On developing deep learning models with particle swarm optimization in the presence of poisoning attacks-Reference-Cited by-同舟云学术

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On developing deep learning models with particle swarm optimization in the presence of poisoning attacks

Published:2022-11-22 Issue: Volume: Page:
ISSN:
Container-title:2022 International Arab Conference on Information Technology (ACIT)
language:
Short-container-title:

Author:

Maabreh Majdi¹,Darwish Omar²,Karajeh Ola³,Tashtoush Yahya⁴

Affiliation:

1. The Hashemite University,Department of Computer Information Systems,Zarqa,Jordan

2. Eastern Michigan University,Information Security and Applied Computing Department,MI,USA

3. Virginia Polytechnic Institute and State University,Department of Computer Science,VA,USA

4. Jordan University of Science and Technology,Department of Computer Science,Irbid,Jordan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9994070/9994081/09994126.pdf?arnumber=9994126

Reference22 articles.

1. The robustness of popular multiclass machine learning models against poisoning attacks: Lessons and insights

2. Developing future human-centered smart cities: Critical analysis of smart city security, Data management, and Ethical challenges

3. Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning

4. Label flipping attacks against Naive Bayes on spam filtering systems

5. Poisoning attacks against support vector machines;Biggio;arXiv preprint,2012

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine Learning Regression Algorithms for Shear Strength Prediction of SFRC-DBs: Performance Evaluation and Comparisons;Arabian Journal for Science and Engineering;2023-08-21

2. Toward Secure and Efficient CNN Recognition with Different Activation and Optimization Functions;Proceedings of the 2023 International Conference on Advances in Computing Research (ACR’23);2023

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