{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:SQVRAQ2CW4D7W3VRIHMYHUA5CS","short_pith_number":"pith:SQVRAQ2C","schema_version":"1.0","canonical_sha256":"942b104342b707fb6eb141d983d01d14bd18cd0b74ad4814e31f0b5b817c41b1","source":{"kind":"arxiv","id":"2309.01386","version":1},"attestation_state":"computed","paper":{"title":"SemProtector: A Unified Framework for Semantic Protection in Deep Learning-based Semantic Communication Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CR","authors_text":"Guoshun Nan, Hanqing Mu, Peiyuan Liu, Qimei Cui, Tony Q.S. Quek, Xiaofeng Tao, Xinghan Liu, Zebin Xing, Zeju Li","submitted_at":"2023-09-04T06:34:43Z","abstract_excerpt":"Recently proliferated semantic communications (SC) aim at effectively transmitting the semantics conveyed by the source and accurately interpreting the meaning at the destination. While such a paradigm holds the promise of making wireless communications more intelligent, it also suffers from severe semantic security issues, such as eavesdropping, privacy leaking, and spoofing, due to the open nature of wireless channels and the fragility of neural modules. Previous works focus more on the robustness of SC via offline adversarial training of the whole system, while online semantic protection, a"},"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":"2309.01386","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2023-09-04T06:34:43Z","cross_cats_sorted":[],"title_canon_sha256":"c8e88f356065d0890fef7cf47c07655ca10521cb0b5e98d1192b0c2d6d69bdd4","abstract_canon_sha256":"ba10526e625e07c1060f292b079248ae0f5a63d01666c45da36a04f8c8599306"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:47:37.253443Z","signature_b64":"atOJsmZfJ3wnrkdUlDQRzmnhBmt+cUikXShzTsyk3ubme7p7bvBRl0nBqqrtWNeCN+WxUaJcRLRJImB0c7LPAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"942b104342b707fb6eb141d983d01d14bd18cd0b74ad4814e31f0b5b817c41b1","last_reissued_at":"2026-07-05T06:47:37.252964Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:47:37.252964Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"SemProtector: A Unified Framework for Semantic Protection in Deep Learning-based Semantic Communication Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CR","authors_text":"Guoshun Nan, Hanqing Mu, Peiyuan Liu, Qimei Cui, Tony Q.S. Quek, Xiaofeng Tao, Xinghan Liu, Zebin Xing, Zeju Li","submitted_at":"2023-09-04T06:34:43Z","abstract_excerpt":"Recently proliferated semantic communications (SC) aim at effectively transmitting the semantics conveyed by the source and accurately interpreting the meaning at the destination. While such a paradigm holds the promise of making wireless communications more intelligent, it also suffers from severe semantic security issues, such as eavesdropping, privacy leaking, and spoofing, due to the open nature of wireless channels and the fragility of neural modules. Previous works focus more on the robustness of SC via offline adversarial training of the whole system, while online semantic protection, a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.01386","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/2309.01386/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":"2309.01386","created_at":"2026-07-05T06:47:37.253022+00:00"},{"alias_kind":"arxiv_version","alias_value":"2309.01386v1","created_at":"2026-07-05T06:47:37.253022+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.01386","created_at":"2026-07-05T06:47:37.253022+00:00"},{"alias_kind":"pith_short_12","alias_value":"SQVRAQ2CW4D7","created_at":"2026-07-05T06:47:37.253022+00:00"},{"alias_kind":"pith_short_16","alias_value":"SQVRAQ2CW4D7W3VR","created_at":"2026-07-05T06:47:37.253022+00:00"},{"alias_kind":"pith_short_8","alias_value":"SQVRAQ2C","created_at":"2026-07-05T06:47:37.253022+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/SQVRAQ2CW4D7W3VRIHMYHUA5CS","json":"https://pith.science/pith/SQVRAQ2CW4D7W3VRIHMYHUA5CS.json","graph_json":"https://pith.science/api/pith-number/SQVRAQ2CW4D7W3VRIHMYHUA5CS/graph.json","events_json":"https://pith.science/api/pith-number/SQVRAQ2CW4D7W3VRIHMYHUA5CS/events.json","paper":"https://pith.science/paper/SQVRAQ2C"},"agent_actions":{"view_html":"https://pith.science/pith/SQVRAQ2CW4D7W3VRIHMYHUA5CS","download_json":"https://pith.science/pith/SQVRAQ2CW4D7W3VRIHMYHUA5CS.json","view_paper":"https://pith.science/paper/SQVRAQ2C","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2309.01386&json=true","fetch_graph":"https://pith.science/api/pith-number/SQVRAQ2CW4D7W3VRIHMYHUA5CS/graph.json","fetch_events":"https://pith.science/api/pith-number/SQVRAQ2CW4D7W3VRIHMYHUA5CS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SQVRAQ2CW4D7W3VRIHMYHUA5CS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SQVRAQ2CW4D7W3VRIHMYHUA5CS/action/storage_attestation","attest_author":"https://pith.science/pith/SQVRAQ2CW4D7W3VRIHMYHUA5CS/action/author_attestation","sign_citation":"https://pith.science/pith/SQVRAQ2CW4D7W3VRIHMYHUA5CS/action/citation_signature","submit_replication":"https://pith.science/pith/SQVRAQ2CW4D7W3VRIHMYHUA5CS/action/replication_record"}},"created_at":"2026-07-05T06:47:37.253022+00:00","updated_at":"2026-07-05T06:47:37.253022+00:00"}