 2021
2 Aravind V. Nair Akhila Sajani Dandu Spot the Hole Completed 2021
3 Aashrith Palathoti Lakshman Venkat Sai Image Caption Generator Completed 2021
4 M. Arun Rajesh M. Sai Surya Teja M. Sai Nikhil Speech to emotion recognition Completed 2021
5 Reddygari Showmya Thiriveedhi Rishitha Vadla Sushma Sree Power Aware Routing Protocol in WSN Completed 2020
6 Rohith R. Chetan Krishna Social Network Analysis Completed 2020
7 G. Jaswanth D. Chandramouli Sai Hrishikesh Election Analysis using Deep Learning Completed Completed 2019
8 Nitin Bhagat Parvathy Sunil Shubham Silswal  False Data Injection Prevention Scheme using Computation to Identify Trusted Nodes Completed 2018
9 Amritha A. M. Vaishnavi Meenakshy V.P Integrity and Security of the data transmitted with Energy Optimization in WSN Completed 2017
10 M. Sai Rohith  P.N. Nitin Reddy D. Abhishikth Sagar Weather Forecasting and Rainfall Prediction using Data Mining   2017

Postgraduate Students

Sl. No. Name of the Student(s) Topic Status – Ongoing/ Completed Year of Completion
1 Manish Pratap Singh Advanced Driver Assistance Based on Vehicle to Vehicle Communication for Fog Weather Condition Completed 2019
2 Venkateswarao Tella An Energy Efficient Wireless Sensor Node Deployment for Maximizing the Coverage by Optimizing through PSO Completed 2020