KDDT: Knowledge Distillation-Empowered Digital Twin for Anomaly Detection-Reference-Cited by-同舟云学术

KDDT: Knowledge Distillation-Empowered Digital Twin for Anomaly Detection

Published:2023-11-30 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
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Author:

Xu Qinghua¹,Ali Shaukat²,Yue Tao³,Nedim Zaimovic⁴,Singh Inderjeet⁴

Affiliation:

1. Simula Research Laboratory, Oslo, Norway / University of Oslo, Oslo, Norway

2. Simula Research Laboratory, Oslo, Norway / Oslo Metropolitan University, Oslo, Norway

3. Simula Research Laboratory, Oslo, Norway

4. Alstom Rail, Västerås, Sweden

Funder

Horizon 2020 Framework Programme

Norges Forskningsråd

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3611643.3613879

Reference43 articles.

1. A survey of network anomaly detection techniques

2. R Anushiya and V S Lavanya . 2021. A COMPARATIVE STUDY ON INTRUSION DETECTION SYSTEMS FOR SECURED COMMUNICATION IN INTERNET OF THINGS. ICTACT JOURNAL ON COMMUNICATION TECHNOLOGY, 12, 03 ( 2021 ). R Anushiya and V S Lavanya. 2021. A COMPARATIVE STUDY ON INTRUSION DETECTION SYSTEMS FOR SECURED COMMUNICATION IN INTERNET OF THINGS. ICTACT JOURNAL ON COMMUNICATION TECHNOLOGY, 12, 03 (2021).

3. A practical guide for using statistical tests to assess randomized algorithms in software engineering

4. Cross-Validation Methods

5. KR1442 Chowdhary and KR Chowdhary. 2020. Natural language processing. Fundamentals of artificial intelligence 603–649. KR1442 Chowdhary and KR Chowdhary. 2020. Natural language processing. Fundamentals of artificial intelligence 603–649.

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2. KDDT: Knowledge Distillation-Empowered Digital Twin for Anomaly Detection;Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering;2023-11-30