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Detecting operational adversarial examples for reliable deep learning
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Zhao, Xingyu, Huang, Wei, Schewe, Sven, Dong, Yi and Huang, Xiaowei (2021) Detecting operational adversarial examples for reliable deep learning. In: 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN'21), Taipei, Taiwan, 21-24 Jun 2021 pp. 5-6. ISBN 9781665435666. doi:10.1109/DSN-S52858.2021.00013
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Official URL: http://dx.doi.org/10.1109/DSN-S52858.2021.00013
Abstract
The utilisation of Deep Learning (DL) raises new challenges regarding its dependability in critical applications. Sound verification and validation methods are needed to assure the safe and reliable use of DL. However, state-of-the-art debug testing methods on DL that aim at detecting adversarial examples (AEs) ignore the operational profile, which statistically depicts the software’s future operational use. This may lead to very modest effectiveness on improving the software’s delivered reliability, as the testing budget is likely to be wasted on detecting AEs that are unrealistic or encountered very rarely in real-life operation. In this paper, we first present the novel notion of “operational AEs” which are AEs that have relatively high chance to be seen in future operation. Then an initial design of a new DL testing method to efficiently detect “operational AEs” is provided, as well as some insights on our prospective research plan.
Item Type: | Conference Item (Paper) | ||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | ||||||
Publisher: | IEEE | ||||||
ISBN: | 9781665435666 | ||||||
Book Title: | 2021 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume (DSN-S) | ||||||
Official Date: | 1 September 2021 | ||||||
Dates: |
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Page Range: | pp. 5-6 | ||||||
DOI: | 10.1109/DSN-S52858.2021.00013 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||
Conference Paper Type: | Paper | ||||||
Title of Event: | 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN'21) | ||||||
Type of Event: | Conference | ||||||
Location of Event: | Taipei, Taiwan | ||||||
Date(s) of Event: | 21-24 Jun 2021 |
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