{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:CYFZACZUBJCF2NKY7UTBIXI6OV","short_pith_number":"pith:CYFZACZU","schema_version":"1.0","canonical_sha256":"160b900b340a445d3558fd26145d1e757a14c81594e0433653902a1431a8eacf","source":{"kind":"arxiv","id":"1701.04174","version":2},"attestation_state":"computed","paper":{"title":"Quantifying vulnerability of secret generation using hyper-distributions (extended version)","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CR","authors_text":"M\\'ario S. Alvim, Michael Hicks, Piotr Mardziel","submitted_at":"2017-01-16T05:44:05Z","abstract_excerpt":"Traditional approaches to Quantitative Information Flow (QIF) represent the adversary's prior knowledge of possible secret values as a single probability distribution. This representation may miss important structure. For instance, representing prior knowledge about passwords of a system's users in this way overlooks the fact that many users generate passwords using some strategy. Knowledge of such strategies can help the adversary in guessing a secret, so ignoring them may underestimate the secret's vulnerability. In this paper we explicitly model strategies as distributions on secrets, and g"},"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":"1701.04174","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2017-01-16T05:44:05Z","cross_cats_sorted":[],"title_canon_sha256":"607de3f65887337d0a51c26f14ef6e408c123cfe7a5d337ee6f4f17c6ae5b7e9","abstract_canon_sha256":"9751df11dfcdf618021ad1529dbbf1f7b57bb84c34c73b476ec142ff822a7606"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:52:22.191832Z","signature_b64":"8/mrTrOh8Znsefjf2GIRKsxiR1jOZqFxN4hA0Jk7noes21LWIUXgY9plLXJ1oYBf3UMRgKeSMk/2t7XAwKoCAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"160b900b340a445d3558fd26145d1e757a14c81594e0433653902a1431a8eacf","last_reissued_at":"2026-05-18T00:52:22.190989Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:52:22.190989Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Quantifying vulnerability of secret generation using hyper-distributions (extended version)","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CR","authors_text":"M\\'ario S. Alvim, Michael Hicks, Piotr Mardziel","submitted_at":"2017-01-16T05:44:05Z","abstract_excerpt":"Traditional approaches to Quantitative Information Flow (QIF) represent the adversary's prior knowledge of possible secret values as a single probability distribution. This representation may miss important structure. For instance, representing prior knowledge about passwords of a system's users in this way overlooks the fact that many users generate passwords using some strategy. Knowledge of such strategies can help the adversary in guessing a secret, so ignoring them may underestimate the secret's vulnerability. In this paper we explicitly model strategies as distributions on secrets, and g"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1701.04174","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":"1701.04174","created_at":"2026-05-18T00:52:22.191120+00:00"},{"alias_kind":"arxiv_version","alias_value":"1701.04174v2","created_at":"2026-05-18T00:52:22.191120+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1701.04174","created_at":"2026-05-18T00:52:22.191120+00:00"},{"alias_kind":"pith_short_12","alias_value":"CYFZACZUBJCF","created_at":"2026-05-18T12:31:10.602751+00:00"},{"alias_kind":"pith_short_16","alias_value":"CYFZACZUBJCF2NKY","created_at":"2026-05-18T12:31:10.602751+00:00"},{"alias_kind":"pith_short_8","alias_value":"CYFZACZU","created_at":"2026-05-18T12:31:10.602751+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/CYFZACZUBJCF2NKY7UTBIXI6OV","json":"https://pith.science/pith/CYFZACZUBJCF2NKY7UTBIXI6OV.json","graph_json":"https://pith.science/api/pith-number/CYFZACZUBJCF2NKY7UTBIXI6OV/graph.json","events_json":"https://pith.science/api/pith-number/CYFZACZUBJCF2NKY7UTBIXI6OV/events.json","paper":"https://pith.science/paper/CYFZACZU"},"agent_actions":{"view_html":"https://pith.science/pith/CYFZACZUBJCF2NKY7UTBIXI6OV","download_json":"https://pith.science/pith/CYFZACZUBJCF2NKY7UTBIXI6OV.json","view_paper":"https://pith.science/paper/CYFZACZU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1701.04174&json=true","fetch_graph":"https://pith.science/api/pith-number/CYFZACZUBJCF2NKY7UTBIXI6OV/graph.json","fetch_events":"https://pith.science/api/pith-number/CYFZACZUBJCF2NKY7UTBIXI6OV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CYFZACZUBJCF2NKY7UTBIXI6OV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CYFZACZUBJCF2NKY7UTBIXI6OV/action/storage_attestation","attest_author":"https://pith.science/pith/CYFZACZUBJCF2NKY7UTBIXI6OV/action/author_attestation","sign_citation":"https://pith.science/pith/CYFZACZUBJCF2NKY7UTBIXI6OV/action/citation_signature","submit_replication":"https://pith.science/pith/CYFZACZUBJCF2NKY7UTBIXI6OV/action/replication_record"}},"created_at":"2026-05-18T00:52:22.191120+00:00","updated_at":"2026-05-18T00:52:22.191120+00:00"}