{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:VQHGC2IJOA2ZX6DCL3Y7AXMPJJ","short_pith_number":"pith:VQHGC2IJ","schema_version":"1.0","canonical_sha256":"ac0e61690970359bf8625ef1f05d8f4a76a4c048fa1c3bc71809f0666c765540","source":{"kind":"arxiv","id":"2608.05605","version":1},"attestation_state":"computed","paper":{"title":"Enhancing Anomaly Resilience in Research Networks: A Large-Scale Forecasting Benchmark for Dynamic Security Baselining","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NI"],"primary_cat":"cs.CR","authors_text":"Byrav Ramamurthy, Mohammad Arafath Uddin Shariff","submitted_at":"2026-08-06T05:04:38Z","abstract_excerpt":"Research and Education Networks (RENs) serve as critical infrastructure for scientific discovery, yet they face a unique security paradox: their normal traffic patterns which are characterized by massive, bursty \"elephant flows\" are statistically indistinguishable from volumetric attacks such as DDoS to conventional monitoring systems. This similarity leads to high false-positive rates in anomaly detection, blinding security operators to genuine threats. In this paper, we propose and evaluate a high-fidelity traffic forecasting framework designed to establish dynamic security baselines for REN"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2608.05605","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2026-08-06T05:04:38Z","cross_cats_sorted":["cs.LG","cs.NI"],"title_canon_sha256":"a6c0a46441844d93918d3083c82988202b2e7e4a1cfc293adccb76f6cc238a74","abstract_canon_sha256":"f6f03b6663909cd5349fdfa2fd6cc18a101d49c00828facc589607d8f422c89d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-07T00:50:17.313819Z","signature_b64":"mHlGpF3u5YagE6jCAyOJEm34OOiaU+nUw6jG/Xaww8AyjEJ4PGRwJ7ryIlVwXZAxk4UpptSog4bKjAWSAhkpBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ac0e61690970359bf8625ef1f05d8f4a76a4c048fa1c3bc71809f0666c765540","last_reissued_at":"2026-08-07T00:50:17.312346Z","signature_status":"signed_v1","first_computed_at":"2026-08-07T00:50:17.312346Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Enhancing Anomaly Resilience in Research Networks: A Large-Scale Forecasting Benchmark for Dynamic Security Baselining","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NI"],"primary_cat":"cs.CR","authors_text":"Byrav Ramamurthy, Mohammad Arafath Uddin Shariff","submitted_at":"2026-08-06T05:04:38Z","abstract_excerpt":"Research and Education Networks (RENs) serve as critical infrastructure for scientific discovery, yet they face a unique security paradox: their normal traffic patterns which are characterized by massive, bursty \"elephant flows\" are statistically indistinguishable from volumetric attacks such as DDoS to conventional monitoring systems. This similarity leads to high false-positive rates in anomaly detection, blinding security operators to genuine threats. In this paper, we propose and evaluate a high-fidelity traffic forecasting framework designed to establish dynamic security baselines for REN"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.05605","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2608.05605/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2608.05605","created_at":"2026-08-07T00:50:17.313826+00:00"},{"alias_kind":"arxiv_version","alias_value":"2608.05605v1","created_at":"2026-08-07T00:50:17.313826+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.05605","created_at":"2026-08-07T00:50:17.313826+00:00"},{"alias_kind":"pith_short_12","alias_value":"VQHGC2IJOA2Z","created_at":"2026-08-07T00:50:17.313826+00:00"},{"alias_kind":"pith_short_16","alias_value":"VQHGC2IJOA2ZX6DC","created_at":"2026-08-07T00:50:17.313826+00:00"},{"alias_kind":"pith_short_8","alias_value":"VQHGC2IJ","created_at":"2026-08-07T00:50:17.313826+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/VQHGC2IJOA2ZX6DCL3Y7AXMPJJ","json":"https://pith.science/pith/VQHGC2IJOA2ZX6DCL3Y7AXMPJJ.json","graph_json":"https://pith.science/api/pith-number/VQHGC2IJOA2ZX6DCL3Y7AXMPJJ/graph.json","events_json":"https://pith.science/api/pith-number/VQHGC2IJOA2ZX6DCL3Y7AXMPJJ/events.json","paper":"https://pith.science/paper/VQHGC2IJ"},"agent_actions":{"view_html":"https://pith.science/pith/VQHGC2IJOA2ZX6DCL3Y7AXMPJJ","download_json":"https://pith.science/pith/VQHGC2IJOA2ZX6DCL3Y7AXMPJJ.json","view_paper":"https://pith.science/paper/VQHGC2IJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2608.05605&json=true","fetch_graph":"https://pith.science/api/pith-number/VQHGC2IJOA2ZX6DCL3Y7AXMPJJ/graph.json","fetch_events":"https://pith.science/api/pith-number/VQHGC2IJOA2ZX6DCL3Y7AXMPJJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VQHGC2IJOA2ZX6DCL3Y7AXMPJJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VQHGC2IJOA2ZX6DCL3Y7AXMPJJ/action/storage_attestation","attest_author":"https://pith.science/pith/VQHGC2IJOA2ZX6DCL3Y7AXMPJJ/action/author_attestation","sign_citation":"https://pith.science/pith/VQHGC2IJOA2ZX6DCL3Y7AXMPJJ/action/citation_signature","submit_replication":"https://pith.science/pith/VQHGC2IJOA2ZX6DCL3Y7AXMPJJ/action/replication_record"}},"created_at":"2026-08-07T00:50:17.313826+00:00","updated_at":"2026-08-07T00:50:17.313826+00:00"}