mlsanityData to 7 Oct 2026

TraceCodec: A Compiler-Backed Neural Codec for Stateful Multi-Flow Network Traffic Traces

arXiv 2605.29941 ↗First posted 28 May 2026cs.NI cs.LGcited by 0

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Abstract (arXiv)

Critical networking workflows require high-fidelity packet captures (PCAPs) for testing, security analysis, and protocol validation, not just statistical flow-level summaries. Recent packet generators have demonstrated protocol-constrained PCAP synthesis, but they universally decode directly to raw packet fields. That interface entangles learned behavioral choices with deterministic protocol consequences, which forces packet realization to depend on post-hoc heuristic repair. We identify this decode interface as the fundamental bottleneck and present TraceCodec, a state-aware neural codec for stateful multi-flow traces. TraceCodec lifts each packet into a timed packet action with explicit flow slots and transport cues, then learns a continuous per-packet latent. A deterministic compiler lowers decoded actions back to PCAPs, owning endpoint assignment, TCP state, legality constraints, and packet rendering. The latent layer exposes a generator-facing sequence space, so downstream traffic models can operate on packet-action latents rather than raw header fields. On CICIDS2017 Monday, TraceCodec matches packet count, protocol composition, and flow population to within 0.03%. Raw-field baselines under the same non-repair policy distort flow counts and TCP state by orders of magnitude. Structural diagnostics show that TraceCodec preserves TCP state transitions and multi-flow interleaving that raw-field decoders fragment. This work establishes a new foundation for high-fidelity packet-trace generation.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 15 of its 37 references that are in the map. First posted on arXiv 28 May 2026.

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15 of 37 references.

References · 15

  1. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  2. 2017Neural Discrete Representation Learningcited by 4,650
  3. 2021SoundStream: An End-to-End Neural Audio Codeccited by 756
  4. 2019Modeling Tabular data using Conditional GANcited by 695
  5. 2023Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Spacecited by 183
  6. 2017Deep Packet: A Novel Approach For Encrypted Traffic Classification Using Deep Learningcited by 69
  7. 2022ET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic Classificationcited by 66
  8. 2023NetDiffusion: Network Data Augmentation Through Protocol-Constrained Traffic Generationcited by 27
  9. 2020New Directions in Automated Traffic Analysiscited by 26
  10. 2024NetMamba: Efficient Network Traffic Classification via Pre-training Unidirectional Mambacited by 24
  11. 2025TrafficLLM: Enhancing Large Language Models for Network Traffic Analysis with Generic Traffic Representationcited by 15
  12. 2024Robustifying ML-powered Network Classifiers with PANTScited by 6
3 more
  1. 2025Generative Active Adaptation for Drifting and Imbalanced Network Intrusion Detectioncited by 4
  2. 2025NetSSM: Multi-Flow and State-Aware Network Trace Generation using State Space Modelscited by 3
  3. 2026PACC: Protocol-Aware Cross-Layer Compression for Compact Network Traffic Representationcited by 1

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