• Computer Science > Networking and Internet Architecture [Submitted on 25 Feb 2026] Title:Lossy Compression of Network Feature Data: When Less Is Enough View PDF HTML (experimental)Abstract:Network traffic analysis increasingly relies on feature-based representations to support monitoring and security in the presence of pervasive encryption • Although features are more compact than raw packet traces, their storage has become a scalability bottleneck from large-scale core networks to resource-constrained Internet of Things (IoT) environments • This article investigates task-aware lossy compression strategies that reduce the storage footprint of traffic features while preserving analytics accuracy • Using website classification in core networks and device identification in IoT environments as representative use cases, we show that simple, semantics-preserving compression techniques expose stable operating regions that balance storage efficiency and task performance • These results highlight compression as a first-class design dimension in scalable network monitoring systems • References & Citations export BibTeX citation Loading

Article Summaries:

  • Computer Science > Networking and Internet Architecture [Submitted on 25 Feb 2026] Title:Lossy Compression of Network Feature Data: When Less Is Enough View PDF HTML (experimental)Abstract:Network traffic analysis increasingly relies on feature-based representations to support monitoring and security in the presence of pervasive encryption. Although features are more compact than raw packet traces, their storage has become a scalability bottleneck from large-scale core networks to resource-constrained Internet of Things (IoT) environments. This article investigates task-aware lossy compression

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