Attacks Against Machine Learning Systems: Analysis and GAN-based Approach to Protection-Reference-Cited by-同舟云学术

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Attacks Against Machine Learning Systems: Analysis and GAN-based Approach to Protection

Published:2023 Issue: Volume: Page:49-59
ISSN:2367-3370
Container-title:Proceedings of the Seventh International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’23)
language:
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Author:

Kotenko Igor^ORCID,Saenko Igor^ORCID,Lauta Oleg^ORCID,Vasiliev Nikita^ORCID,Iatsenko Dmitry

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-43792-2_5

Reference34 articles.

1. Kotenko, I., Saenko, I., Lauta, O., Vasiliev, N., Kribel, K.: Attacks against artificial intelligence systems: classification, the threat model and the approach to protection. In: Kovalev, S., Sukhanov, A., Akperov, I., Ozdemir, S. (eds.) Proceedings of the Sixth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’22). IITI 2022. Lecture Notes in Networks and Systems, vol 566. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-19620-1_28

2. Xu, H., Li, Y., Jin, W., Tang, J.: Adversarial attacks and defenses: frontiers, advances and practice. In: Proceedings of the 26th International Conference on Knowledge Discovery, Virtual Event, CA, USA, pp. 3541–3542 (2020)

3. Liu, Q., Li, P., Zhao, W., Cai, W., Yu, S., Leung, V.C.M.: A survey on security threats and defensive techniques of machine learning: a data driven view. IEEE Access 6, 12103–12117 (2018)

4. Pitropakis, N., Panaousis, E., Giannetsos, T., Anastasiadis, E., Loukas, G.: A taxonomy and survey of attacks against machine learning. Comput. Sci. Rev. 34, 100199 (2019)

5. Ren, K., Zheng, T., Qin, Z., Liu, X.: Adversarial attacks and defenses in deep learning. Engineering 6, 346–360 (2019)

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1. Countering Adversarial Zeroth Order Optimization Attacks Based on Neural-Cleanse, Gaussian and Poisson Noise Adding;2024 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM);2024-05-20

2. An Approach to Countering Adversarial Attacks on Image Recognition Based on JPEG-Compression and Neural-Cleanse;2024 IEEE Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT);2024-05-13

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