APPLY NOW
Mukesh Patel School of Technology Management and Engineering
search
SM Handles:
Educational Qualification (highest):
  • PhD (Pursuing)
  • MTech ( Information Security and Computer Forensics)

Area of Research: Cybersecurity, Machine Learning, MedicalAI

Department: Computer Engineering

Basic Information:
  • Email Id: deepa.krishnan@nmims.edu
  • Landline extension: 114879
  • Desk (location): 401 Cubicle 13
Publications:

Journals

  1. Krishnan, D., Shrinath, P. Robust Botnet Detection Approach for Known and Unknown Attacks in IoT Networks Using Stacked Multi-classifier and Adaptive Thresholding. Arab J Sci Eng (2024). https://doi.org/10.1007/s13369-024-08742-y
  2. Vakadkar, K., Purkayastha, D. & Krishnan, D. Detection of Autism Spectrum Disorder in Children Using Machine Learning Techniques. SN COMPUT. SCI. 2, 386 (2021). https://doi.org/10.1007/s42979-021-00776-5

Conferences

  1. Soni, P., Tewari, Y., & Krishnan, D. (2022). Machine Learning approaches in stock price prediction: A systematic review. In Journal of Physics: Conference Series (Vol. 2161, No. 1, p. 012065). IOP Publishing.
  2. Nair, A., Paralkar, C., Pandya, J., Chopra, Y., & Krishnan, D. (2021, April). Comparative Review on Sentiment analysis-based Recommendation system. In 2021 6th International Conference for Convergence in Technology (I2CT) (pp. 1-6). IEEE.
  3. Falor, A., Hirani, M., Vedant, H., Mehta, P., & Krishnan, D. (2022). A deep learning approach for detection of SQL injection attacks using convolutional neural networks. In Proceedings of Data Analytics and Management: ICDAM 2021, Volume 2 (pp. 293-304). Springer Singapore.
  4. Krishnan, D., & Babu, P. (2021). Imbalanced classification for botnet detection in Internet of Things. In Next Generation of Internet of Things: Proceedings of ICNGIoT 2021 (pp. 595-605). Springer Singapore.

Chapters

  1. Krishnan, D., & Singh, S. (2022). Medical IoT: Opportunities, Issues in Security and Privacy-A Comprehensive Review. Smart and Secure Internet of Healthcare Things, 91-112.
  2. Singh, S., Vazirani, V., & Krishnan, D. (2022). Review of medical imaging with machine learning and deep learning-based approaches for COVID-19. Smart Health Technologies for the COVID-19 Pandemic: Internet of Medical Things Perspectives, 42, 261.