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Unsupervised Anomaly Detection and Explanation in Network Traffic with Transformers

https://doi.org/10.3390/electronics13224570

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Review of intrusion detection systems based on deep learning techniques: coherent taxonomy, challenges, motivations, recommendations, substantial analysis and future directions

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Explainable artificial intelligence: a comprehensive review

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Performance evaluation of unsupervised techniques in cyber-attack anomaly detection

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Unsupervised Anomaly Detection Approach for Cyberattack Identification

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Anomaly explanation: A review

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Temporal Fusion Transformers for interpretable multi-horizon time series forecasting

inferredcites →https://doi.org/10.1016/j.knosys.2019.105124openalex-snapshot

Deep learning approaches for anomaly-based intrusion detection systems: A survey, taxonomy, and open issues

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Siamese recurrent neural networks for the robust classification of grid disturbances in transmission power systems considering unknown events

inferredcites →https://doi.org/10.1109/access.2017.2780250openalex-snapshot

HAST-IDS: Learning Hierarchical Spatial-Temporal Features Using Deep Neural Networks to Improve Intrusion Detection

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Deep Learning-Based Intrusion Detection Systems: A Systematic Review

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RTIDS: A Robust Transformer-Based Approach for Intrusion Detection System

inferredcites →https://doi.org/10.1109/bigdata47090.2019.9005989openalex-snapshot

ACE – An Anomaly Contribution Explainer for Cyber-Security Applications

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A detailed analysis of the KDD CUP 99 data set

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GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection

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Network Anomaly Detection with Stochastically Improved Autoencoder Based Models

inferredcites →https://doi.org/10.1109/hsi.2018.8430788openalex-snapshot

Toward Explainable Deep Neural Network Based Anomaly Detection

inferredcites →https://doi.org/10.1109/icde51399.2021.00228openalex-snapshot

DAEMON: Unsupervised Anomaly Detection and Interpretation for Multivariate Time Series

inferredcites →https://doi.org/10.1109/ijcnn.2018.8488987openalex-snapshot

Character-Level Intrusion Detection Based On Convolutional Neural Networks

inferredcites →https://doi.org/10.1109/lcn58197.2023.10223390openalex-snapshot

Transparent autoencoding of network packets with self-attention-based transformers

inferredcites →https://doi.org/10.1109/mprv.2018.03367731openalex-snapshot

N-BaIoT—Network-Based Detection of IoT Botnet Attacks Using Deep Autoencoders

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Anomalous Communications Detection in IoT Networks Using Sparse Autoencoders

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Self-Supervised and Interpretable Anomaly Detection Using Network Transformers

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A Survey of Methods for Explaining Black Box Models

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Reliable Counterfactual Explanations for Autoencoder based Anomalies

inferredcites →https://doi.org/10.1145/3442381.3449868openalex-snapshot

Beyond Outlier Detection: Outlier Interpretation by Attention-Guided Triplet Deviation Network

inferredcites →https://doi.org/10.1145/3519602openalex-snapshot

General-purpose Unsupervised Cyber Anomaly Detection via Non-negative Tensor Factorization

inferredcites →https://doi.org/10.14722/ndss.2018.23191openalex-snapshot

Investigating Ad Transparency Mechanisms in Social Media: A Case Study of Facebook's Explanations

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IT-Sicherheit in digitalen Stationen: Cyber-physische Systemmodellierung, -bewertung und -analyse

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IoT network intrusion dataset

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Machine Learning and Deep Learning Methods for Intrusion Detection Systems: A Survey

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Explainable AI: A Review of Machine Learning Interpretability Methods

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Combined Network Intrusion and Phasor Data Anomaly Detection for Secure Dynamic Control Centers

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A Novel Hybrid Unsupervised Learning Approach for Enhanced Cybersecurity in the IoT

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Analysis of Autoencoders for Network Intrusion Detection

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AI-Assisted Pipeline for Dynamic Generation of Trustworthy Health Supplement Content at Scale

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Unsupervised Ensemble Based Deep Learning Approach for Attack Detection in IoT Network

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ATMAN: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Cyber-Electromagnetic Anomaly Detection Through Time-Series Analysis

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An explainable, resource-efficient transformer-based IDS with adaptive agent routing

inferred← citeshttps://doi.org/10.1016/j.adhoc.2025.104031openalex-snapshot

Generative AI-based intrusion detection systems for intra-vehicle networks

inferred← citeshttps://doi.org/10.1016/j.neucom.2026.134408openalex-snapshot

Unsupervised representation learning for anomaly detection in power grid communications via spatio-temporal graph neural networks

inferred← citeshttps://doi.org/10.1109/cisat71030.2026.11682668openalex-snapshot

SPQ-AT: Point-Query Cross-Attention with a Semantic Prior for Unsupervised Network Intrusion Detection

inferred← citeshttps://doi.org/10.1109/cises66934.2025.11265148openalex-snapshot

Outlier-Aware Road Traffic Speed Estimation: A Comparative Framework for Detection and Modeling Techniques

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A Network Anomaly Traffic Detection Method Based on Deep Stacked Ensemble Learning

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A Dynamic Graph Attention and Bi-LSTM Framework for Encrypted Malicious Traffic Detection

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MedNet: A Medical Overview-Focus Network With Uncertainty-Regularized Loss for Unsupervised ECG Anomaly Detection

inferred← citeshttps://doi.org/10.1109/prmvai65741.2025.11108334openalex-snapshot

A CNN-BiLSTM-Attention Model for Network Anomaly Traffic Detection

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Essence of Unsupervised Learning in Early Cybersecurity Attacks Detection

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Multitask Transformer‐Gradient Boost Ensemble‐Based Zero‐Day Threat Detection Framework for Cyber‐Physical Systems

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Use of Artificial Intelligence for Deep Learning Based Security Detection Systems: A Systematic Review of Techniques

inferred← citeshttps://doi.org/10.3390/electronics14050987openalex-snapshot

xIIRS: Industrial Internet Intrusion Response Based on Explainable Deep Learning

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Source-Rate Representations and Attention Autoencoders for Leakage-Safe Zero-Day Sybil Detection in UAV Networks

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Anomalies Classification in Fan Systems Using Dual-Branch Neural Networks with Continuous Wavelet Transform Layers: An Experimental Study

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