A Machine Learning Approach for the Underwater Investigation of Malicious Activity in a Wireless Sensor Network-Reference-Cited by-同舟云学术

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A Machine Learning Approach for the Underwater Investigation of Malicious Activity in a Wireless Sensor Network

Published:2023-11-15 Issue: Volume:13 Page:128-132
ISSN:
Container-title:2023 International Conference on Sustainable Communication Networks and Application (ICSCNA)
language:
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Author:

M S Murali Dhar¹,R Mahaveerakannan²,Ravindaran F.³,MurthyRaju Kommisetti⁴

Affiliation:

1. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology,Department of Computer Science and Engineering,Chennai,Tamil Nadu,600062

2. The Institute of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences,Department of Spatial Informatics

3. Karpagam College of Engineering,Department of Computer Science and Engineering (Cyber Security),Coimbatore,Tamil Nadu

4. Shri Vishnu Engineering College For Women,Department of Electronics and Communication Engineering,BHIMAVARAM,Andha Pradesh

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10370002/10368600/10370730.pdf?arnumber=10370730

Reference20 articles.

1. MrakovChainMonte Carlo Based Internal Attack Evaluation for Wireless Sensor Network;Ahmed;Int

2. CURD: Controllable reactive jamming detection in underwater sensor networks

3. The challenges of building scalable mobile underwater wireless sensor networks for aquatic applications

4. Securing underwater wireless communication networks

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