Network Traffic

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4 papers in the last four weeks, with none the four weeks before. 0.0% of all new papers.

Jul 13Week of Sep 28

Latest papers 25

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FlowAtom: Atom-Based Evidence Aggregation for Multi-Label Website Fingerprinting
Sep 24, 2026Chongru Fan, Wentao Huang, Wei Wang +4Network Traffic Fingerprint
School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, China · Zhongguancun Laboratory, Beijing, China
Topological Signatures of Cyber-Attack Classes in Natural Visibility Graph Representations of Network Traffic
Sep 22, 2026Ali Melih Kanca, Ilker TurkerNetwork Traffic Threat Detection
Department of Computer Engineering, Faculty of Computing and Informatics Sciences, Karabuk University, Karabuk, Türkiye
Concept drift mitigation through community and spectral graph analysis for the detectionof cyberattacks in network traffic
Sep 8, 2026Julien Michel, Abdul Qadir Khan, Majed Jaber +1Threat Detection Generalist Graph Anomaly Detection
Laboratoire de Recherche de l’EPITA, 14-16 Rue Voltaire, Le Kremlin-Bicêtre, 94270, France · ICube, UMR7357, Université de Strasbourg, Strasbourg, 67000, France
ResLearn-XR: Residual Learning for Network Traffic and Quality-of-Experience-Aware Modeling in Extended Reality
Sep 7, 2026Yoga Suhas Kuruba Manjunath, Jie Gao, Lian ZhaoAccurate Traffic Forecasting Residual Learning
School of Information Technology, Carleton University, Ottawa, ON, K1S 5B6, Canada · Department of Electrical, Computer and Biomedical Engineering, Toronto Metropolitan University, Toronto, ON M5B 2K3, Canada
Learning Compression Rules for Network Traffic
Aug 5, 2026Quentin Lampin, Éloi Sainte-Beuve, Louis-Adrien Dufrène +2Network Traffic Data Compression Methods
Orange Research · 1Orange Research · Université Grenoble Alpes +1
BANDMAS: Causality-Inspired Semantic Packet Scheduling for Bandwidth-Efficient Multi-Agent Collaboration
Aug 1, 2026Jiangwen Dong, Wanyu LinModel-Based Multi-Agent Systems Multi-Agent Coordination
Department of Computing, The Hong Kong Polytechnic University, Hong Kong SAR, China
PCAP-LM: An LLM-Native Text Representation for TLS Bulk Traffic Analysis
Jul 30, 2026Xavier Marjou, Lucas Tamic, Ilan Jaffeux-ChenioutCapture Protocol Network Traffic
Orange
Drift-Aware RL-based Wavelet Denoising for Network-Traffic Anomaly Detection
Jul 22, 2026Priyalakshmi Sheela, Indrakshi DeyWavelets Network Traffic
Walton Institute, Department of Computing, South East Technological University, Waterford, Ireland
Sobek: Streaming Equivariant Tensor Product Convolutions
Jul 20, 2026Vladimir Chorošajev, Cédric BényConvolutional Graph Neural Networks
Cortex Discovery
A Multi-Model Hybrid Defense Approach Against White-box Adversarial Attacks in Computer Network Traffic
Jul 19, 2026Khushnaseeb RoshanBlack-Box Adversarial Attacks Intrusion Detection
Department of Computer Science, Aligarh Muslim University (AMU), Aligarh, INDIA
The Memory Wall of Green Software: Empirical Energy Evaluation of Memento Design Pattern
Jul 8, 2026Imane Jriri, Tarik Houichime, Younes El AmraniPeak Memory Software Engineering
LRIT, Faculty of Science, Mohammed V University In Rabat, Rabat, 10112, Morocco · Meridian Team, LyRICA Laboratory, School of Information Sciences, Rabat 10100, Morocco
Traffic-CBM: A Structurally Interpretable Multimodal Framework for Encrypted Traffic Classification
Jun 29, 2026Honglei Jin, Wenshuo Chen, Shaofeng Liang +6Network Traffic Multimodal Model
HKUST (GZ) Guangzhou, China · Shandong University Qingdao, China
PLAA: Packet-level Adversarial Attacks in Network Traffic Detection
Jun 26, 2026Jinhao You, Zan Zhou, Shujie Yang +3Intrusion Detection Distributed Denial-Of-Service
Beijing University of Posts and Telecommunications · Zhongguancun Laboratory
Timestamp-Aware Spatio-Temporal Graph Contrastive Learning for Network Intrusion Detection
Jun 15, 2026Jianli Dai, Guangwei Wu, Jiacheng Li +3Intrusion Detection Temporal Graph Neural Networks
Central South University of Forestry and Technology, School of Computer Science and Mathematics, Changsha, 410004, Hunan, P.R. China · Central South University, School of Computer Science and Engineering, Changsha, 410083, Hunan, P.R. China
An Improved CNN-LSTM Based Intrusion Detection System for IoT Networks
Jun 4, 2026Mohammad Tariq Ikhlas, Pohanyar Khowaja Khil, Malik Muhammad Mueed Aslam +1Intrusion Detection Internet Of Thing
SEECS NUST, Pakistan
Contrastive Learning and Correlation Clustering for Sequences of Network Telescope Data
Jun 3, 2026Jannik Presberger, Alexander Männel, Maynard Koch +3Network Traffic Contrastive Learning
1TU Dresden · 2HAW Hamburg · Center for Scalable Data Analytics and AI Dresden/Leipzig
Treat Traffic Like Trees: A Semantic-Preserving Hierarchical Graph-Based Expert Framework for Encrypted Traffic Analysis
Jun 3, 2026Yuantu Luo, Jun Tao, Linxiao Yu +1Network Traffic Interleaved Graph Attention
School of Cyber Science and Engineering, Southeast University, Nanjing 211189, China · Purple Mountain Laboratories, Nanjing 210096, China · Engineering Research Center of Blockchain Application, Supervision and Management (Southeast University), MoE, Nanjing 211189, Jiangsu, China +1
GETA: Generalized Encrypted Traffic Analysis
May 29, 2026Ransika Gunasekara, Rahat Masood, Salil KanhereNetwork Traffic Threat Detection
University of New South Wales (UNSW)
A Protocol-Language Model for Network Intrusion (Without Deep Packet Inspection)
May 29, 2026Vivek Kumar SharmaIntrusion Detection Network Traffic
Palo Alto Networks
TraceCodec: A Compiler-Backed Neural Codec for Stateful Multi-Flow Network Traffic Traces
May 28, 2026Junhui Ding, Xinchen Zhang, Xiaohui Xie +1Capture Protocol Network Traffic
Tsinghua University · University of Hong Kong
More Than Meets the Eye: A Semantics-Aware Traffic Augmentation Framework for Generalizable Website Fingerprinting
May 12, 2026Youquan Xian, Xueying Zeng, Lingjia Meng +6Accurate Traffic Forecasting Network Traffic
School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, China · School of Computer Science and Engineering, Beihang University, Beijing, China · Zhongguancun Laboratory, Beijing, China +2
Addressing Labelled Data Scarcity: Taxonomy-Agnostic Annotation of PII Values in HTTP Traffic using LLMs
May 7, 2026Thomas Cory, Axel KüpperLarge Language Model Annotations Human Annotations
Technische Universität Berlin
From Packets to Patterns: Interpreting Encrypted Network Traffic as Longitudinal Behavioral Signals
May 2, 2026Rameen Mahmood, Omar El Shahawy, Souptik Barua +5Network Traffic Sleep
New York University, New York, New York, USA · NYU Langone Health, New York, New York, USA · NYU Grossman School of Medicine, New York, New York, USA +3
Forecasting Individual NetFlows using a Predictive Masked Graph Autoencoder
Apr 22, 2026Georgios Anyfantis, Pere Barlet-RosGraph Neural Networks Accurate Traffic Forecasting
Department of Computer Architecture Universitat Polit`ecnica de Catalunya Barcelona, Spain
TDDM-Melatt: A Decoupled Memory and Diffusion Framework for Generalizable Encrypted Traffic Classification
Date pendingZe Chen, Qiming Yu, Zijia Song +2Network Traffic Diffusion Models
National University of Defense Technology Hefei, Anhui, China

Sep 24, 2026, cs.LGJ/K move · Enter open · S save

FlowAtom: Atom-Based Evidence Aggregation for Multi-Label Website Fingerprinting

Chongru Fan, Wentao Huang, Wei Wang, Zhenquan Ding+3

School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, China · Zhongguancun Laboratory, Beijing, China

Network Traffic Fingerprint Web Information-Flow Control

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Identifying the set of monitored websites in mixed encrypted traffic is challenging because an individual flow often provides only partial evidence of website identity. To address this challenge, we propose FlowAtom, which constructs shared prototypes, called Atoms, from flow representations without website labels. Specifically, FlowAtom pretrains a flow encoder on external unlabeled traffic and aggregates Atom responses across flows within each observation window into a fixed-dimensional, permutation-invariant representation for monitored website-set prediction. Across Direct HTTPS, Trojan, and VMess, FlowAtom achieves micro-F1 scores of 97.82%, 94.43%, and 93.92% in closed-world evaluation, respectively, and consistently outperforms the evaluated baselines in open-world evaluation on windows containing monitored visits. The code is available at https://github.com/aimafan123/FlowAtom.

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