Pith Number

pith:NFT4R4KH

pith:2026:NFT4R4KH74MQKD4DPUZJ2WE7RV

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Few-Shot Network Intrusion Detection Using Online Triplet Mining

Christos Tachtatzis, Hanan Hindy, Jack Wilkie, Miroslav Bures, Robert Atkinson

A triplet network with online mining and KNN classification detects intrusions competitively after training on only ten malicious samples per class.

arxiv:2605.17530 v1 · 2026-05-17 · cs.CR · cs.AI · cs.LG · cs.NI

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\pithnumber{NFT4R4KH74MQKD4DPUZJ2WE7RV}

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3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

the proposed approach was found to be competitive with existing methods when trained on as little as 10 malicious samples of each class.

C2weakest assumption

That the learned embeddings from the triplet network with online mining will form clusters separable by KNN even when trained on very small numbers of malicious samples from network traffic datasets.

C3one line summary

A triplet network using online triplet mining and KNN classifier achieves competitive few-shot performance on network intrusion detection with as few as 10 malicious samples per class.

References

39 extracted · 39 resolved · 3 Pith anchors

[1] Corporation, I.Cost of a Data Breach Report 2022; Technical Report; IBM Security: Cambridge, MA, USA, 2022 2022

[2] An optimization method for intrusion detection classification model based on deep belief network.IEEE Access2019,7, 87593–87605 2019 · doi:10.1109/access.2019.2925828

[3] An Intrusion Detection Model Based on Feature Reduction and Convolutional Neural Networks.IEEE Access2019,7, 42210–42219 2019 · doi:10.1109/access.2019.2904620

[4] A CNN-LSTM Model for Intrusion Detection System from High Dimensional Data.J 2020

[5] Learning a Neural-network-based Representation for Open Set Recognition 2020

Formal links

1 machine-checked theorem link

Receipt and verification

First computed	2026-05-20T00:04:44.288205Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

6967c8f147ff19050f837d329d589f8d481e3f95b729cf65a509448d38ed2be3

Aliases

arxiv: 2605.17530 · arxiv_version: 2605.17530v1 · doi: 10.48550/arxiv.2605.17530 · pith_short_12: NFT4R4KH74MQ · pith_short_16: NFT4R4KH74MQKD4D · pith_short_8: NFT4R4KH

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/NFT4R4KH74MQKD4DPUZJ2WE7RV \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 6967c8f147ff19050f837d329d589f8d481e3f95b729cf65a509448d38ed2be3

Canonical record JSON

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    "abstract_canon_sha256": "1d7b9da98baf9f635bfe7964f0dbf4e0fb8a4387572e9a7d2cee7bde4cec3efd",
    "cross_cats_sorted": [
      "cs.AI",
      "cs.LG",
      "cs.NI"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CR",
    "submitted_at": "2026-05-17T16:30:06Z",
    "title_canon_sha256": "dadbfb3a66013feedc36369d437a01ac4634f2822aceb8cc7694400594c8ba19"
  },
  "schema_version": "1.0",
  "source": {
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    "kind": "arxiv",
    "version": 1
  }
}