Sharmila Subudhi

ORCID ID

Scopus ID

Researcher ID

Google Scholar ID
EXPERTISE INFORMATION

Research Group

Areas of Interest

Data Security, Anomaly Detection , Artificial Intelligence

Dr. Sharmila Subudhi

Assistant Professor–I, Computer Science

M.Tech., Ph.D.

sharmilasubudhi1@gmail.com

Biosketch

7873783109

11
Publications
2
Sponsored Projects

Doctoral Students
7
Courses Taught
PERSONAL INFORMATION

CourseYearUniversity
B.Tech. (CSE)2010Biju Patnaik University of Technology, Odisha
M. Tech. (IT)2012Biju Patnaik University of Technology, Odisha
Ph.D. (CSE)2019Veer Surendra Sai University of Technology, Burla, Odisha

PositionInstituteDuration
Assistant ProfessorMaharaja Sriram Chandra Bhanja Deo (MSCB) University, Baripada, OdishaJanuary 2022 ~ Current
Assistant ProfessorSiksha' O' Anusandhan University, Bhubaneswar, OdishaJanuary 2019 – January 2022
LecturerGandhi Institute For Technology, Bhubaneswar, OdishaJuly 2013-March 2014

TitleFunding AgencyAmountDurationCompleted / Ongoing
HealthWatch: Intrusion Detection in IoMT based Medical DevicesMukhyamantri Research Innovation for Extramural Research Funding (MRIP-2024) by Govt. of Odisha₹9,17,000/-2 yearsOngoing
Designing of Advance Intelligent Data driven framework for Mining Socioeconomic Factors Influencing Tribal Girl’s Education in Rural Mayurbhanj District of Northern OdishaUniversity Intramural Research Funded Project (UFIRP-2024) funded by MSCB University, Baripada, Odisha₹5,84,000/-1 yearCompleted

Paper CodePaper NameTeaching Years
CS-101Advanced C programming4
CS-103Advanced Data Structure and algorithms4
CS-106Indian Knowledge System2
CS-202Python Programming4
CS-206MATLAB Programming3
CS-302Advanced Java Programming4
CC-RData Analytics using R3

Type: M.Phil. / Ph.D.TitleEnrolled YearGraduated YearRole: Supervisor /Co-Supervisor
Data Hiding Using Digital Image Steganography And Watermarking2023Supervisor
Ph.D.Applied AI on Intrusion Detection System2023
Analysis of Network Intrusion using Deep Learning Techniques2024
Intrusion Detection in IoT-based Healthcare Industry Using Machine Learning Techniques2024

Senior Member (Indian National Academy of Engineering (INAE)) – 2025

  • ACM Member
  • IEEE, IEEE-WIE Member
  • Computer Society of India (CSI)
  • International Association of Engineers (IAENG)

Assistant Superintendent, Salandi Ladies Hostel-4, MSCBU 2022 – current

Journals

  • S. Subudhi, Ravindra G. Dabhade, Rajveer Shastri, Venkateswarlu Gundu, G.D. Vignesh, Abhay Chaturvedi (2023). Empowering sustainable farming practices with AI-enabled interactive visualization of hyperspectral imaging data, Measurement: Sensors, Elsevier, Volume 30, 100935, ISSN: 2665-9174, DOI: 10.1016/j.measen.2023.100935 [SCOPUS]
  • P. Dileep, M. Durairaj, S. Subudhi, V. V. R. Maheswara Rao, J. Jayanthi, D. Suganthi (2023). AI-driven drowned-detection system for rapid coastal rescue operations, Spatial Information Research, Springer, DOI: 10.1007/s41324-023-00549-7 [ESCI, SCOPUS]
  • M. Sudha, V. M. K. Reddy, W. Deva Priya, Shaik Mohammad Rafi, Sharmila Subudhi, S. Jayachitra (2023). Optimizing intrusion detection systems using parallel metric learning, Computers and Electrical Engineering, Elsevier, Volume 110, 108869, ISSN: 0045-7906, DOI: 10.1016/j.compeleceng.2023.108869 [Impact Factor: 4.0, SCIE, SCOPUS]
  • R. Bhukya, R. Shastri, S. S. Chandurkar, S. Subudhi, D. Suganthi, M. S. R. Sekhar (2023). Detection and classification of cardiac arrhythmia using artificial intelligence, International Journal of System Assurance Engineering and Management, Springer, DOI: 10.1007/s13198-023-02035-7 [ESCI, SCOPUS]
  • S. Subudhi and S. Panigrahi (2022). Application of OPTICS and Ensemble Learning for Database Intrusion Detection, Journal of King Saud University – Computer and Information Sciences, Elsevier, Vol. 34, Issue 3, pp. 972–981, DOI: 10.1016/j.jksuci.2019.05.001 [Impact Factor: 5.2, SCIE, SCOPUS]
  • S. Subudhi and S. Panigrahi (2020). Two-stage Automobile Insurance Fraud Detection using Optimized Fuzzy C-Means Clustering and Supervised Learning, International Journal of Information Security and Privacy, IGI Global, Vol. 14, Issue 3, pp. 18–37, DOI: 10.4018/IJISP.2020070102 [ESCI, SCOPUS]
  • S. Subudhi and S. Panigrahi (2020). Optimized Fuzzy C-Means Clustering and Supervised Classifiers for Automobile Insurance Fraud Detection, Journal of King Saud University – Computer and Information Sciences, Elsevier, Vol. 32, Issue 5, pp. 568–575, DOI: 10.1016/j.jksuci.2017.09.010 [Impact Factor: 5.2, SCIE, SCOPUS]
  • S. Subudhi and S. Panigrahi (2018). Hybrid Mobile Call Fraud Detection Model using Optimized Fuzzy C-Means Clustering and GMDH Network, Vietnam Journal of Computer Science, World Scientific, Vol. 5, Issue 3–4, pp. 205–217, DOI: 10.1007/s40595-018-0116-x [ESCI, SCOPUS]
  • S. Subudhi and S. Panigrahi (2018). Detection of Automobile Insurance Fraud using Feature Selection and Data Mining Techniques, International Journal of Rough Sets and Data Analysis, IGI Global, Vol. 5, No. 3, pp. 1–20, DOI: 10.4018/IJRSDA.2018070101
  • S. Subudhi, S. Panigrahi and T. K. Behera (2016). Detection of Mobile Phone Fraud using Possibilistic Fuzzy C-Means Clustering and Hidden Markov Model, International Journal of Synthetic Emotions, IGI Global, Vol. 7, No. 2, pp. 23–44, DOI: 10.4018/IJSE.2016070102
  • S. Subudhi and S. Panigrahi (2016). Use of Fuzzy Clustering and Support Vector Machine for Detecting Fraud in Mobile Telecommunication Networks, International Journal of Security and Networks (IJSN), Inderscience, Vol. 11, Nos. 1/2, pp. 3–11, DOI: 10.1504/IJSN.2016.075069 [SCOPUS]

S. Panigrahi, H. Swapnarekha, S. Subudhi (2023). GACO: A Genetic Algorithm with Ant Colony Optimization—Based Feature Selection for Breast Cancer Diagnosis. In: Nayak, J., Das, A.K., Naik, B., Meher, S.K., Brahnam, S. (eds) Nature-Inspired Optimization Methodologies in Biomedical and Healthcare. Intelligent Systems Reference Library, vol 233. Springer, Cham. https://doi.org/10.1007/978-3-031-17544-2_12.

  • D. Rana and S. Subudhi (2026). A hybrid two-stage ensemble model for detecting intrusion in IoIT environment. In Artificial Intelligence Sustainable Innovation (Vol. 2), Taylor & Francis, DOI: 10.1201/9781003654483-1
  • R. C. Shit and S. Subudhi (2025). AI-Powered Anomaly Detection with Blockchain for Real-Time Security and Reliability in Autonomous Vehicles. In 2025 IEEE Space, Aerospace and Defence Conference (SPACE), Bangalore, India, pp. 1–6, DOI: 10.1109/SPACE65882.2025.11170917
  • S. N. Bal and S. Subudhi (2025). Efficient watermarking framework using cryptography and bit substitution. In CRC Press eBooks, pp. 238–243, DOI: 10.1201/9781003581215-48
  • S. Panigrahi and S. Subudhi (2025). Online auction fraud detection using deep learning network. In CRC Press eBooks, pp. 163–166, DOI: 10.1201/9781003581215-33
  • D. Rana and S. Subudhi (2024). A balanced ensemble approach towards network intrusion in IoT environment. In 2024 IEEE 21st India Council International Conference (INDICON), pp. 1–5, DOI: 10.1109/INDICON63790.2024.10958490
  • J. Tripathy and S. Subudhi (2024). Effect of data imbalance in telecom fraud. In International Conference on Computational Intelligence in Pattern Recognition, pp. 221–232, Springer, Singapore, DOI: 10.1007/978-981-97-8093-8_16
  • S. N. Bal and S. Subudhi (2024). Secured watermarking framework using cryptography and pixel scheming. In International Conference on Computational Intelligence in Pattern Recognition, pp. 221–232, Springer, Singapore, DOI: 10.1007/978-981-97-8093-8_17
  • A. Dash, K. Naik, S. Subudhi (2023). Digital watermarking using visual cryptography. In Computational Intelligence in Pattern Recognition (CIPR 2022), Lecture Notes in Networks and Systems, vol. 725, Springer, Singapore, DOI: 10.1007/978-981-99-3734-9_5
  • S. Das, J. Nayak, S. Subudhi (2022). An impact study on COVID-19 with sustainable sports tourism: intelligent solutions, issues and future challenges. In Computational Intelligence in Pattern Recognition (CIPR 2022), LNNS vol. 480, Springer, Singapore, DOI: 10.1007/978-981-19-3089-8_57
  • S. Panigrahi, S. Subudhi, and S. Z. Ninoria (2022). A comprehensive performance analysis on artificial neural networks. In 2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART), IEEE, pp. 489–495, DOI: 10.1109/SMART55829.2022.10047509
  • A. Das and S. Subudhi (2022). Effect of class imbalanceness in credit card fraud. In Intelligent and Cloud Computing, Smart Innovation, Systems and Technologies, vol. 286, Springer, Singapore, pp. 471–480, DOI: 10.1007/978-981-16-9873-6_43
  • S. Sharma, A. Ghosh, and S. Subudhi (2022). Hand sign language detection using deep learning. In Advances in Distributed Computing and Machine Learning, LNNS vol. 302, Springer, Singapore, pp. 493–502, DOI: 10.1007/978-981-16-4807-6_47
  • D. K. Patel and S. Subudhi (2019). Application of extreme learning machine in detecting auto insurance fraud. In 2019 International Conference on Applied Machine Learning (ICAML), Bhubaneswar, India, IEEE, pp. 78–81, DOI: 10.1109/ICAML48257.2019.00023
  • S. Subudhi and S. Panigrahi (2018). Effect of class imbalanceness in detecting automobile insurance fraud. In 2018 2nd International Conference on Data Science and Business Analytics (ICDSBA), Changsha, China, IEEE, pp. 528–531, DOI: 10.1109/ICDSBA.2018.00104
  • S. Subudhi and S. Panigrahi (2017). Use of possibilistic fuzzy C-means clustering for telecom fraud detection. In Computational Intelligence in Data Mining, Advances in Intelligent Systems and Computing, vol. 556, Springer, Singapore, pp. 633–641, DOI: 10.1007/978-981-10-3874-7_60
  • S. Subudhi, S. Panigrahi, and T. K. Behera (2017). Use of OPTICS and supervised learning methods for database intrusion detection. In IEEE Sponsored 3rd International Conference on Computational Intelligence and Networks (CINE 2017), DOI: 10.1109/CINE.2017.10
  • S. Subudhi and S. Panigrahi (2015). Quarter-sphere support vector machine for fraud detection in mobile telecommunication networks. Procedia Computer Science, Vol. 48, pp. 353–359, Elsevier, DOI: 10.1016/j.procs.2015.04.193