Reinforcement Learning-assisted Threshold Optimization for Dynamic Honeypot Adaptation to Enhance IoBT Networks Security-Reference-Cited by-同舟云学术

Reinforcement Learning-assisted Threshold Optimization for Dynamic Honeypot Adaptation to Enhance IoBT Networks Security

Published:2021-12-05 Issue: Volume: Page:
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Container-title:2021 IEEE Symposium Series on Computational Intelligence (SSCI)
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Author:

Limouchi Elnaz,Mahgoub Imad

Funder

Office of the Secretary of Defense (OSD)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9659537/9659538/09660066.pdf?arnumber=9660066

Reference23 articles.

1. Security for resilient iobt systems: Emerging research directions;agadakos;IEEE INFOCOM 2019 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS),0

2. Reputation Management Using Honeypots for Intrusion Detection in the Internet of Things

3. Recent Advancements in Intrusion Detection Systems for the Internet of Things

4. A theory of memory retrieval.

5. Threshold learning for optimal decision making;lepora;Advances in Neural Information Processing Systems 20 NIPS,2016

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