{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2012:K2ZQEYTX6AVV44JOXHZJOSCWE2","short_pith_number":"pith:K2ZQEYTX","schema_version":"1.0","canonical_sha256":"56b3026277f02b5e712eb9f297485626bb3a8a2bbdac5b9679c1ae383ac120b2","source":{"kind":"arxiv","id":"1201.6181","version":2},"attestation_state":"computed","paper":{"title":"Contextual Multi-armed Bandits for the Prevention of Spam in VoIP Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NI","authors_text":"Damien Ernst, Guy Leduc, Sylvain Martin, Tobias Jung","submitted_at":"2012-01-30T11:40:06Z","abstract_excerpt":"In this paper we argue that contextual multi-armed bandit algorithms could open avenues for designing self-learning security modules for computer networks and related tasks. The paper has two contributions: a conceptual one and an algorithmical one. The conceptual contribution is to formulate -- as an example -- the real-world problem of preventing SPIT (Spam in VoIP networks), which is currently not satisfyingly addressed by standard techniques, as a sequential learning problem, namely as a contextual multi-armed bandit. Our second contribution is to present CMABFAS, a new algorithm for gener"},"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":"1201.6181","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2012-01-30T11:40:06Z","cross_cats_sorted":[],"title_canon_sha256":"e16177d78c923184809d526f548805c22a568a6c87f3385a32800e65c8439bac","abstract_canon_sha256":"09ef320dd48623f1962015eaeba1b2abdf6cc5db19cda1e4a1b652362b335878"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:51:14.241188Z","signature_b64":"sr6SnseL6eyq2kyWE55BA5F77M9Co8bKiX37FC1zlWqlxH30AiFQSKupzMyJIL/BiaHil4n8/WRlbc7pqVX2DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"56b3026277f02b5e712eb9f297485626bb3a8a2bbdac5b9679c1ae383ac120b2","last_reissued_at":"2026-05-18T03:51:14.240597Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:51:14.240597Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Contextual Multi-armed Bandits for the Prevention of Spam in VoIP Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NI","authors_text":"Damien Ernst, Guy Leduc, Sylvain Martin, Tobias Jung","submitted_at":"2012-01-30T11:40:06Z","abstract_excerpt":"In this paper we argue that contextual multi-armed bandit algorithms could open avenues for designing self-learning security modules for computer networks and related tasks. The paper has two contributions: a conceptual one and an algorithmical one. The conceptual contribution is to formulate -- as an example -- the real-world problem of preventing SPIT (Spam in VoIP networks), which is currently not satisfyingly addressed by standard techniques, as a sequential learning problem, namely as a contextual multi-armed bandit. Our second contribution is to present CMABFAS, a new algorithm for gener"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1201.6181","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"1201.6181","created_at":"2026-05-18T03:51:14.240690+00:00"},{"alias_kind":"arxiv_version","alias_value":"1201.6181v2","created_at":"2026-05-18T03:51:14.240690+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1201.6181","created_at":"2026-05-18T03:51:14.240690+00:00"},{"alias_kind":"pith_short_12","alias_value":"K2ZQEYTX6AVV","created_at":"2026-05-18T12:27:11.947152+00:00"},{"alias_kind":"pith_short_16","alias_value":"K2ZQEYTX6AVV44JO","created_at":"2026-05-18T12:27:11.947152+00:00"},{"alias_kind":"pith_short_8","alias_value":"K2ZQEYTX","created_at":"2026-05-18T12:27:11.947152+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/K2ZQEYTX6AVV44JOXHZJOSCWE2","json":"https://pith.science/pith/K2ZQEYTX6AVV44JOXHZJOSCWE2.json","graph_json":"https://pith.science/api/pith-number/K2ZQEYTX6AVV44JOXHZJOSCWE2/graph.json","events_json":"https://pith.science/api/pith-number/K2ZQEYTX6AVV44JOXHZJOSCWE2/events.json","paper":"https://pith.science/paper/K2ZQEYTX"},"agent_actions":{"view_html":"https://pith.science/pith/K2ZQEYTX6AVV44JOXHZJOSCWE2","download_json":"https://pith.science/pith/K2ZQEYTX6AVV44JOXHZJOSCWE2.json","view_paper":"https://pith.science/paper/K2ZQEYTX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1201.6181&json=true","fetch_graph":"https://pith.science/api/pith-number/K2ZQEYTX6AVV44JOXHZJOSCWE2/graph.json","fetch_events":"https://pith.science/api/pith-number/K2ZQEYTX6AVV44JOXHZJOSCWE2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/K2ZQEYTX6AVV44JOXHZJOSCWE2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/K2ZQEYTX6AVV44JOXHZJOSCWE2/action/storage_attestation","attest_author":"https://pith.science/pith/K2ZQEYTX6AVV44JOXHZJOSCWE2/action/author_attestation","sign_citation":"https://pith.science/pith/K2ZQEYTX6AVV44JOXHZJOSCWE2/action/citation_signature","submit_replication":"https://pith.science/pith/K2ZQEYTX6AVV44JOXHZJOSCWE2/action/replication_record"}},"created_at":"2026-05-18T03:51:14.240690+00:00","updated_at":"2026-05-18T03:51:14.240690+00:00"}