Dr. Gowri Raghavendra Narayan Kurmala

About

Dr. K. Gowri Raghavendra Narayan received his B.Tech and M.Tech degrees in Computer Science and Engineering from Jawaharlal Nehru Technological University, Kakinada, India. He completed his Ph.D. in the Department of Computer Science and Engineering at the Indian Institute of Information Technology, Sri City, Chittoor, Andhra Pradesh, India. He is currently working as an Assistant Professor in the Department of Computer Science and Engineering at Amrita Vishwa Vidyapeetham, Amaravati. He has 10 years of experience in teaching and research, having served in various academic roles at reputed institutions.

Employment

• Amrita Viswa Vidyapeetham Assistant Professor
  2025 - Present
• Vasireddy Venkatadri Institute of Technology Assistant Professor
  2015 - 2021

Education

• Indian Institute of Information Technology Sri City Ph.D
  2021 - 2025
• Jawaharlal Nehru Technological University, Kakinada B.Tech
  2009 - 2013

Projects & Funding

Projects & funding information is unavailable.

Publications (13)

• Privacy-Preserving Unlinkable Identity Management on Blockchain for e-Health Records
  2026 DOI: 10.1145/3807407.3807473
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• Z-IDS: Zero-Day Intrusion Detection in IoV Using Generative Adversarial Networks
  IEEE Access 2026 DOI: 10.1109/access.2026.3682762
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• A framework for handling class imbalance in malicious URL dataset
  Computers and Electrical Engineering 2026 DOI: 10.1016/j.compeleceng.2026.111004
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• A Novel Heuristic-Based Heart Disease Detection Framework for Imbalanced Dataset
  2025 IEEE 9th International Conference on Information and Communication Technology (CICT) 2025 DOI: 10.1109/cict67193.2025.11398983
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• A Penalty-Based Entropy Driven Universal Password Strength for Lightweight Devices
  2024 16th International Conference on COMmunication Systems and NETworkS, COMSNETS 2024 2024 DOI: 10.1109/COMSNETS59351.2024.10427138
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• An RFID-Based Authentication Protocol for Smart Healthcare Applications
  Lecture Notes in Networks and Systems 2024 DOI: 10.1007/978-981-97-2004-0_20
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• Attenuating majority attack class bias using hybrid deep learning based IDS framework
  Journal of Network and Computer Applications 2024 DOI: 10.1016/j.jnca.2024.103954
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• Malicious Domain Detection Using Random Indexing and Machine Learning
  2024 DOI: 10.1007/978-981-99-8438-1_39
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• Comment on “Improved RSA Technique with Efficient Data Integrity Verification for Outsourcing Database in Cloud”
  arXiv 2023 DOI: 10.48550/arXiv.2311.14499
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• IIDS: Design of Intelligent Intrusion Detection System for Internet-of-Things Applications
  2023 IEEE 7th Conference on Information and Communication Technology, CICT 2023 2023 DOI: 10.1109/CICT59886.2023.10455720
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