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SimCSE for Encrypted Traffic Detection and Zero-Day Attack Detection

https://doi.org/10.1109/access.2022.3177272
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What this work says

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

inferredcites →https://doi.org/10.1007/3-540-44673-7_12openalex-snapshot
Support Vector Machines: Theory and Applications
inferredcites →https://doi.org/10.1007/s10207-023-00676-0openalex-snapshot
From zero-shot machine learning to zero-day attack detection
inferredcites →https://doi.org/10.1016/j.array.2021.100081openalex-snapshot
Industrial control system device classification using network traffic features and neural network embeddings
inferredcites →https://doi.org/10.1016/j.cose.2020.101917openalex-snapshot
Encrypted video traffic clustering demystified
inferredcites →https://doi.org/10.1016/j.icte.2020.03.003openalex-snapshot
Deep transductive transfer learning framework for zero-day attack detection
inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot
Random Forests
inferredcites →https://doi.org/10.1080/03081079.2017.1291635openalex-snapshot
A simple probabilistic explanation of term frequency-inverse document frequency (tf-idf) heuristic (and variations motivated by this explanation)
inferredcites →https://doi.org/10.1109/access.2020.3013849openalex-snapshot
The Weighted Word2vec Paragraph Vectors for Anomaly Detection Over HTTP Traffic
inferredcites →https://doi.org/10.1109/access.2020.3035967openalex-snapshot
A Deep Hierarchical Network for Packet-Level Malicious Traffic Detection
inferredcites →https://doi.org/10.1109/ccnc49033.2022.9700625openalex-snapshot
MalDIST: From Encrypted Traffic Classification to Malware Traffic Detection and Classification
inferredcites →https://doi.org/10.1109/icoin.2017.7899588openalex-snapshot
Malware traffic classification using convolutional neural network for representation learning
inferredcites →https://doi.org/10.1109/infocom41043.2020.9155278openalex-snapshot
ZeroWall: Detecting Zero-Day Web Attacks through Encoder-Decoder Recurrent Neural Networks
inferredcites →https://doi.org/10.1109/netsoft48620.2020.9165381openalex-snapshot
IoT Malware Network Traffic Classification using Visual Representation and Deep Learning
inferredcites →https://doi.org/10.1109/nsyss.2015.7043530openalex-snapshot
Malware detection in Android by network traffic analysis
inferredcites →https://doi.org/10.1109/tnsm.2021.3071441openalex-snapshot
FlowPic: A Generic Representation for Encrypted Traffic Classification and Applications Identification
inferredcites →https://doi.org/10.1145/3457904openalex-snapshot
A Survey on Encrypted Network Traffic Analysis Applications, Techniques, and Countermeasures
inferredcites →https://doi.org/10.18653/v1/2021.emnlp-main.552openalex-snapshot
SimCSE: Simple Contrastive Learning of Sentence Embeddings
inferredcites →https://doi.org/10.20517/jsss.2020.15openalex-snapshot
Feature extraction based on word embedding models for intrusion detection in network traffic
inferredcites →https://doi.org/10.3390/app9163414openalex-snapshot
An LSTM-Based Deep Learning Approach for Classifying Malicious Traffic at the Packet Level
inferredcites →https://doi.org/10.3390/electronics9101684openalex-snapshot
Utilising Deep Learning Techniques for Effective Zero-Day Attack Detection
inferredcites →https://doi.org/10.34028/iajit/17/4a/4openalex-snapshot
Enhanced Android Malware Detection and Family Classification, using Conversation-level Network Traffic Features
inferredcites →https://doi.org/10.48550/arxiv.1301.3781openalex-snapshot
Efficient Estimation of Word Representations in Vector Space
inferredcites →https://doi.org/10.48550/arxiv.1706.01084openalex-snapshot
Joint Text Embedding for Personalized Content-based Recommendation
inferredcites →https://doi.org/10.48550/arxiv.2004.13006openalex-snapshot
NetML: A Challenge for Network Traffic Analytics

What points at this work

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

inferred← citeshttps://doi.org/10.2139/ssrn.4679061openalex-extracted
inferred← citeshttps://doi.org/10.1007/978-3-031-60935-0_70openalex-snapshot
Early Detection and Classification of Zero-Day Attacks in Network Traffic Using Convolutional Neural Network
inferred← citeshttps://doi.org/10.1007/978-3-031-87886-2_4openalex-snapshot
Design of an Iterative Method for Zero-Day Attack Detection Using Adversarial Graph Temporal Convolutional Networks and Federated Learning
inferred← citeshttps://doi.org/10.1007/978-3-031-96590-6_1openalex-snapshot
Jibber-Jabber!: Encoding the (Un-)Natural Language of Network Devices and Applications
inferred← citeshttps://doi.org/10.1007/s11063-024-11545-9openalex-snapshot
GNNCL: A Graph Neural Network Recommendation Model Based on Contrastive Learning
inferred← citeshttps://doi.org/10.1016/j.cose.2022.103000openalex-snapshot
When a RF beats a CNN and GRU, together—A comparison of deep learning and classical machine learning approaches for encrypted malware traffic classification
inferred← citeshttps://doi.org/10.1016/j.cose.2023.103466openalex-snapshot
TGPrint: Attack fingerprint classification on encrypted network traffic based graph convolution attention networks
inferred← citeshttps://doi.org/10.1016/j.cosrev.2025.100781openalex-snapshot
A comprehensive review on machine learning-based VPN detection: Scenarios, methods, and open challenges
inferred← citeshttps://doi.org/10.1016/j.eswa.2024.124166openalex-snapshot
The art of time-bending: Data augmentation and early prediction for efficient traffic classification
inferred← citeshttps://doi.org/10.1061/jccee5.cpeng-6561openalex-snapshot
Development of Multilabel Text Classification with Contrastive Learning for Safety Hazard Analysis in Large-Scale Construction Projects
inferred← citeshttps://doi.org/10.1109/access.2025.3555201openalex-snapshot
Protocol-Agnostic and Packet-Based Intrusion Detection Using a Multi-Layer Deep-Learning Architecture at the Network Edge
inferred← citeshttps://doi.org/10.1109/ccnc51664.2024.10454807openalex-snapshot
Hidden in Time, Revealed in Frequency: Spectral Features and Multiresolution Analysis for Encrypted Internet Traffic Classification
inferred← citeshttps://doi.org/10.1109/etfa61755.2024.10711134openalex-snapshot
Efficient Machine Learning-Based Security Monitoring and Cyberattack Classification of Encrypted Network Traffic in Industrial Control Systems
inferred← citeshttps://doi.org/10.1109/icraset63057.2024.10895836openalex-snapshot
Natural Language Processing Based Intrusion Detection Interface For IoT Devices
inferred← citeshttps://doi.org/10.1109/iscs69371.2025.11386278openalex-snapshot
Deep Learning for Web Application Security: A Comprehensive Survey on Intrusion Detection Systems
inferred← citeshttps://doi.org/10.1109/iske60036.2023.10481498openalex-snapshot
A Named Entity Recognition Method for Substation Location Selection
inferred← citeshttps://doi.org/10.1109/jiot.2025.3586290openalex-snapshot
TGDCLNet: Teacher-Guided Denoising Contrastive Learning Network-Based IoT Network Intrusion Detection
inferred← citeshttps://doi.org/10.1145/3731867.3731894openalex-snapshot
Contrastive Learning for Network Intrusion Detection: A Comprehensive Survey
inferred← citeshttps://doi.org/10.14569/ijacsa.2023.01411129openalex-snapshot
CESSO-HCRNN: A Hybrid CRNN With Chaotic Enriched SSO-based Improved Information Gain to Detect Zero-Day Attacks
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