Advanced NID-VGG16 with Orca Predation Optimization Based 1DCNN-BiLSTM for Network Intrusion Detection-Reference-Cited by-同舟云学术

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Advanced NID-VGG16 with Orca Predation Optimization Based 1DCNN-BiLSTM for Network Intrusion Detection

Published:2024-01-18 Issue: Volume:56 Page:840-845
ISSN:
Container-title:2024 14th International Conference on Cloud Computing, Data Science & Engineering (Confluence)
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Author:

K Ratna Kumari¹^ORCID,N Durga¹^ORCID,T Gayathri¹^ORCID,Sundari Ch Lalitha Syama²,Uppalapati Padma Jyothi³^ORCID

Affiliation:

1. Shri Vishnu engineering college for women,Computer science and engineering,Bhimavaram,India

2. Sasi Institute of Technology and Engineering,Information Technology,Tadepalligudem,India

3. Vishnu Institute of Technology,Computer science and engineering,Bhimavaram,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10463166/10463197/10463215.pdf?arnumber=10463215

Reference32 articles.

1. Feature engineering and deep learning-based intrusion detection framework for securing edge IoT

2. APMSA: Adversarial Perturbation Against Model Stealing Attacks

3. Ad Hoc Vehicular Fog Enabling Cooperative Low-Latency Intrusion Detection

4. Internet of Things Intrusion Detection: Centralized, On-Device, or Federated Learning?

5. Attack-Specific Feature Selection for Anomaly Detection in Software-Defined Networks

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