Defed: An Edge-Feature-Enhanced Image Denoised Network Against Adversarial Attacks for Secure Internet of Things

Author:

Xiao Yang1ORCID,Yan Chengjia1ORCID,Lyu Shuo1,Pei Qingqi2ORCID,Liu Ximeng3ORCID,Zhang Ning4ORCID,Dong Mianxiong5ORCID

Affiliation:

1. State Key Laboratory of Integrated Service Networks, School of Cyber Engineering, and the Engineering Research Center of Trusted Digital Economy, Universities of Shaanxi Province, Xidian University, Xi’an, China

2. State Key Laboratory of Integrated Service Networks, School of Telecommunications Engineering, and the Engineering Research Center of Trusted Digital Economy, Universities of Shaanxi Province, Xidian University, Xi’an, China

3. School of Computer and Data Science, Fuzhou University, Fujian, China

4. Department of Electrical and Computer Engineering, University of Windsor, Windsor, Canada

5. Department of Information and Electronic Engineering, Muroran Institute of Technology, Muroran, Japan

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Key Research and Development Programs of Shaanxi

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Reference54 articles.

1. Defense Against Adversarial Attacks by Reconstructing Images

2. Decision-based adversarial attacks: Reliable attacks against black-box machine learning models;brendel;Proc Int Conf Learn Represent,2018

3. Networking and Communications in Autonomous Driving: A Survey

4. Securable networked scheme with face authentication

5. A Computational Approach to Edge Detection

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