pith:WB2BPMDF
Detection of Anomalous Network Nodes via Hierarchical Prediction and Extreme Value Theory
A two-stage method using hierarchical time series prediction of ARP calls followed by extreme value theory flags anomalous network nodes while cutting false positives.
arxiv:2304.13941 v3 · 2023-04-27 · cs.CR
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{WB2BPMDFYAJFJEZBJUHZ26DF5A}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge
Record completeness
Claims
Empirical evaluations on a real-life dataset containing over 10M ARP calls from 362 nodes show that the proposed method results in considerably reduced number of false positives, addressing the problem of alert fatigue commonly reported by security professionals.
That the residuals from the hierarchical time series predictions of ARP behavior follow heavy-tailed distributions for which Extreme Value Theory provides a reliable threshold to separate normal variation from anomalous behavior.
Hierarchical time series prediction of ARP calls combined with Extreme Value Theory identifies anomalous nodes while substantially lowering false positive rates on a real dataset of over 10 million calls.
Receipt and verification
| First computed | 2026-05-26T02:03:44.390000Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
b07417b065c0125493214d0f9d7865e8166b2c49581a8eb60920207cee134aa4
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/WB2BPMDFYAJFJEZBJUHZ26DF5A \
| 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: b07417b065c0125493214d0f9d7865e8166b2c49581a8eb60920207cee134aa4
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "25834a3a4c29e17db70be54647aee3b8098ea2dbcfcb9d8d57457d7e1a66117e",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CR",
"submitted_at": "2023-04-27T03:19:26Z",
"title_canon_sha256": "8f442d6bde68b66c7791b2014ddce01af56c9b53f34d954b685e73f443b23e3c"
},
"schema_version": "1.0",
"source": {
"id": "2304.13941",
"kind": "arxiv",
"version": 3
}
}