Federated Anomaly Detection on System Logs for the Internet of Things: A Customizable and Communication-Efficient Approach-Reference-Cited by-同舟云学术

Federated Anomaly Detection on System Logs for the Internet of Things: A Customizable and Communication-Efficient Approach

Author:

Li Beibei¹^ORCID,Ma Shang¹^ORCID,Deng Ruilong²^ORCID,Choo Kim-Kwang Raymond³^ORCID,Yang Jin¹^ORCID

Affiliation:

1. School of Cyber Science and Engineering, Sichuan University, Chengdu, China

2. State Key Laboratory of Industrial Control Technology and the College of Control Science and Engineering, Zhejiang University, Hangzhou, China

3. Department of Information Systems and Cyber Security, University of Texas at San Antonio, San Antonio, TX, USA

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

Cloud Technology Endowed Professorship

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Link

Reference38 articles.

1. Advances and open problems in federated learning;kairouz;arXiv 1912 04977,2019

3. Communication-efficient learning of deep networks from decentralized data;mcmahan;Proc Int Conf Artif Intell Stat (AISTATS),2017

Cited by 19 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