{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:YJ2KFVPUAG7C3WH6SSFZEX5KFO","short_pith_number":"pith:YJ2KFVPU","schema_version":"1.0","canonical_sha256":"c274a2d5f401be2dd8fe948b925faa2b8e73996d32e237a67b25d7576fdaaad0","source":{"kind":"arxiv","id":"2212.14677","version":1},"attestation_state":"computed","paper":{"title":"Adversarial attacks and defenses on ML- and hardware-based IoT device fingerprinting and identification","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CR","authors_text":"Alberto Huertas Celdr\\'an, G\\'er\\^ome Bovet, Gregorio Mart\\'inez P\\'erez, Pedro Miguel S\\'anchez S\\'anchez","submitted_at":"2022-12-30T13:11:35Z","abstract_excerpt":"In the last years, the number of IoT devices deployed has suffered an undoubted explosion, reaching the scale of billions. However, some new cybersecurity issues have appeared together with this development. Some of these issues are the deployment of unauthorized devices, malicious code modification, malware deployment, or vulnerability exploitation. This fact has motivated the requirement for new device identification mechanisms based on behavior monitoring. Besides, these solutions have recently leveraged Machine and Deep Learning techniques due to the advances in this field and the increase"},"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":"2212.14677","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2022-12-30T13:11:35Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"4b3513a9ecd10faab50c7957e66437544cc57e1cf5d91477e081c22f5f89e928","abstract_canon_sha256":"1fa20bc8b6b5a1df719c6e51b01b5f431c12d66c4045c737831eee6286dee897"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:29:20.424586Z","signature_b64":"/T7KX9Myt4D80xFxotCQt/3RQztdGnrkWhFIxOWIT8ZHLFi/dd4+8tL8mq5zXM3uEtcu76F2mLabUFOrB+M5DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c274a2d5f401be2dd8fe948b925faa2b8e73996d32e237a67b25d7576fdaaad0","last_reissued_at":"2026-07-05T05:29:20.424224Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:29:20.424224Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Adversarial attacks and defenses on ML- and hardware-based IoT device fingerprinting and identification","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CR","authors_text":"Alberto Huertas Celdr\\'an, G\\'er\\^ome Bovet, Gregorio Mart\\'inez P\\'erez, Pedro Miguel S\\'anchez S\\'anchez","submitted_at":"2022-12-30T13:11:35Z","abstract_excerpt":"In the last years, the number of IoT devices deployed has suffered an undoubted explosion, reaching the scale of billions. However, some new cybersecurity issues have appeared together with this development. Some of these issues are the deployment of unauthorized devices, malicious code modification, malware deployment, or vulnerability exploitation. This fact has motivated the requirement for new device identification mechanisms based on behavior monitoring. Besides, these solutions have recently leveraged Machine and Deep Learning techniques due to the advances in this field and the increase"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.14677","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/2212.14677/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":"2212.14677","created_at":"2026-07-05T05:29:20.424279+00:00"},{"alias_kind":"arxiv_version","alias_value":"2212.14677v1","created_at":"2026-07-05T05:29:20.424279+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.14677","created_at":"2026-07-05T05:29:20.424279+00:00"},{"alias_kind":"pith_short_12","alias_value":"YJ2KFVPUAG7C","created_at":"2026-07-05T05:29:20.424279+00:00"},{"alias_kind":"pith_short_16","alias_value":"YJ2KFVPUAG7C3WH6","created_at":"2026-07-05T05:29:20.424279+00:00"},{"alias_kind":"pith_short_8","alias_value":"YJ2KFVPU","created_at":"2026-07-05T05:29:20.424279+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/YJ2KFVPUAG7C3WH6SSFZEX5KFO","json":"https://pith.science/pith/YJ2KFVPUAG7C3WH6SSFZEX5KFO.json","graph_json":"https://pith.science/api/pith-number/YJ2KFVPUAG7C3WH6SSFZEX5KFO/graph.json","events_json":"https://pith.science/api/pith-number/YJ2KFVPUAG7C3WH6SSFZEX5KFO/events.json","paper":"https://pith.science/paper/YJ2KFVPU"},"agent_actions":{"view_html":"https://pith.science/pith/YJ2KFVPUAG7C3WH6SSFZEX5KFO","download_json":"https://pith.science/pith/YJ2KFVPUAG7C3WH6SSFZEX5KFO.json","view_paper":"https://pith.science/paper/YJ2KFVPU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2212.14677&json=true","fetch_graph":"https://pith.science/api/pith-number/YJ2KFVPUAG7C3WH6SSFZEX5KFO/graph.json","fetch_events":"https://pith.science/api/pith-number/YJ2KFVPUAG7C3WH6SSFZEX5KFO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YJ2KFVPUAG7C3WH6SSFZEX5KFO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YJ2KFVPUAG7C3WH6SSFZEX5KFO/action/storage_attestation","attest_author":"https://pith.science/pith/YJ2KFVPUAG7C3WH6SSFZEX5KFO/action/author_attestation","sign_citation":"https://pith.science/pith/YJ2KFVPUAG7C3WH6SSFZEX5KFO/action/citation_signature","submit_replication":"https://pith.science/pith/YJ2KFVPUAG7C3WH6SSFZEX5KFO/action/replication_record"}},"created_at":"2026-07-05T05:29:20.424279+00:00","updated_at":"2026-07-05T05:29:20.424279+00:00"}