{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:FHF7OQYTWDWTF2JB3CWKE3I3OZ","short_pith_number":"pith:FHF7OQYT","canonical_record":{"source":{"id":"1705.07512","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2017-05-21T21:47:21Z","cross_cats_sorted":[],"title_canon_sha256":"047b0a77e9c560f267a1a443425bbdcb1c9132a852225b566d7a63c545c1e577","abstract_canon_sha256":"b8beadc9980155f4f9741f4ed1f9bbfd79cb1d3a9f2511148d696504726c125e"},"schema_version":"1.0"},"canonical_sha256":"29cbf74313b0ed32e921d8aca26d1b7648ec354fb27097b49ff801bb0f1e155a","source":{"kind":"arxiv","id":"1705.07512","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1705.07512","created_at":"2026-05-18T00:44:05Z"},{"alias_kind":"arxiv_version","alias_value":"1705.07512v1","created_at":"2026-05-18T00:44:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.07512","created_at":"2026-05-18T00:44:05Z"},{"alias_kind":"pith_short_12","alias_value":"FHF7OQYTWDWT","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_16","alias_value":"FHF7OQYTWDWTF2JB","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_8","alias_value":"FHF7OQYT","created_at":"2026-05-18T12:31:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:FHF7OQYTWDWTF2JB3CWKE3I3OZ","target":"record","payload":{"canonical_record":{"source":{"id":"1705.07512","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2017-05-21T21:47:21Z","cross_cats_sorted":[],"title_canon_sha256":"047b0a77e9c560f267a1a443425bbdcb1c9132a852225b566d7a63c545c1e577","abstract_canon_sha256":"b8beadc9980155f4f9741f4ed1f9bbfd79cb1d3a9f2511148d696504726c125e"},"schema_version":"1.0"},"canonical_sha256":"29cbf74313b0ed32e921d8aca26d1b7648ec354fb27097b49ff801bb0f1e155a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:44:05.334156Z","signature_b64":"v6IhgMwl5BKCb6ds0UsFPoeOAn1MgRPtahycyGNZyHdBmiYytYLUbLcqCekxmGWyNeQcYBRM+BSIqnOF00RYAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"29cbf74313b0ed32e921d8aca26d1b7648ec354fb27097b49ff801bb0f1e155a","last_reissued_at":"2026-05-18T00:44:05.333529Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:44:05.333529Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1705.07512","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:44:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5+whl54mhmVIg/kxbovT1ZCaHsqPBQQUDhplkc7d5j1PAZKGmTb0xWeGGZqgL6hQObYjcGzWmGL2VP9beqyICw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T15:45:15.991168Z"},"content_sha256":"0160caa739b75bfe674b9226c78b324c15375ebc6f67669c83a4c4767b6598b1","schema_version":"1.0","event_id":"sha256:0160caa739b75bfe674b9226c78b324c15375ebc6f67669c83a4c4767b6598b1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:FHF7OQYTWDWTF2JB3CWKE3I3OZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Pyramid: Enhancing Selectivity in Big Data Protection with Count Featurization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CR","authors_text":"Mathias Lecuyer, Riley Spahn, Roxana Geambasu, Siddhartha Sen, Tzu-Kuo Huang","submitted_at":"2017-05-21T21:47:21Z","abstract_excerpt":"Protecting vast quantities of data poses a daunting challenge for the growing number of organizations that collect, stockpile, and monetize it. The ability to distinguish data that is actually needed from data collected \"just in case\" would help these organizations to limit the latter's exposure to attack. A natural approach might be to monitor data use and retain only the working-set of in-use data in accessible storage; unused data can be evicted to a highly protected store. However, many of today's big data applications rely on machine learning (ML) workloads that are periodically retrained"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.07512","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":""},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:44:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mEDX8kwPfN6KIi9WkBEaKszWlzctE+pg/zpRdoAKYxNzLZWmbKr711keoiU63Y/m1rO9/bRYzyqePxK8JAWxDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T15:45:15.991591Z"},"content_sha256":"45649e0986a2f2caa96c434feff601503dcd743f7098c18c5ad57baa943e93cc","schema_version":"1.0","event_id":"sha256:45649e0986a2f2caa96c434feff601503dcd743f7098c18c5ad57baa943e93cc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FHF7OQYTWDWTF2JB3CWKE3I3OZ/bundle.json","state_url":"https://pith.science/pith/FHF7OQYTWDWTF2JB3CWKE3I3OZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FHF7OQYTWDWTF2JB3CWKE3I3OZ/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-31T15:45:15Z","links":{"resolver":"https://pith.science/pith/FHF7OQYTWDWTF2JB3CWKE3I3OZ","bundle":"https://pith.science/pith/FHF7OQYTWDWTF2JB3CWKE3I3OZ/bundle.json","state":"https://pith.science/pith/FHF7OQYTWDWTF2JB3CWKE3I3OZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FHF7OQYTWDWTF2JB3CWKE3I3OZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:FHF7OQYTWDWTF2JB3CWKE3I3OZ","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"b8beadc9980155f4f9741f4ed1f9bbfd79cb1d3a9f2511148d696504726c125e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2017-05-21T21:47:21Z","title_canon_sha256":"047b0a77e9c560f267a1a443425bbdcb1c9132a852225b566d7a63c545c1e577"},"schema_version":"1.0","source":{"id":"1705.07512","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1705.07512","created_at":"2026-05-18T00:44:05Z"},{"alias_kind":"arxiv_version","alias_value":"1705.07512v1","created_at":"2026-05-18T00:44:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.07512","created_at":"2026-05-18T00:44:05Z"},{"alias_kind":"pith_short_12","alias_value":"FHF7OQYTWDWT","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_16","alias_value":"FHF7OQYTWDWTF2JB","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_8","alias_value":"FHF7OQYT","created_at":"2026-05-18T12:31:15Z"}],"graph_snapshots":[{"event_id":"sha256:45649e0986a2f2caa96c434feff601503dcd743f7098c18c5ad57baa943e93cc","target":"graph","created_at":"2026-05-18T00:44:05Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Protecting vast quantities of data poses a daunting challenge for the growing number of organizations that collect, stockpile, and monetize it. The ability to distinguish data that is actually needed from data collected \"just in case\" would help these organizations to limit the latter's exposure to attack. A natural approach might be to monitor data use and retain only the working-set of in-use data in accessible storage; unused data can be evicted to a highly protected store. However, many of today's big data applications rely on machine learning (ML) workloads that are periodically retrained","authors_text":"Mathias Lecuyer, Riley Spahn, Roxana Geambasu, Siddhartha Sen, Tzu-Kuo Huang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2017-05-21T21:47:21Z","title":"Pyramid: Enhancing Selectivity in Big Data Protection with Count Featurization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.07512","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:0160caa739b75bfe674b9226c78b324c15375ebc6f67669c83a4c4767b6598b1","target":"record","created_at":"2026-05-18T00:44:05Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"b8beadc9980155f4f9741f4ed1f9bbfd79cb1d3a9f2511148d696504726c125e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2017-05-21T21:47:21Z","title_canon_sha256":"047b0a77e9c560f267a1a443425bbdcb1c9132a852225b566d7a63c545c1e577"},"schema_version":"1.0","source":{"id":"1705.07512","kind":"arxiv","version":1}},"canonical_sha256":"29cbf74313b0ed32e921d8aca26d1b7648ec354fb27097b49ff801bb0f1e155a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"29cbf74313b0ed32e921d8aca26d1b7648ec354fb27097b49ff801bb0f1e155a","first_computed_at":"2026-05-18T00:44:05.333529Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:44:05.333529Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"v6IhgMwl5BKCb6ds0UsFPoeOAn1MgRPtahycyGNZyHdBmiYytYLUbLcqCekxmGWyNeQcYBRM+BSIqnOF00RYAw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:44:05.334156Z","signed_message":"canonical_sha256_bytes"},"source_id":"1705.07512","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0160caa739b75bfe674b9226c78b324c15375ebc6f67669c83a4c4767b6598b1","sha256:45649e0986a2f2caa96c434feff601503dcd743f7098c18c5ad57baa943e93cc"],"state_sha256":"8258b65e6dcaa429a7773a40a22385a1cac277d9808fd5c0edcdfcf1af00a0fa"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1USJ4Y59Lsyz0UAgqyMwiG9PRNqQW0pcs4YzgfrMO8yM7vi3nzFaAI1Hw+evia2ZNRqC7kJGq3GSktkJp71GAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T15:45:15.994142Z","bundle_sha256":"0510f04a79f916c9419e90db031b1ab8d38343afe60f26e0dcc497b86f457521"}}