REGISTRATION OPEN FOR MD/MS & MDS PROGRAMMES Apply Now

Admissions Open Apply now

icon

Amrita

Assistant Professor, Computer Science and Engineering (CSE)

amrita.prasad@sharda.ac.in

About

Amrita received her Ph.D. in Computer Science and Engineering from Sharda University, Greater Noida, India and M.Tech in Computer Science from Banasthali Vidyapith, Rajasthan, India.  She is currently working as an Assistant Professor in the Department of Computer Science and Engineering, School of Engineering and Technology, Sharda University. She has more than 13 years of experience in academic and research in addition to 5 years of Industry experience. She has published papers in refereed journals, international conferences and book chapter. Her research interests include Intrusion Detection System, Soft Computing, Machine Learning, Data Mining, Pattern Recognition, Hybrid System, Feature Selection, Cyber Security, Network Security.

Experience
  • 18 years
Qualification
  • Ph. D. (Computer Science and Engineering)
  • M. Tech (Computer Science)
Research

  • Amrita, Shri Kant, “Machine Learning and Feature Selection Approach for Anomaly based Intrusion Detection: A Systematic Novice Approach”, International Journal of Innovative Technology and Exploring Engineering (IJITEE), Vol. 8, Issue-6S, pp. 434-443, 2019.
  • Amrita and Kiran Kumar Ravulakollu, “A Hybrid Intrusion Detection System: Integrating Hybrid Feature Selection Approach with Heterogeneous Ensemble of Intelligent Classifiers”, International Journal of Network Security, Vol.20, No.1, pp. 41-55, 2018.
  • F. L. Bello, K. Ravulakollu and Amrita, "Analysis and evaluation of hybrid intrusion detection system models," 2015 International Conference on Computers, Communications, and Systems (ICCCS), Kanyakumari, pp. 93-97, 2015.
  • Amrita & P Ahmed, A Hybrid-Based Feature Selection Approach for IDS, Springers-LNEE proceedings of 5th International Conference on networks & Communications (NETCOM-2013), Vol. 284, pp. 195-211, 2014,.
  • Sneh Lata Pundir & Amrita, Feature Selection Using Random Forest in Intrusion Detection System, International Journal of Advances in Engineering & Technology (IJAET), Vol. 6(3), pp. 1319-1324, 2013.
  • Megha Aggarwal & Amrita, Performance Analysis of Different Feature Selection Methods In Intrusion Detection, International Journal of Scientific & Technology Research (IJSTR), Vol. 2(6), pp. 225-231, 2013.
  • Megha Aggarwal & Amrita, Fusion of Statistic, Data Mining and Genetic Algorithm for feature selection in Intrusion Detection, International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), Vol.2(5), pp. 1725-1731, 2013.
  • Amrita & P Ahmed, A Study of Feature Selection Methods in Intrusion Detection System: A Survey, International Journal of Computer Science Engineering and Information Technology Research (IJCSEITR), Vol.2(3), pp. 1-25, 2012

Book Chapters:

  • Amrita & P Ahmed, A Hybrid-Based Feature Selection Approach for IDS, In: Networks and Communications, Springer International Publishing, Vol 284, 195-211, 2014

Certifications

  • The Dale Carnegie Certification for High Impact Teaching Skills.

Area of Interest

  • Operating System
  • Soft Computing
  • Machine Learning
  • Pattern Recognition
  • Data Mining
  • Data Warehouse
  • Computer Networks
  • Data and Network Security
  • Compiler Design
  • Web Technologies
  • Java