Machine Learning Approach Using Artificial Neural Networks to Detect Malicious Nodes in IoT Networks-Reference-Cited by-同舟云学术

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Machine Learning Approach Using Artificial Neural Networks to Detect Malicious Nodes in IoT Networks

Published:2023 Issue: Volume: Page:27-37
ISSN:2524-7565
Container-title:Computer Vision and Robotics
language:
Short-container-title:

Author:

Liyakat Kazi Kutubuddin Sayyad

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-4577-1_3

Reference58 articles.

1. Javed F, Afzal MK, Sharif M, Kim B-S (2020) Internet of things (IoT) operating systems support, networking technologies, applications, and challenges: a comparative review. IEEE Commun Surv Tuts 20:2062–2100

2. Corak BH, Okay FY, Guzel M, Murt S, Ozdemir S (2018) Comparative analysis of IoT communication protocols. In: 2020 international symposium on networks, computers and communications (ISNCC), pp 1–6

3. Tseng F-H, Chiang H-P, Chao H-C (2018) Black hole along with other attacks in MANETs: a survey. J Inf Process Syst 14:56–78

4. Jan MA, Nanda P, Liu RP (2018) A Sybil attack detection scheme for a forest wildfire monitoring application. Fut Gener Comp Syst 80:613–626

5. Papernot N, McDaniel P, Sinha A, Wellman MP (2021) Sok: security and privacy in machine learning. In: 2018 IEEE European symposium on security and privacy (EuroS P), pp 399–414

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