{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:YXZLFLVP65GMRGPHLMTHWL2MDX","short_pith_number":"pith:YXZLFLVP","schema_version":"1.0","canonical_sha256":"c5f2b2aeaff74cc899e75b267b2f4c1dc1ae9b8be3d681fdf219dc506bb06963","source":{"kind":"arxiv","id":"2605.27497","version":1},"attestation_state":"computed","paper":{"title":"From Provable to Practical: A Problem-Driven Survey of Classical and Machine-Learning Defenses for DV/CV Quantum Key Distribution","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"quant-ph","authors_text":"Afnan S. Al-Ali, Hasan Abbas Al-Mohammed","submitted_at":"2026-05-26T17:44:51Z","abstract_excerpt":"Quantum key distribution (QKD) promises information-theoretic security, yet practical deployments in discrete-variable (DV) and continuous-variable (CV) settings remain exposed to device imperfections, channel manipulation, finite-key effects, and vulnerabilities in machine-learning (ML) components used for adaptation and monitoring. This survey adopts a problem-driven perspective based on nine practical problem classes (P1-P9) spanning device, channel, protocol, ML, and network layers. For each class, we compare classical defenses with ML-enabled solutions including anomaly detection, paramet"},"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":"2605.27497","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2026-05-26T17:44:51Z","cross_cats_sorted":[],"title_canon_sha256":"88681e984bb1e977f18add331443007a34c8a2833727454df57a86861401f834","abstract_canon_sha256":"2e88fda83d2af6340f5fe44549ca2dac05d01292cfa82802e4718c6067f898df"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-28T00:05:21.324885Z","signature_b64":"7pKTu+tp1StG+6etb+rN5kUXPK3dmNYtoMLX0og256JR4qeGKEZ4wQ2tWrwWldmT2QyMXTgMe6ZZLpiTtsr/BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c5f2b2aeaff74cc899e75b267b2f4c1dc1ae9b8be3d681fdf219dc506bb06963","last_reissued_at":"2026-05-28T00:05:21.324173Z","signature_status":"signed_v1","first_computed_at":"2026-05-28T00:05:21.324173Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"From Provable to Practical: A Problem-Driven Survey of Classical and Machine-Learning Defenses for DV/CV Quantum Key Distribution","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"quant-ph","authors_text":"Afnan S. Al-Ali, Hasan Abbas Al-Mohammed","submitted_at":"2026-05-26T17:44:51Z","abstract_excerpt":"Quantum key distribution (QKD) promises information-theoretic security, yet practical deployments in discrete-variable (DV) and continuous-variable (CV) settings remain exposed to device imperfections, channel manipulation, finite-key effects, and vulnerabilities in machine-learning (ML) components used for adaptation and monitoring. This survey adopts a problem-driven perspective based on nine practical problem classes (P1-P9) spanning device, channel, protocol, ML, and network layers. For each class, we compare classical defenses with ML-enabled solutions including anomaly detection, paramet"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.27497","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/2605.27497/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":"2605.27497","created_at":"2026-05-28T00:05:21.324286+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.27497v1","created_at":"2026-05-28T00:05:21.324286+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.27497","created_at":"2026-05-28T00:05:21.324286+00:00"},{"alias_kind":"pith_short_12","alias_value":"YXZLFLVP65GM","created_at":"2026-05-28T00:05:21.324286+00:00"},{"alias_kind":"pith_short_16","alias_value":"YXZLFLVP65GMRGPH","created_at":"2026-05-28T00:05:21.324286+00:00"},{"alias_kind":"pith_short_8","alias_value":"YXZLFLVP","created_at":"2026-05-28T00:05:21.324286+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/YXZLFLVP65GMRGPHLMTHWL2MDX","json":"https://pith.science/pith/YXZLFLVP65GMRGPHLMTHWL2MDX.json","graph_json":"https://pith.science/api/pith-number/YXZLFLVP65GMRGPHLMTHWL2MDX/graph.json","events_json":"https://pith.science/api/pith-number/YXZLFLVP65GMRGPHLMTHWL2MDX/events.json","paper":"https://pith.science/paper/YXZLFLVP"},"agent_actions":{"view_html":"https://pith.science/pith/YXZLFLVP65GMRGPHLMTHWL2MDX","download_json":"https://pith.science/pith/YXZLFLVP65GMRGPHLMTHWL2MDX.json","view_paper":"https://pith.science/paper/YXZLFLVP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.27497&json=true","fetch_graph":"https://pith.science/api/pith-number/YXZLFLVP65GMRGPHLMTHWL2MDX/graph.json","fetch_events":"https://pith.science/api/pith-number/YXZLFLVP65GMRGPHLMTHWL2MDX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YXZLFLVP65GMRGPHLMTHWL2MDX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YXZLFLVP65GMRGPHLMTHWL2MDX/action/storage_attestation","attest_author":"https://pith.science/pith/YXZLFLVP65GMRGPHLMTHWL2MDX/action/author_attestation","sign_citation":"https://pith.science/pith/YXZLFLVP65GMRGPHLMTHWL2MDX/action/citation_signature","submit_replication":"https://pith.science/pith/YXZLFLVP65GMRGPHLMTHWL2MDX/action/replication_record"}},"created_at":"2026-05-28T00:05:21.324286+00:00","updated_at":"2026-05-28T00:05:21.324286+00:00"}