{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:LHSKPG3K4BSZNTLTKIZTYLXYLI","short_pith_number":"pith:LHSKPG3K","schema_version":"1.0","canonical_sha256":"59e4a79b6ae06596cd7352333c2ef85a1655216cecca580183c21335b869c3b8","source":{"kind":"arxiv","id":"2607.29541","version":1},"attestation_state":"computed","paper":{"title":"The K-Space Signature: Frequency-Domain Representation Learning for Medical Deepfake Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Francesco Guarnera, Francesco Rundo, Luca Guarnera, Riccardo Raciti, Sebastiano Battiato","submitted_at":"2026-07-31T15:36:35Z","abstract_excerpt":"In medical imaging, generative models are increasingly deployed to synthesize realistic data and augment limited datasets. Unfortunately, while beneficial for privacy-preserving data sharing, these synthesized images can be repurposed for malicious intents, threatening public health through the creation of Medical Deepfakes. To address this threat, we introduce the K-Space Signature (KSS), a novel forensic framework that isolates hardware and generative traces within the spectral domain. By shifting analysis to the frequency domain, the KSS suppresses macroscopic anatomical variance by subtrac"},"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":"2607.29541","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-31T15:36:35Z","cross_cats_sorted":[],"title_canon_sha256":"3f155eb39bb348ff21da00f1db59dfa331c547d66669bf116599b079ee09a62e","abstract_canon_sha256":"aa3f8639b0fa265df54c34ec1ec81b4f4a00163f7dd16d78028d478112377084"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-03T01:37:53.913001Z","signature_b64":"+9dcGlG7ksYHnxc308VvqxUIgBcCBFHlDRPiEK3Sm1p7NRPvJbpvkQ9zr6lzliqFzxPaIYIYDuSiKbxkGCYUBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"59e4a79b6ae06596cd7352333c2ef85a1655216cecca580183c21335b869c3b8","last_reissued_at":"2026-08-03T01:37:53.911330Z","signature_status":"signed_v1","first_computed_at":"2026-08-03T01:37:53.911330Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"The K-Space Signature: Frequency-Domain Representation Learning for Medical Deepfake Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Francesco Guarnera, Francesco Rundo, Luca Guarnera, Riccardo Raciti, Sebastiano Battiato","submitted_at":"2026-07-31T15:36:35Z","abstract_excerpt":"In medical imaging, generative models are increasingly deployed to synthesize realistic data and augment limited datasets. Unfortunately, while beneficial for privacy-preserving data sharing, these synthesized images can be repurposed for malicious intents, threatening public health through the creation of Medical Deepfakes. To address this threat, we introduce the K-Space Signature (KSS), a novel forensic framework that isolates hardware and generative traces within the spectral domain. By shifting analysis to the frequency domain, the KSS suppresses macroscopic anatomical variance by subtrac"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.29541","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/2607.29541/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":"2607.29541","created_at":"2026-08-03T01:37:53.912350+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.29541v1","created_at":"2026-08-03T01:37:53.912350+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.29541","created_at":"2026-08-03T01:37:53.912350+00:00"},{"alias_kind":"pith_short_12","alias_value":"LHSKPG3K4BSZ","created_at":"2026-08-03T01:37:53.912350+00:00"},{"alias_kind":"pith_short_16","alias_value":"LHSKPG3K4BSZNTLT","created_at":"2026-08-03T01:37:53.912350+00:00"},{"alias_kind":"pith_short_8","alias_value":"LHSKPG3K","created_at":"2026-08-03T01:37:53.912350+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/LHSKPG3K4BSZNTLTKIZTYLXYLI","json":"https://pith.science/pith/LHSKPG3K4BSZNTLTKIZTYLXYLI.json","graph_json":"https://pith.science/api/pith-number/LHSKPG3K4BSZNTLTKIZTYLXYLI/graph.json","events_json":"https://pith.science/api/pith-number/LHSKPG3K4BSZNTLTKIZTYLXYLI/events.json","paper":"https://pith.science/paper/LHSKPG3K"},"agent_actions":{"view_html":"https://pith.science/pith/LHSKPG3K4BSZNTLTKIZTYLXYLI","download_json":"https://pith.science/pith/LHSKPG3K4BSZNTLTKIZTYLXYLI.json","view_paper":"https://pith.science/paper/LHSKPG3K","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.29541&json=true","fetch_graph":"https://pith.science/api/pith-number/LHSKPG3K4BSZNTLTKIZTYLXYLI/graph.json","fetch_events":"https://pith.science/api/pith-number/LHSKPG3K4BSZNTLTKIZTYLXYLI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LHSKPG3K4BSZNTLTKIZTYLXYLI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LHSKPG3K4BSZNTLTKIZTYLXYLI/action/storage_attestation","attest_author":"https://pith.science/pith/LHSKPG3K4BSZNTLTKIZTYLXYLI/action/author_attestation","sign_citation":"https://pith.science/pith/LHSKPG3K4BSZNTLTKIZTYLXYLI/action/citation_signature","submit_replication":"https://pith.science/pith/LHSKPG3K4BSZNTLTKIZTYLXYLI/action/replication_record"}},"created_at":"2026-08-03T01:37:53.912350+00:00","updated_at":"2026-08-03T01:37:53.912350+00:00"}