{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:56PCRAQZVTDAPIHQSPEY2NM34O","short_pith_number":"pith:56PCRAQZ","canonical_record":{"source":{"id":"1906.11327","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2019-06-26T20:15:54Z","cross_cats_sorted":["cs.CG","cs.CR","cs.DB","cs.DC"],"title_canon_sha256":"873ccf74a7597060e5dff7c48dd5f8bd0dbe7389eafd7656f5f30eabe08600c7","abstract_canon_sha256":"bbdf5ce0746d1cffb174fd09076a6a14c2a025d3135dfa7767e0794e8a89f7f8"},"schema_version":"1.0"},"canonical_sha256":"ef9e288219acc607a0f093c98d359be39a65fa64de482b7208724520131f2d2e","source":{"kind":"arxiv","id":"1906.11327","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.11327","created_at":"2026-05-17T23:42:07Z"},{"alias_kind":"arxiv_version","alias_value":"1906.11327v1","created_at":"2026-05-17T23:42:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.11327","created_at":"2026-05-17T23:42:07Z"},{"alias_kind":"pith_short_12","alias_value":"56PCRAQZVTDA","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"56PCRAQZVTDAPIHQ","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"56PCRAQZ","created_at":"2026-05-18T12:33:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:56PCRAQZVTDAPIHQSPEY2NM34O","target":"record","payload":{"canonical_record":{"source":{"id":"1906.11327","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2019-06-26T20:15:54Z","cross_cats_sorted":["cs.CG","cs.CR","cs.DB","cs.DC"],"title_canon_sha256":"873ccf74a7597060e5dff7c48dd5f8bd0dbe7389eafd7656f5f30eabe08600c7","abstract_canon_sha256":"bbdf5ce0746d1cffb174fd09076a6a14c2a025d3135dfa7767e0794e8a89f7f8"},"schema_version":"1.0"},"canonical_sha256":"ef9e288219acc607a0f093c98d359be39a65fa64de482b7208724520131f2d2e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:42:07.510763Z","signature_b64":"lGgvcFZAAK6LuTPcLFRxs66jtwM83A2mE0VLrmHEnJbiWJXSkYYKOB7DNRgdKla0SUdGpmsIkT3r6a9PYH1kAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ef9e288219acc607a0f093c98d359be39a65fa64de482b7208724520131f2d2e","last_reissued_at":"2026-05-17T23:42:07.510180Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:42:07.510180Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.11327","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":"2026-05-17T23:42:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"92HnUFmfa3v0Q5ssxSQzEC0xhzV31yutNUMu+wrbihUVR+TFGhv1+FOVPZEW5InLIiCsFppKLDWwugxEc53VDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T04:39:06.525574Z"},"content_sha256":"342d4c4f2334424d823487be08be2fc4a271ad7aa011789df9c23c23e612e00e","schema_version":"1.0","event_id":"sha256:342d4c4f2334424d823487be08be2fc4a271ad7aa011789df9c23c23e612e00e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:56PCRAQZVTDAPIHQSPEY2NM34O","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"The Adversarial Robustness of Sampling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CG","cs.CR","cs.DB","cs.DC"],"primary_cat":"cs.DS","authors_text":"Eylon Yogev, Omri Ben-Eliezer","submitted_at":"2019-06-26T20:15:54Z","abstract_excerpt":"Random sampling is a fundamental primitive in modern algorithms, statistics, and machine learning, used as a generic method to obtain a small yet \"representative\" subset of the data. In this work, we investigate the robustness of sampling against adaptive adversarial attacks in a streaming setting: An adversary sends a stream of elements from a universe $U$ to a sampling algorithm (e.g., Bernoulli sampling or reservoir sampling), with the goal of making the sample \"very unrepresentative\" of the underlying data stream. The adversary is fully adaptive in the sense that it knows the exact content"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.11327","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":"2026-05-17T23:42:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oPcSmn/WIGRfObTnazkzjXL21SociMwWd03Htz2S7ga1WERk+erHhueqXoOh5N+K45DpbFKF54fMnEgJYzk5Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T04:39:06.525960Z"},"content_sha256":"db8ec689f48895a4c4b521b27cd5d123a0f10f1b6d075defcc1f4593c6194f82","schema_version":"1.0","event_id":"sha256:db8ec689f48895a4c4b521b27cd5d123a0f10f1b6d075defcc1f4593c6194f82"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/56PCRAQZVTDAPIHQSPEY2NM34O/bundle.json","state_url":"https://pith.science/pith/56PCRAQZVTDAPIHQSPEY2NM34O/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/56PCRAQZVTDAPIHQSPEY2NM34O/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":"2026-05-26T04:39:06Z","links":{"resolver":"https://pith.science/pith/56PCRAQZVTDAPIHQSPEY2NM34O","bundle":"https://pith.science/pith/56PCRAQZVTDAPIHQSPEY2NM34O/bundle.json","state":"https://pith.science/pith/56PCRAQZVTDAPIHQSPEY2NM34O/state.json","well_known_bundle":"https://pith.science/.well-known/pith/56PCRAQZVTDAPIHQSPEY2NM34O/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:56PCRAQZVTDAPIHQSPEY2NM34O","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":"bbdf5ce0746d1cffb174fd09076a6a14c2a025d3135dfa7767e0794e8a89f7f8","cross_cats_sorted":["cs.CG","cs.CR","cs.DB","cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2019-06-26T20:15:54Z","title_canon_sha256":"873ccf74a7597060e5dff7c48dd5f8bd0dbe7389eafd7656f5f30eabe08600c7"},"schema_version":"1.0","source":{"id":"1906.11327","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.11327","created_at":"2026-05-17T23:42:07Z"},{"alias_kind":"arxiv_version","alias_value":"1906.11327v1","created_at":"2026-05-17T23:42:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.11327","created_at":"2026-05-17T23:42:07Z"},{"alias_kind":"pith_short_12","alias_value":"56PCRAQZVTDA","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"56PCRAQZVTDAPIHQ","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"56PCRAQZ","created_at":"2026-05-18T12:33:10Z"}],"graph_snapshots":[{"event_id":"sha256:db8ec689f48895a4c4b521b27cd5d123a0f10f1b6d075defcc1f4593c6194f82","target":"graph","created_at":"2026-05-17T23:42:07Z","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":"Random sampling is a fundamental primitive in modern algorithms, statistics, and machine learning, used as a generic method to obtain a small yet \"representative\" subset of the data. In this work, we investigate the robustness of sampling against adaptive adversarial attacks in a streaming setting: An adversary sends a stream of elements from a universe $U$ to a sampling algorithm (e.g., Bernoulli sampling or reservoir sampling), with the goal of making the sample \"very unrepresentative\" of the underlying data stream. The adversary is fully adaptive in the sense that it knows the exact content","authors_text":"Eylon Yogev, Omri Ben-Eliezer","cross_cats":["cs.CG","cs.CR","cs.DB","cs.DC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2019-06-26T20:15:54Z","title":"The Adversarial Robustness of Sampling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.11327","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":"sha256:342d4c4f2334424d823487be08be2fc4a271ad7aa011789df9c23c23e612e00e","target":"record","created_at":"2026-05-17T23:42:07Z","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":"bbdf5ce0746d1cffb174fd09076a6a14c2a025d3135dfa7767e0794e8a89f7f8","cross_cats_sorted":["cs.CG","cs.CR","cs.DB","cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2019-06-26T20:15:54Z","title_canon_sha256":"873ccf74a7597060e5dff7c48dd5f8bd0dbe7389eafd7656f5f30eabe08600c7"},"schema_version":"1.0","source":{"id":"1906.11327","kind":"arxiv","version":1}},"canonical_sha256":"ef9e288219acc607a0f093c98d359be39a65fa64de482b7208724520131f2d2e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ef9e288219acc607a0f093c98d359be39a65fa64de482b7208724520131f2d2e","first_computed_at":"2026-05-17T23:42:07.510180Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:42:07.510180Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lGgvcFZAAK6LuTPcLFRxs66jtwM83A2mE0VLrmHEnJbiWJXSkYYKOB7DNRgdKla0SUdGpmsIkT3r6a9PYH1kAQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:42:07.510763Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.11327","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:342d4c4f2334424d823487be08be2fc4a271ad7aa011789df9c23c23e612e00e","sha256:db8ec689f48895a4c4b521b27cd5d123a0f10f1b6d075defcc1f4593c6194f82"],"state_sha256":"292b5341fb1b8b77da1a783767b366a9ce2ae9f10796520e24a2404cc28af1bf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HS2bj3E2sgAqAYLILIspLE7uaukpVNaFPcOH4Kzge2XTRkAQ97el8u7Tu0til0Uv1OmJmsO64636oQzMzC9vAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T04:39:06.528283Z","bundle_sha256":"1b24ddd2ddc2cbb32f9b23c27ef11a6821b6e3a7efa062510b7c9d404b2e9627"}}