An attentive interpretable approach for identifying and quantifying malware-infected internet-scale IoT bots behind a NAT-Reference-Cited by-同舟云学术

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An attentive interpretable approach for identifying and quantifying malware-infected internet-scale IoT bots behind a NAT

Published:2022-05-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 19th ACM International Conference on Computing Frontiers
language:
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Author:

Nader Christelle¹,Bou-Harb Elias¹

Affiliation:

1. University of Texas at San Antonio

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3528416.3530995

Reference34 articles.

1. 2021. https://blog.netlab.360.com/ten-families-of-malicious-samples-are-spreading-using-the-log4j2-vulnerability-now/ 2021. https://blog.netlab.360.com/ten-families-of-malicious-samples-are-spreading-using-the-log4j2-vulnerability-now/

2. 2021. https://github.com/NATedIoTFingerprinting/NATedIoTFingerprinting 2021. https://github.com/NATedIoTFingerprinting/NATedIoTFingerprinting

3. 2021. https://github.com/dreamquark-ai/tabnet 2021. https://github.com/dreamquark-ai/tabnet

4. 2021. https://www.maxmind.com/en/geoip2-databases 2021. https://www.maxmind.com/en/geoip2-databases

5. 2022. https://www.shodan.io/ 2022. https://www.shodan.io/

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