{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:WQNMQQ5BDPP7Q3CZT3T2DVGCOM","short_pith_number":"pith:WQNMQQ5B","schema_version":"1.0","canonical_sha256":"b41ac843a11bdff86c599ee7a1d4c273146d646f697fca48ca7ccddda61b1d35","source":{"kind":"arxiv","id":"2508.09660","version":1},"attestation_state":"computed","paper":{"title":"Anomaly Detection for IoT Global Connectivity","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.NI","authors_text":"Andra Lutu, Carlos Segura Perales, Diego Perino, Jesus Oma\\~na Iglesias, Stefan Gei{\\ss}ler","submitted_at":"2025-08-13T09:44:51Z","abstract_excerpt":"Internet of Things (IoT) application providers rely on Mobile Network Operators (MNOs) and roaming infrastructures to deliver their services globally. In this complex ecosystem, where the end-to-end communication path traverses multiple entities, it has become increasingly challenging to guarantee communication availability and reliability. Further, most platform operators use a reactive approach to communication issues, responding to user complaints only after incidents have become severe, compromising service quality. This paper presents our experience in the design and deployment of ANCHOR "},"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":"2508.09660","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.NI","submitted_at":"2025-08-13T09:44:51Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"eda1788fbd3ade2f617565d10a1af8f041e696ed62e2b337e822dcf04b070538","abstract_canon_sha256":"5bde6749c9ca405de21aa789478cf8ad9d1cfa6acafc6380727cd06a3e7fcdd1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:53:19.334461Z","signature_b64":"8v8m8y/27P0I9R+2Wv+zhNmHmQgGOE2R1F5K4sZ+eCZDS5k1ceJllWEimgcG0rkmDzY/BSAORZfunZwwmKLwDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b41ac843a11bdff86c599ee7a1d4c273146d646f697fca48ca7ccddda61b1d35","last_reissued_at":"2026-07-05T11:53:19.333949Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:53:19.333949Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Anomaly Detection for IoT Global Connectivity","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.NI","authors_text":"Andra Lutu, Carlos Segura Perales, Diego Perino, Jesus Oma\\~na Iglesias, Stefan Gei{\\ss}ler","submitted_at":"2025-08-13T09:44:51Z","abstract_excerpt":"Internet of Things (IoT) application providers rely on Mobile Network Operators (MNOs) and roaming infrastructures to deliver their services globally. In this complex ecosystem, where the end-to-end communication path traverses multiple entities, it has become increasingly challenging to guarantee communication availability and reliability. Further, most platform operators use a reactive approach to communication issues, responding to user complaints only after incidents have become severe, compromising service quality. This paper presents our experience in the design and deployment of ANCHOR "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.09660","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/2508.09660/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":"2508.09660","created_at":"2026-07-05T11:53:19.334020+00:00"},{"alias_kind":"arxiv_version","alias_value":"2508.09660v1","created_at":"2026-07-05T11:53:19.334020+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.09660","created_at":"2026-07-05T11:53:19.334020+00:00"},{"alias_kind":"pith_short_12","alias_value":"WQNMQQ5BDPP7","created_at":"2026-07-05T11:53:19.334020+00:00"},{"alias_kind":"pith_short_16","alias_value":"WQNMQQ5BDPP7Q3CZ","created_at":"2026-07-05T11:53:19.334020+00:00"},{"alias_kind":"pith_short_8","alias_value":"WQNMQQ5B","created_at":"2026-07-05T11:53:19.334020+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2508.09664","citing_title":"Multimodal Fusion And Sparse Attention-based Alignment Model for Long Sequential Recommendation","ref_index":1,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/WQNMQQ5BDPP7Q3CZT3T2DVGCOM","json":"https://pith.science/pith/WQNMQQ5BDPP7Q3CZT3T2DVGCOM.json","graph_json":"https://pith.science/api/pith-number/WQNMQQ5BDPP7Q3CZT3T2DVGCOM/graph.json","events_json":"https://pith.science/api/pith-number/WQNMQQ5BDPP7Q3CZT3T2DVGCOM/events.json","paper":"https://pith.science/paper/WQNMQQ5B"},"agent_actions":{"view_html":"https://pith.science/pith/WQNMQQ5BDPP7Q3CZT3T2DVGCOM","download_json":"https://pith.science/pith/WQNMQQ5BDPP7Q3CZT3T2DVGCOM.json","view_paper":"https://pith.science/paper/WQNMQQ5B","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2508.09660&json=true","fetch_graph":"https://pith.science/api/pith-number/WQNMQQ5BDPP7Q3CZT3T2DVGCOM/graph.json","fetch_events":"https://pith.science/api/pith-number/WQNMQQ5BDPP7Q3CZT3T2DVGCOM/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WQNMQQ5BDPP7Q3CZT3T2DVGCOM/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WQNMQQ5BDPP7Q3CZT3T2DVGCOM/action/storage_attestation","attest_author":"https://pith.science/pith/WQNMQQ5BDPP7Q3CZT3T2DVGCOM/action/author_attestation","sign_citation":"https://pith.science/pith/WQNMQQ5BDPP7Q3CZT3T2DVGCOM/action/citation_signature","submit_replication":"https://pith.science/pith/WQNMQQ5BDPP7Q3CZT3T2DVGCOM/action/replication_record"}},"created_at":"2026-07-05T11:53:19.334020+00:00","updated_at":"2026-07-05T11:53:19.334020+00:00"}