DEEPA KRISHNAN

Assistant Professor with 14 years experience recognized for high productivity and efficiency in task completion. Specializes in curriculum development, academic research, and student mentorship, with a strong research interest in cybersecurity and machine learning. Skilled in communication, critical thinking, and collaboration, ensuring success in both individual initiatives and team projects. Courses taught include Computer Networks, Mobile Computing, Information Security, Cyber Security, and Ethical Hacking.

IoT Botnet Detection, Computationally efficient feature selection techniques, Addressing class imbalance, Class-wise feature selection, Detecting unseen attacks, Evaluating adversarial robustness,  Novel multi-stage feature selection method, Algorithmic Weighted approach to severe imbalance problems, Modified matrix learning vector quantization approach, Reconstruction error thresholding technique for detecting unseen attacks, Evaluation of adversarial attack severity under popular gradient-based attacks

• Krishnan, D., Shrinath, P. Robust Botnet Detection Approach for Known and Unknown Attacks in IoT Networks Using Stacked Multi-classifier and Adaptive Thresholding. Arabian Journal of Science and Engineering , Springer, 2024.[Q1]
• Krishnan D, Shrinath, P. Robust IoT Botnet Detection Framework Resilient to Gradient Based Adversarial Attacks, S.N Computer Science, Springer Nature, 2024 [Q2] [Accepted for Publication]
• Krishnan D, Bishnoi A, Bansal S, Ravi V, Ravi P. Enhancing Classification of Alzheimer’s Disease using Spatial Attention Mechanism. The Open Neuroimaging Journal, Bentham Open, 2024; 17: e18744400305746 [Q4]
• Shah, V. N., Shah, D. R., Shetty, M. U., Krishnan, D., Ravi, V., Singh, S., Investigation of imbalanced sentiment analysis in voice data: a comparative study of machine learning algorithms, EAI Endorsed Transactions on Scalable Information Systems, 2024 [Q4]
• Pal V, Pabari H, Indoria S, Patel S, Krishnan D, Ravi V. Multifaceted Disease Diagnosis: Leveraging Transfer Learning with Deep Convolutional Neural Networks on Chest X-Rays for COVID-19, Pneumonia, and Tuberculosis. Open Bioinformatics Journal, 2024; 17: e18750362303182[Q4]
• Singh S, Vazirani V, Singhania S, Singh V, Soni V, Biwalker A, Krishnan D, Beyond Boundaries: Unifying Classification and Segmentation in Wildfire Detection Systems, Multimedia Tools and Applications, Springer,2024 [Q1]
• Vakadkar, K., Purkayastha, D., Krishnan, D., Detection of autism spectrum disorder in children using machine learning techniques, SN Computer Science, Springer, Vol2, 1-9, 2021[Q2]

• · Verma, P., Deshmukh, K., Krishnan, D., Multiclass classification of liver diseases using optimized machine learning classifiers, 2023 International Conference on Computational Intelligence and Knowledge Management (CIKM), 1-6, 2023
• · Soni, P., Tewari, Y., Krishnan, D., Machine learning approaches in stock price prediction: a systematic review, Journal of Physics: Conference Series, 2161, 1, 012065, 2022
• · Falor, A., Hirani, M., Vedant, H., Mehta, P., Krishnan, D., A deep learning approach for detection of SQL injection attacks using convolutional neural networks, Proceedings of Data Analytics and Management: ICDAM 2021, 2, 293-304, 2022
• · Nair, A., Paralkar, C., Pandya, J., Chopra, Y., Krishnan, D., Comparative review on sentiment analysis-based recommendation system, 2021 6th International Conference for Convergence in Technology (I2CT), 1-6, 2021
• · Krishnan, D., Babu, P., Imbalanced classification for botnet detection in Internet of Things, Next Generation of Internet of Things: Proceedings of ICNGIoT 2021, 595-605, 2021
• · Krishnan, D., Detection of denial-of-service attacks using stacked LSTM networks, Proceedings of Data Analytics and Management: ICDAM 2021, 2, 229-239, 2022
• · Krishnan, D., Singh, S., Cost-sensitive bootstrapped weighted random forest for DoS attack detection in wireless sensor networks, TENCON 2021-2021 IEEE Region 10 Conference (TENCON), 375-380, 2021
• · Udawat, B., Kale, A., Sinha, D., Sharma, H., Krishnan, D., Campus placement prediction system using deep neural networks, International Conference on Innovative Computing and Communications (ICICC), 1-6, 2022
• · Krishnan, D., Babu, P., An adaptive weighted voting classifier for botnet detection in Internet of Things, 2021 IEEE 18th India Council International Conference (INDICON), 1-6, 2021
• · Krishnan, D., Analysis of accuracy of supervised machine learning algorithms in detecting denial of service attacks, Advances in Signal and Data Processing: Select Proceedings of ICSDP 2019, 1-8, 2021
• · Krishnan, D., A survey on security attacks in Internet of Things and challenges in existing countermeasures, Proceedings of International Conference on Wireless Communication and Sensor Networks (WCSN), 463-469, 2020
• · Krishnan, D., A distributed self-adaptive intrusion detection system for mobile ad-hoc networks using tamper evident mobile agents, Procedia Computer Science, 46, 1203-1208, 2015
• · Singh, S., Singh, A., Majumder, S., Sawhney, A., Krishnan, D., Extractive text summarization techniques of news articles: issues, challenges and approaches, 2019 International Conference on Vision Towards Emerging Trends in Communication and Networking (ViTECoN), 1-5, 2019
• · Krishnan, D., Chatterjee, M., An adaptive distributed intrusion detection system for cloud computing framework, Recent Trends in Computer Networks and Distributed Systems Security, 1-10, 2012
• · Krishnan, D., Chatterjee, M., Cloud security management suite—security as a service, 2012 World Congress on Information and Communication Technologies, 431-436, 2012

• EC Council's Certified Ethical Hacking
• CompTIA Security+

• Dr. Pravin Shrinath, PhD Supervisor , pravin.shrinath@nmims.edu
• Dr.Arokiraj Jovith, MTech Supervisor, arokiarajjovith.a@ktr.srmuniv.ac.in