Code integrity attestation for PLCs using black box neural network predictions-Reference-Cited by-同舟云学术

Code integrity attestation for PLCs using black box neural network predictions

Published:2021-08-18 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering
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Author:

Chen Yuqi¹,Poskitt Christopher M.¹^ORCID,Sun Jun¹^ORCID

Affiliation:

1. Singapore Management University, Singapore

Funder

National Research Foundation, Singapore

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3468264.3468617

Reference82 articles.

1. 2021. Secure Water Treatment (SWaT). http://itrust.sutd.edu.sg/research/testbeds/secure-water-treatment-swat/ Accessed: June 2021. 2021. Secure Water Treatment (SWaT). http://itrust.sutd.edu.sg/research/testbeds/secure-water-treatment-swat/ Accessed: June 2021.

2. 2021. Supplementary material. https://github.com/sav-smu/plc-code-integrity 2021. Supplementary material. https://github.com/sav-smu/plc-code-integrity

3. ECFI

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