ZT-NIDS: Zero Trust, Network Intrusion Detection System

Abeer Z. Alalmaie, Priyadarsi Nanda, Xiangjian He

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review


Zero Trust security can tackle various cyberthreats. Current trends in security monitoring must shift to a “never trust, always verify” approach, as data security is threatened when cloud-based third parties access network traces. Network Intrusion Detection System (NIDS) can be exploited to detect anomalous behaviour. Convolution Neural Network (CNN), Bi-directional Long Short Term Memory (BiLSTM) based classifiers and Auto-Encoder (AE) feature extractors have presented promising results in NIDS. AE feature extractor can compress the important information and train the unsupervised model. CNNs detect local spatial relationships, while BiLSTMs can exploit temporal interactions. Furthermore, Attention modules can capture content-based global interactions and can be applied on CNNs to attend to the significant contextual information. In this paper, we utilized the advantages of all AE, CNN and BiLSTM structures using a multi-head Self Attention mechanism to integrate CNN features for feeding into BiLSTM classifier. We use the bottleneck features of a pre-trained AE for an Attention-based CNN-BiLSTM classifier. Our experiments using 10, 6 and 2 categories NID system on UNSW-NB15 dataset showed that the proposed method outperforms state-of-the-art methods and achieved accuracy of 91.72%, 89.79% and 93.01%, respectively. Plus, we introduced a balanced data sampler for training 10 categories of NIDS.

Original languageEnglish
Title of host publicationSECRYPT 2023 - Proceedings of the 20th International Conference on Security and Cryptography
EditorsSabrina De Capitani di Vimercati, Pierangela Samarati
PublisherScience and Technology Publications, Lda
Number of pages12
ISBN (Print)9789897586668
Publication statusPublished - 2023
Event20th International Conference on Security and Cryptography, SECRYPT 2023 - Rome, Italy
Duration: 10 Jul 202312 Jul 2023

Publication series

NameProceedings of the International Conference on Security and Cryptography
ISSN (Print)2184-7711


Conference20th International Conference on Security and Cryptography, SECRYPT 2023


  • Attention
  • Cybersecurity
  • Network Intrusion Detection
  • Network Security
  • Zero Trust

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Software


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