An Adaptive Policy-Based Anomaly Object Control System for Enhanced Cybersecurity-Reference-Cited by-同舟云学术

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An Adaptive Policy-Based Anomaly Object Control System for Enhanced Cybersecurity

Published:2024 Issue: Volume:12 Page:55281-55291
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Sakong Won¹^ORCID,Kim Wooju¹^ORCID

Affiliation:

1. Department of Industrial Engineering, Yonsei University, Seoul, South Korea

Funder

Industrial Strategic Technology Development Program-ATC+

Ministry of Trade, Industry and Energy (MOTIE), South Korea

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10500433.pdf?arnumber=10500433

Reference40 articles.

1. Isolation Forest-Based Mechanism to Defend against Interest Flooding Attacks in Named Data Networking

2. A deep learning approach combining autoencoder with one-class SVM for DDoS attack detection in SDNs;Mhamdi

3. An efficient hybrid SVDD/clustering approach for anomaly-based intrusion detection

4. DDoS Attacks Detection with AutoEncoder

5. Unsupervised learning approach for network intrusion detection system using autoencoders

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