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Imbalanced Data Problems in Deep Learning-Based Side-Channel Attacks: Analysis and Solution

  • Published:2021 Issue: Volume:16 Page:3790-3802
  • ISSN:1556-6013
  • Container-title:IEEE Transactions on Information Forensics and Security
  • language:
  • Short-container-title:IEEE Trans.Inform.Forensic Secur.

Author:

Ito AkiraORCID,Saito Kotaro,Ueno ReiORCID,Homma NaofumiORCID

Funder

Japan Society for the Promotion of Science (JSPS) KAKENHI

JSPS Research Fellow

Japan Science and Technology Agency (JST) Core Research for Evolutional Science and Technology (CREST), Japan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Safety, Risk, Reliability and Quality

Cited by 22 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. Advanced Side-Channel Profiling Attacks with Deep Neural Networks: A Hill Climbing Approach;Electronics;2024-09-05

2. The METRIC-framework for assessing data quality for trustworthy AI in medicine: a systematic review;npj Digital Medicine;2024-08-03

3. Dual-Path Hybrid Residual Network for Profiled Side-Channel Analysis;IEEE Transactions on Circuits and Systems II: Express Briefs;2024-08

4. SecMdp: Towards Privacy-Preserving Multimodal Deep Learning in End-Edge-Cloud;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13

5. Lightweight Machine-Learning-Based Diagnosis for Power Electronic Systems Subject to Imbalanced Data;IEEE Journal of Emerging and Selected Topics in Industrial Electronics;2024-04
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