{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:SIO7H4CUFPAK5HHMPXRUO5IB5A","short_pith_number":"pith:SIO7H4CU","canonical_record":{"source":{"id":"2201.01621","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2022-01-05T14:03:26Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"80a353bcdc6bb15ff60c9022fb8c5ba6fe104cb1e2b5972b2539f5ff4b6be60d","abstract_canon_sha256":"0a67f859a304bddb3cc7a1def5a58bc217abbb57e2674963f5525407de5c2788"},"schema_version":"1.0"},"canonical_sha256":"921df3f0542bc0ae9cec7de3477501e81f4f7e073eb78e529409354859457432","source":{"kind":"arxiv","id":"2201.01621","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2201.01621","created_at":"2026-07-05T03:46:15Z"},{"alias_kind":"arxiv_version","alias_value":"2201.01621v1","created_at":"2026-07-05T03:46:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.01621","created_at":"2026-07-05T03:46:15Z"},{"alias_kind":"pith_short_12","alias_value":"SIO7H4CUFPAK","created_at":"2026-07-05T03:46:15Z"},{"alias_kind":"pith_short_16","alias_value":"SIO7H4CUFPAK5HHM","created_at":"2026-07-05T03:46:15Z"},{"alias_kind":"pith_short_8","alias_value":"SIO7H4CU","created_at":"2026-07-05T03:46:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:SIO7H4CUFPAK5HHMPXRUO5IB5A","target":"record","payload":{"canonical_record":{"source":{"id":"2201.01621","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2022-01-05T14:03:26Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"80a353bcdc6bb15ff60c9022fb8c5ba6fe104cb1e2b5972b2539f5ff4b6be60d","abstract_canon_sha256":"0a67f859a304bddb3cc7a1def5a58bc217abbb57e2674963f5525407de5c2788"},"schema_version":"1.0"},"canonical_sha256":"921df3f0542bc0ae9cec7de3477501e81f4f7e073eb78e529409354859457432","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:46:15.101428Z","signature_b64":"87goa/xCcAs5b/lxweMzVVIJCnbRR4k7ne0/NolI6/34/MfVrJzxhj2Jp1+1UowWhmnEOH9m/nHu7BiOqARwAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"921df3f0542bc0ae9cec7de3477501e81f4f7e073eb78e529409354859457432","last_reissued_at":"2026-07-05T03:46:15.100933Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:46:15.100933Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2201.01621","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":"2026-07-05T03:46:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WLy1ltmrziRlskvB0bCpFZWFiIS6BU8SckH1tMyD+SXT0CrXQwMp1VyXxOcPCA47G8uAonTIoYTyY1GhMz2LCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T14:56:59.617713Z"},"content_sha256":"9c5b4b683331a45385e16f07cdff8a24f68974312dd18e44faa8178b8eaf0d19","schema_version":"1.0","event_id":"sha256:9c5b4b683331a45385e16f07cdff8a24f68974312dd18e44faa8178b8eaf0d19"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:SIO7H4CUFPAK5HHMPXRUO5IB5A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ROOM: Adversarial Machine Learning Attacks Under Real-Time Constraints","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CR","authors_text":"Amira Guesmi, Ihsen Alouani, Khaled N. Khasawneh, Nael Abu-Ghazaleh","submitted_at":"2022-01-05T14:03:26Z","abstract_excerpt":"Advances in deep learning have enabled a wide range of promising applications. However, these systems are vulnerable to Adversarial Machine Learning (AML) attacks; adversarially crafted perturbations to their inputs could cause them to misclassify. Several state-of-the-art adversarial attacks have demonstrated that they can reliably fool classifiers making these attacks a significant threat. Adversarial attack generation algorithms focus primarily on creating successful examples while controlling the noise magnitude and distribution to make detection more difficult. The underlying assumption o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.01621","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/2201.01621/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:46:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9bvzDzT7MZpInUIwdAPthUa47hqcNs7Eki9P83Fay4F47I7ez9Om2WevarJf6PLwNmNv9zaMEh3UXutGybq9BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T14:56:59.619592Z"},"content_sha256":"241a69eba36507a1341e53ec047fc065be02b116430a3ef84dca2fed43fea5d1","schema_version":"1.0","event_id":"sha256:241a69eba36507a1341e53ec047fc065be02b116430a3ef84dca2fed43fea5d1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SIO7H4CUFPAK5HHMPXRUO5IB5A/bundle.json","state_url":"https://pith.science/pith/SIO7H4CUFPAK5HHMPXRUO5IB5A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SIO7H4CUFPAK5HHMPXRUO5IB5A/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":"2026-08-14T14:56:59Z","links":{"resolver":"https://pith.science/pith/SIO7H4CUFPAK5HHMPXRUO5IB5A","bundle":"https://pith.science/pith/SIO7H4CUFPAK5HHMPXRUO5IB5A/bundle.json","state":"https://pith.science/pith/SIO7H4CUFPAK5HHMPXRUO5IB5A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SIO7H4CUFPAK5HHMPXRUO5IB5A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:SIO7H4CUFPAK5HHMPXRUO5IB5A","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":"0a67f859a304bddb3cc7a1def5a58bc217abbb57e2674963f5525407de5c2788","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2022-01-05T14:03:26Z","title_canon_sha256":"80a353bcdc6bb15ff60c9022fb8c5ba6fe104cb1e2b5972b2539f5ff4b6be60d"},"schema_version":"1.0","source":{"id":"2201.01621","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2201.01621","created_at":"2026-07-05T03:46:15Z"},{"alias_kind":"arxiv_version","alias_value":"2201.01621v1","created_at":"2026-07-05T03:46:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.01621","created_at":"2026-07-05T03:46:15Z"},{"alias_kind":"pith_short_12","alias_value":"SIO7H4CUFPAK","created_at":"2026-07-05T03:46:15Z"},{"alias_kind":"pith_short_16","alias_value":"SIO7H4CUFPAK5HHM","created_at":"2026-07-05T03:46:15Z"},{"alias_kind":"pith_short_8","alias_value":"SIO7H4CU","created_at":"2026-07-05T03:46:15Z"}],"graph_snapshots":[{"event_id":"sha256:241a69eba36507a1341e53ec047fc065be02b116430a3ef84dca2fed43fea5d1","target":"graph","created_at":"2026-07-05T03:46:15Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2201.01621/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Advances in deep learning have enabled a wide range of promising applications. However, these systems are vulnerable to Adversarial Machine Learning (AML) attacks; adversarially crafted perturbations to their inputs could cause them to misclassify. Several state-of-the-art adversarial attacks have demonstrated that they can reliably fool classifiers making these attacks a significant threat. Adversarial attack generation algorithms focus primarily on creating successful examples while controlling the noise magnitude and distribution to make detection more difficult. The underlying assumption o","authors_text":"Amira Guesmi, Ihsen Alouani, Khaled N. Khasawneh, Nael Abu-Ghazaleh","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2022-01-05T14:03:26Z","title":"ROOM: Adversarial Machine Learning Attacks Under Real-Time Constraints"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.01621","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":"sha256:9c5b4b683331a45385e16f07cdff8a24f68974312dd18e44faa8178b8eaf0d19","target":"record","created_at":"2026-07-05T03:46:15Z","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":"0a67f859a304bddb3cc7a1def5a58bc217abbb57e2674963f5525407de5c2788","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2022-01-05T14:03:26Z","title_canon_sha256":"80a353bcdc6bb15ff60c9022fb8c5ba6fe104cb1e2b5972b2539f5ff4b6be60d"},"schema_version":"1.0","source":{"id":"2201.01621","kind":"arxiv","version":1}},"canonical_sha256":"921df3f0542bc0ae9cec7de3477501e81f4f7e073eb78e529409354859457432","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"921df3f0542bc0ae9cec7de3477501e81f4f7e073eb78e529409354859457432","first_computed_at":"2026-07-05T03:46:15.100933Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:46:15.100933Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"87goa/xCcAs5b/lxweMzVVIJCnbRR4k7ne0/NolI6/34/MfVrJzxhj2Jp1+1UowWhmnEOH9m/nHu7BiOqARwAg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:46:15.101428Z","signed_message":"canonical_sha256_bytes"},"source_id":"2201.01621","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9c5b4b683331a45385e16f07cdff8a24f68974312dd18e44faa8178b8eaf0d19","sha256:241a69eba36507a1341e53ec047fc065be02b116430a3ef84dca2fed43fea5d1"],"state_sha256":"22d2af0d96c6c7e219fedd38577d2b7ba53c6e01337e3355e6890ead26437893"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0N2VLTz6kKPXz/fwCdE/0iQhwjBkFSCdTlSyeGnjYd6JMK2Lw4dwtZEipMlpJQYYF22ULEPep/PGH2OD7ldZAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T14:56:59.630312Z","bundle_sha256":"1711c38f5e5a28d1e0c0fe9f33eb63fa84485d740e9b6c8ebf9938bbc3b0922e"}}