Datasets › SIDD-Image

SIDD-Image (Segmented Intrusion Detection Dataset)

Introduced by Yuwei Sun et al. in Adaptive Intrusion Detection in the Networking of Large-Scale LANs with Segmented Federated Learning16 Dec 2020 archive 2025-07-28

This is the first image-based network intrusion detection dataset. This large-scale dataset included network traffic protocol communication-based images from 15 different observation locations of different countries in Asia. This dataset is used to identify two different types of anomalies from benign network traffic. Each image with a size of 48 × 48 contains multi-protocol communications within 128 seconds. The SIDD dataset can be to applied to a broad range of tasks such as machine learning-based network intrusion detection, non-iid federated learning, and so forth.

Benchmarks archive 2025-07-28

All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Network Intrusion Detection SIDD-Image Segmented-FL F1 Score 0.893 Intrusion Detection with Segmented Federated Learning... yuweisunn/segmented-FL 1 Compare

Papers archive 2025-07-28

1 shown of 1 paper with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 3. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
Intrusion Detection with Segmented Federated Learning for Large-Scale Multiple LANs 1 1 28 Sep 2020 not harvested

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

CC-BY

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • SIDD-Image

1 variant name, as the archive lists them.

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