Hybrid Convolutional Multilayer Perceptron for Cyber Physical Systems (HCMP-CPS)-Reference-Cited by-同舟云学术

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Hybrid Convolutional Multilayer Perceptron for Cyber Physical Systems (HCMP-CPS)

Published:2023 Issue: Volume: Page:1053-1063
ISSN:2367-3370
Container-title:Hybrid Intelligent Systems
language:
Short-container-title:

Author:

Pousia S.,Mythili S.^ORCID,Kalamani M.,Manjith R.,Tharanyaa J. P. Shri,Jayabharathi C.

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-27409-1_97

Reference15 articles.

1. Barati, M., Abdullah, A., Udzir, N.I., Mahmod, R., Mustapha, N.: Distributed denial of service detection using hybrid machine learning technique. In: Proceedings of the 2014 International Symposium on Biometrics and Security Technologies (ISBAST), pp. 268–273, Kuala Lumpur, Malaysia, August. 2014

2. Chong, B.Y., Salam, I.: Investigating Deep Learning Approaches on the Security Analysis of Cryptographic Algorithms. Cryptography, vol. 5, p. 30 2021. https:// doi.org/https://doi.org/10.3390/cryptography5040030

3. Ghanbari, M., Kinsner, W., Ferens, K.: Detecting a distributed denial of service attack using a preprocessed convolutional neural network. In: Electrical Power and Energy Conference, pp. 1–6. IEEE (2017)

4. Goh, J., Adepu, S., Tan, M., Lee, Z.S.: Anomaly detection in cyber physical systems using recurrent neural networks. In: International Symposium on High Assurance Systems Engineering, pp. 140–145. IEEE (2017)

5. He, Y., Mendis, G.J., Wei, J.: Real-time detection of false data injection attacks in smart grid: a deep learning based intelligent mechanism. IEEE Trans. Smart Grid 8(5), 2505–2516 (2017)

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1. A Hybrid ABNB Model for Detecting Malicious Attacks for IIoS;2023 Global Conference on Information Technologies and Communications (GCITC);2023-12-01

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