On Poisoning Attacks and Defenses for LSTM Time Series Prediction Models: Speed Prediction as an Example-Reference-Cited by-同舟云学术

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On Poisoning Attacks and Defenses for LSTM Time Series Prediction Models: Speed Prediction as an Example

Published:2024-05-27 Issue: Volume: Page:610-615
ISSN:
Container-title:2024 International Wireless Communications and Mobile Computing (IWCMC)
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Author:

Chen Yi-Yu¹,Hung Hui-Nien²,Yang Shun-Ren¹,Yen Chia-Cheng¹,Lin Phone³

Affiliation:

1. National Tsing Hua University,Inst. of Info. Sec. and Inst. of Commun. Eng,Dept. of Comp. Sci,Taiwan

2. National Yang Ming Chiao Tung University,Inst. of Stats,Taiwan

3. National Taiwan University,Grad. Inst. of Biomed. Elec. & Bioinform., Grad. Inst. of Net. & MM, Inst. of Med. Device & Imaging and IoT Research Center,Dept. of Comp. Sci. & Info. Eng,Taiwan

Funder

National Science and Technology Council

Ministry of Education

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10592105/10592309/10592413.pdf?arnumber=10592413

Reference11 articles.

1. Poisoning Attacks on Deep Learning based Wireless Traffic Prediction

2. A Black-box based Attack Generation Approach to Create the Transferable Patch Attack

3. Physical Backdoor Attack using Multi-Trigger to Same Class

4. Towards Security Threats of Deep Learning Systems: A Survey

5. Support Vector Machine, Naïve Baye’s, and Recurrent Neural Network to Detect Data Poisoning Attacks on Dataset

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