Poisoning Attacks on Deep Learning based Wireless Traffic Prediction

Author:

Zheng Tianhang1,Li Baochun1

Affiliation:

1. University of Toronto

Publisher

IEEE

Reference37 articles.

1. Concealed Data Poisoning Attacks on NLP Models

2. Be Careful about Poisoned Word Embeddings: Exploring the Vulnerability of the Embedding Layers in NLP Models

3. Subpopulation data poisoning attacks;jagielski;arXiv preprint arXiv 2006 14080,2020

4. Witches’ brew: Industrial scale data poisoning via gradient matching;geiping;arXiv preprint arXiv 2009 02026,2020

5. Can you really backdoor federated learning?;sun;arXiv preprint arXiv 1911 11698,2019

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2. Effective AI/ML Training using Submodular Cell Selection for Network Energy Saving;2024 IEEE International Conference on Communications Workshops (ICC Workshops);2024-06-09

3. Poisoning Attacks on Federated Learning-based Wireless Traffic Prediction;2024 IFIP Networking Conference (IFIP Networking);2024-06-03

4. On Poisoning Attacks and Defenses for LSTM Time Series Prediction Models: Speed Prediction as an Example;2024 International Wireless Communications and Mobile Computing (IWCMC);2024-05-27

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