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

• URL: http://arxiv.org/abs/2605.29941v1
• Date: Thu, 28 May 2026 13:52:40 GMT
• Title: TraceCodec: A Compiler-Backed Neural Codec for Stateful Multi-Flow Network Traffic Traces
• Abstract summary: Critical networking legality require high-fidelity packet captures (PCAPs) for testing, security analysis, and protocol validation.<n>Recent packet generators have demonstrated protocol-constrained PCAP synthesis, but they universally decode directly to raw packet fields.<n>We present TraceCodec, a state-aware neural for stateful multi-flow traces.
• Score: 10.977191979493968
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: 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.

Related papers

• TELLER: Non-intrusive Cross-Layer Root-Cause Analysis for LLM Inference [47.62941623025392]
  We present TELLER, a non-intrusive and Log-aware LLM inference Root-cause analysis framework.<n>TELLER collects NVTX/CUPTI traces and service logs without modifying model binaries.<n>It reconstructs per-request call-chain trees and aligns log lines with corresponding execution steps.<n>On top of these representations, TELLER combines numeric candidate localization with a multimodal root-cause model.
  arXiv  Detail & Related papers  (2026-08-03T09:39:11Z)
• Packet-Loss Robust 3D Gaussian Compression via Atomic Packaging and GNN-based Error Concealment [3.679539308969595]
  We propose a packet-loss robust 3DGS transmission and error concealment framework.<n>A lightweight two-layer graph neural network with cross-attention over hash-grid priors refines high-frequency attribute residuals.<n> Experiments under 20 percent random packet loss on BungeeNeRF, Mip-NeRF 360, and Tanks and Temples show that the proposed method substantially improves over no-concealment transmission.
  arXiv  Detail & Related papers  (2026-07-20T13:13:38Z)
• CoStream: Composing Simple Behaviors for Generalizable Complex Manipulation [61.25264898597319]
  We show that complex manipulation capabilities can emerge naturally from the composition of simple, independent behaviors.<n>We propose CoStream, a framework orchestrating foundation models and diverse sensing modalities into multiple composable core behaviors.<n>We demonstrate CoStream on 8 real-world tasks spanning everyday manipulation and precision assembly, with the strongest gains in contact-rich assembly and object transfer.
  arXiv  Detail & Related papers  (2026-06-24T22:25:19Z)
• Space-Time Tradeoffs of Pauli-Based Computation in Distributed qLDPC Architectures [0.15293427903448018]
  Pauli-based computation (PBC) provides a universal framework for executing fault-tolerant quantum algorithms.<n>We investigate the tradeoff between error-correcting code block size and execution time of PBC within the Q-Fly architecture at intermediate scale.<n>We find that large qLDPC code blocks outperform the surface code baseline in terms of execution time by up to an order of magnitude when evaluated against quantum optimization algorithms.
  arXiv  Detail & Related papers  (2026-05-05T15:19:56Z)
• Towards Practical Lossless Neural Compression for LiDAR Point Clouds [84.36825469211375]
  extreme sparsity of high-precision geometric details hinders efficient context modeling.<n>Our framework comprises two lightweight modules.<n>Experiments demonstrate competitive compression performance at real-time speed.
  arXiv  Detail & Related papers  (2026-03-26T10:02:07Z)
• PACC: Protocol-Aware Cross-Layer Compression for Compact Network Traffic Representation [10.787806670196938]
  PACC is a redundancy-aware, layer-aware representation framework.<n>It consistently outperforms feature-engineered and raw-bit baselines.<n>It improves end-to-end efficiency by up to 3.16x.
  arXiv  Detail & Related papers  (2026-02-09T07:09:31Z)
• Plug-and-Play Benchmarking of Reinforcement Learning Algorithms for Large-Scale Flow Control [61.155940786140455]
  Reinforcement learning (RL) has shown promising results in active flow control (AFC)<n>Current AFC benchmarks rely on external computational fluid dynamics (CFD) solvers, are not fully differentiable, and provide limited 3D and multi-agent support.<n>We introduce FluidGym, the first standalone, fully differentiable benchmark suite for RL in AFC.
  arXiv  Detail & Related papers  (2026-01-21T14:13:44Z)
• Uncovering Gaps Between RFC Updates and TCP/IP Implementations: LLM-Facilitated Differential Checks on Intermediate Representations [21.889716987837428]
  There are often inconsistencies between the implementation of the protocol stack code and the RFC standard.<n>This inconsistency may not only lead to differences in protocol functions but also cause serious security vulnerabilities.<n>With the rise of large language models, researchers have begun to explore how to extract protocol specifications from RFC documents.
  arXiv  Detail & Related papers  (2025-10-28T13:19:46Z)
• Conquering High Packet-Loss Erasure: MoE Swin Transformer-Based Video Semantic Communication [11.845717685362814]
  packet-loss-resistant MoE Swin Transformer-based Video Semantic Communication (MSTVSC) system is proposed in this paper.<n>To address this issue, a packet-loss-resistant MoE Swin Transformer-based Video Semantic Communication (MSTVSC) system is proposed in this paper.
  arXiv  Detail & Related papers  (2025-08-02T05:41:52Z)
• MIETT: Multi-Instance Encrypted Traffic Transformer for Encrypted Traffic Classification [59.96233305733875]
  Classifying traffic is essential for detecting security threats and optimizing network management.<n>We propose a Multi-Instance Encrypted Traffic Transformer (MIETT) to capture both token-level and packet-level relationships.<n>MIETT achieves results across five datasets, demonstrating its effectiveness in classifying encrypted traffic and understanding complex network behaviors.
  arXiv  Detail & Related papers  (2024-12-19T12:52:53Z)
• Data post-processing for the one-way heterodyne protocol under composable finite-size security [62.997667081978825]
  We study the performance of a practical continuous-variable (CV) quantum key distribution protocol. We focus on the Gaussian-modulated coherent-state protocol with heterodyne detection in a high signal-to-noise ratio regime. This allows us to study the performance for practical implementations of the protocol and optimize the parameters connected to the steps above.
  arXiv  Detail & Related papers  (2022-05-20T12:37:09Z)
• Fast and Secure Routing Algorithms for Quantum Key Distribution Networks [5.659290426197763]
  We consider the problem of secure packet routing at the maximum achievable rate in Quantum Key Distribution (QKD) networks. We propose a new secure throughput-optimal policy called Tandem Queue Decomposition (TQD) We show that the TQD policy solves the problem of secure and efficient packet routing for a broad class of traffic, including unicast, broadcast, multicast, and anycast.
  arXiv  Detail & Related papers  (2021-09-16T12:29:41Z)
• Composably secure data processing for Gaussian-modulated continuous variable quantum key distribution [58.720142291102135]
  Continuous-variable quantum key distribution (QKD) employs the quadratures of a bosonic mode to establish a secret key between two remote parties. We consider a protocol with homodyne detection in the general setting of composable finite-size security. In particular, we analyze the high signal-to-noise regime which requires the use of high-rate (non-binary) low-density parity check codes.
  arXiv  Detail & Related papers  (2021-03-30T18:02:55Z)
• End-to-End Object Detection with Transformers [88.06357745922716]
  We present a new method that views object detection as a direct set prediction problem. Our approach streamlines the detection pipeline, effectively removing the need for many hand-designed components. The main ingredients of the new framework, called DEtection TRansformer or DETR, are a set-based global loss.
  arXiv  Detail & Related papers  (2020-05-26T17:06:38Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.