{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:XREZJV5CTU5YVRMZZEZCAGF7OO","short_pith_number":"pith:XREZJV5C","schema_version":"1.0","canonical_sha256":"bc4994d7a29d3b8ac599c9322018bf739c8747b7cf6a9e9a55558420474ad3be","source":{"kind":"arxiv","id":"2108.12071","version":2},"attestation_state":"computed","paper":{"title":"Identifying Non-Control Security-Critical Data through Program Dependence Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CR","authors_text":"Haizhou Wang, Hong Hu, Peng Liu, Zhilong Wang","submitted_at":"2021-08-27T00:28:06Z","abstract_excerpt":"As control-flow protection gets widely deployed, it is difficult for attackers to corrupt control-data and achieve control-flow hijacking. Instead, data-oriented attacks, which manipulate non-control data, have been demonstrated to be feasible and powerful. In data-oriented attacks, a fundamental step is to identify non-control, security-critical data. However, critical data identification processes are not scalable in previous works, because they mainly rely on tedious human efforts to identify critical data. To address this issue, we propose a novel approach that combines traditional program"},"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":"2108.12071","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2021-08-27T00:28:06Z","cross_cats_sorted":[],"title_canon_sha256":"a9c6d5b137c14c5d5238542a1acc880508375b0681203e6dd6bfb84c37e5a422","abstract_canon_sha256":"accd33a28d14dd5f766edd52e51ef1848bfa869e2501acbe4112a59ccb5e8c92"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:14:16.528884Z","signature_b64":"BpVq2vf4sGoKGA+H55Qg5rdG2/E3Vf8fppHKxSPhS03MqpEoPNQFXzKRE+rxI04vc46ELaH5UbcNGhAQBNGLBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bc4994d7a29d3b8ac599c9322018bf739c8747b7cf6a9e9a55558420474ad3be","last_reissued_at":"2026-07-05T08:14:16.528426Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:14:16.528426Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Identifying Non-Control Security-Critical Data through Program Dependence Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CR","authors_text":"Haizhou Wang, Hong Hu, Peng Liu, Zhilong Wang","submitted_at":"2021-08-27T00:28:06Z","abstract_excerpt":"As control-flow protection gets widely deployed, it is difficult for attackers to corrupt control-data and achieve control-flow hijacking. Instead, data-oriented attacks, which manipulate non-control data, have been demonstrated to be feasible and powerful. In data-oriented attacks, a fundamental step is to identify non-control, security-critical data. However, critical data identification processes are not scalable in previous works, because they mainly rely on tedious human efforts to identify critical data. To address this issue, we propose a novel approach that combines traditional program"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2108.12071","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2108.12071/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":"2108.12071","created_at":"2026-07-05T08:14:16.528479+00:00"},{"alias_kind":"arxiv_version","alias_value":"2108.12071v2","created_at":"2026-07-05T08:14:16.528479+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2108.12071","created_at":"2026-07-05T08:14:16.528479+00:00"},{"alias_kind":"pith_short_12","alias_value":"XREZJV5CTU5Y","created_at":"2026-07-05T08:14:16.528479+00:00"},{"alias_kind":"pith_short_16","alias_value":"XREZJV5CTU5YVRMZ","created_at":"2026-07-05T08:14:16.528479+00:00"},{"alias_kind":"pith_short_8","alias_value":"XREZJV5C","created_at":"2026-07-05T08:14:16.528479+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/XREZJV5CTU5YVRMZZEZCAGF7OO","json":"https://pith.science/pith/XREZJV5CTU5YVRMZZEZCAGF7OO.json","graph_json":"https://pith.science/api/pith-number/XREZJV5CTU5YVRMZZEZCAGF7OO/graph.json","events_json":"https://pith.science/api/pith-number/XREZJV5CTU5YVRMZZEZCAGF7OO/events.json","paper":"https://pith.science/paper/XREZJV5C"},"agent_actions":{"view_html":"https://pith.science/pith/XREZJV5CTU5YVRMZZEZCAGF7OO","download_json":"https://pith.science/pith/XREZJV5CTU5YVRMZZEZCAGF7OO.json","view_paper":"https://pith.science/paper/XREZJV5C","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2108.12071&json=true","fetch_graph":"https://pith.science/api/pith-number/XREZJV5CTU5YVRMZZEZCAGF7OO/graph.json","fetch_events":"https://pith.science/api/pith-number/XREZJV5CTU5YVRMZZEZCAGF7OO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XREZJV5CTU5YVRMZZEZCAGF7OO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XREZJV5CTU5YVRMZZEZCAGF7OO/action/storage_attestation","attest_author":"https://pith.science/pith/XREZJV5CTU5YVRMZZEZCAGF7OO/action/author_attestation","sign_citation":"https://pith.science/pith/XREZJV5CTU5YVRMZZEZCAGF7OO/action/citation_signature","submit_replication":"https://pith.science/pith/XREZJV5CTU5YVRMZZEZCAGF7OO/action/replication_record"}},"created_at":"2026-07-05T08:14:16.528479+00:00","updated_at":"2026-07-05T08:14:16.528479+00:00"}