Assessing and Enhancing Adversarial Robustness of Predictive Analytics: An Empirically Tested Design Framework-Reference-Cited by-同舟云学术

Assessing and Enhancing Adversarial Robustness of Predictive Analytics: An Empirically Tested Design Framework

Published:2022-04-03 Issue:2 Volume:39 Page:542-572
ISSN:0742-1222
Container-title:Journal of Management Information Systems
language:en
Short-container-title:Journal of Management Information Systems

Author:

Li Weifeng¹,Chai Yidong²

Affiliation:

1. Department of Management Information Systems, Terry College of Business, University of Georgia, Athens GA, USA

2. School of Management, Hefei University of Technology, Key Laboratory of Process Optimization and Intelligence Decision Making, Ministry of Education, Hefei University of Technology, Hefei, China

Funder

US National Science Foundation

Publisher

Informa UK Limited

Subject

Information Systems and Management,Management Science and Operations Research,Computer Science Applications,Management Information Systems

Link

https://www.tandfonline.com/doi/pdf/10.1080/07421222.2022.2063549

Reference61 articles.

1. MetaFraud: A Meta-Learning Framework for Detecting Financial Fraud

2. Don’t Mention It? Analyzing User-Generated Content Signals for Early Adverse Event Warnings

3. Enhancing Predictive Analytics for Anti-Phishing by Exploiting Website Genre Information

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