Announcement:

Dr.Sharmila B S

Assistant Professor

Department of Electronics & Communication Engineering

Email: sharmilabs@nie.ac.in
Phone No:
About Me:

Dr. Sharmila has delivered numerous technical talks and workshops on Python, Artificial Intelligence, and IoT, contributing significantly to knowledge dissemination. Her research publications, including works on Parallel DNN-based IDS frameworks, Quantized Autoencoder IDS, and optimizing deep learning for edge devices, are published in renowned journals such as Wiley's Security and Privacy and Springer's Cybersecurity.

Her academic qualifications include a B.E. from Kalpataru Institute of Technology and an M.Tech. from Sri Jayachamarajendra College of Engineering, Mysuru. Dr. Sharmila teaches a variety of courses, including Data Structures, IoT, Embedded Systems, and Ethical Hacking. Her research and teaching continue to make substantial contributions to the fields of cybersecurity and IoT technology.
  • B.E. degree from . Kalpataru Institute of Technology, Tiptur (VTU, Belagavi )
  • M.Tech. degree from Sri Jayachamarajendra College of Engineering, Mysuru (VTU, Belagavi)
  • Ph.D. degree from Visvesvaraya Technological University, Belagavi
  • Assistant Professor
  • Received “1970 Alumni- Award for Best Publication" during 2024-25
Publications
  • B S Sharmila, Rohini Nagapadma. "P-DNN: Parallel DNN based IDS framework for the detection of IoT vulnerabilities." Security and Privacy, Wiley: e330. https://onlinelibrary.wiley.com/doi/abs/10.1002/spy2.330 [Web of Science- ESCI].
  • B S Sharmila, Rohini Nagapadma. "Quantized Autoencoder (QAE) Intrusion Detection System for anomaly detection in resource constrained IoT devices using RT-IoT2022 dataset.", Cybersecurity, Springer, https://cybersecurity.springeropen.com/articles/10.1186/s42400-023-00178-5  [Web of Science-ESCI, Scopus Q1 journal]
  • B S Sharmila, Rohini Nagapadma. "QAE-IDS: DDoS anomaly detection in IoT devices using Post-Quantization Training", Smart Science, 1-16. (2023). https://doi.org/10.1080/23080477.2023.2260023  [Web of Science-ESCI, Scopus-Q3 journal]
  • B S Sharmila , Santhosh, H. S., Parameshwara, S., Swamy, M. S., Baig, W. H., & Nanditha, S. V. (2023). Optimizing Deep Learning Networks for Edge Devices with an Instance of Skin Cancer and Corn Leaf Disease Dataset. SN Computer Science, 4(6), 793. https://doi.org/10.1007/s42979-023-02239-5  [Scopus-Q2 journal].
  • B S Sharmila., et al. "Performance Evaluation of Parametric and Non-Parametric Machine Learning Models using Statistical Analysis for RT-IoT2022, Journal of Scientific & Industrial Research (JSIR) 83.8 (2024): 864-872. [SCIE, Scopus Journal]
 

Conference Proceedings:

  • B S Sharmila, Rohini Nagapadma "Intrusion Detection System using Naive Bayes Algorithm", WIECON-2019. https://ieeexplore.ieee.org/document/9019921 [Scopus].
  • B S Sharmila, Rohini Nagapadma "KNN classication using Multi-core Architecture for Intrusion Detection System", International Conference on Communication and Computing Systems (ICCCS - 2018), https://www.taylorfrancis.com/chapters/edit/10.1201/9780429444272-7/  [Scopus]
        • Research Project under Special Call for Vision Viksit Bharat@2047 from ICSSR – 12 Lakh – 2024-25
        • 6G project under TTDF Scheme from TCOE Agency, Department of Telecommunication, India – 20 Lakh 2024-25

UG Courses:

  • Data Structures using C++
  • Internet of Things
  • Embedded Systems
  • Basic Electronics

PG Courses:

  • Information and Network Security
  • Ethical hacking and penetration testing