An Experimental Study of Jamming Attacks in Underwater Acoustic Communication

Xiao, Peng; Kowalski, Michael P.; McCulley, Daniel R.; Zuba, Michael

doi:10.1145/2831296.2831320

Cited by 7 publications

(2 citation statements)

References 9 publications

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“…• Base Station to Cloud: To analyze the critical synchronization of the ground-based sensor nodes with TBSSP keys paired on the cloud server. The proposed approach usually provides dynamic and reliable communication transformation [8]. Since the whole network utilizes keys to secure data transmissions, this application method is similar to a private master key mechanism.…”

Section: The Methods Of Unwavering Data Channelingmentioning

confidence: 99%

Privacy Prevention and Nodes Optimization, Detection of IoUT based on Artificial Intelligence

Gaur

Prakash

2023

Preprint

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Transportation, temperature control, and the production of pharmaceuticals all rely on 71 percent of the Earth's surface, which is covered by water. Valuable things, including minerals, metals, corals, and coral reefs, can be identified with the help of the IoUT, among other applications. One of the crucial uses is in preventing damage caused by natural disasters. The IoT boosted concepts for a new undersea network (IoUT). Underwater networks have many drawbacks, including a lack of dependability, limited bandwidth, long propagation delays, high processing demands, high energy costs, and node detection with secure communication. Real-time, secure data communication is a significant area of research for us, along with node identification and dynamic network configuration. IoUT faces severe obstacles in the form of these issues. Our strategy involves a dynamic graph for network design, an AFA algorithm based on AI for node recognition, and ECC for a secure communication mechanism. In order to increase discretion and provide the undersea network with adequate robust security.

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Section: The Methods Of Unwavering Data Channelingmentioning

confidence: 99%

Privacy Prevention and Nodes Optimization, Detection of IoUT based on Artificial Intelligence

Gaur

Prakash

2023

Preprint

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“…In Su et al (2022) and Xiao et al (2015), collaborative jamming as a countermeasure to security threats is considered as well.…”

Section: Related Workmentioning

confidence: 99%

Network intelligence vs. jamming in underwater networks: how learning can cope with misbehavior

et al. 2023

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In this paper, we present a machine-learning technique to counteract jamming attacks in underwater networks. Indeed, this is relevant in security applications where sensor devices are located in critical regions, for example, in the case of national border surveillance or for identifying any unauthorized intrusion. To this aim, a multi-hop routing protocol that relies on the exploitation of a Q-learning methodology is presented with a focus on increasing reliability in data communication and network lifetime. Performance results assess the effectiveness of the proposed solution as compared to other efficient state-of-the-art approaches.

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Privacy Prevention and Nodes Optimization, Detection of IoUT Based on Artificial Intelligence

Gaur,

Prakash

2024

Wireless Pers Commun

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An Experimental Study of Jamming Attacks in Underwater Acoustic Communication

Cited by 7 publications

References 9 publications

Privacy Prevention and Nodes Optimization, Detection of IoUT based on Artificial Intelligence

Privacy Prevention and Nodes Optimization, Detection of IoUT based on Artificial Intelligence

Network intelligence vs. jamming in underwater networks: how learning can cope with misbehavior

Privacy Prevention and Nodes Optimization, Detection of IoUT Based on Artificial Intelligence

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