Assessing and enhancing adversarial robustness of predictive analytics : an empirically tested design framework
Weifeng Li and Yidong Chai
| Year of publication: |
2022
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|---|---|
| Authors: | Li, Weifeng ; Chai, Yidong |
| Published in: |
Journal of management information systems : JMIS. - Abingdon, Oxon : Routledge, Taylor & Francis, ISSN 1557-928X, ZDB-ID 2033010-8. - Vol. 39.2022, 2, p. 542-572
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| Subject: | adversarial robustness | artificial intelligence security | design frameworks | Predictive analytics | supervised machine learning | text mining | Künstliche Intelligenz | Artificial intelligence | Prognoseverfahren | Forecasting model | Data Mining | Data mining | Text | Neuronale Netze | Neural networks |
Online Resource
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1080/07421222.2022.2063549 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10013367731