{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:RKACRBSRZ4MW7H2XXSGYUEC7NR","short_pith_number":"pith:RKACRBSR","canonical_record":{"source":{"id":"2505.11532","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-05-14T02:05:34Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"a42a67c0662238369e9916d1e9fa2f1174b7b238725ad0a6ba230b6ccec339bf","abstract_canon_sha256":"545396f63bb2e96fa265b455b58c5f728b22039712815d676c9db70d71d4c4f6"},"schema_version":"1.0"},"canonical_sha256":"8a80288651cf196f9f57bc8d8a105f6c449d4f1f4ddecd089964e635fae45cbf","source":{"kind":"arxiv","id":"2505.11532","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.11532","created_at":"2026-07-05T11:08:20Z"},{"alias_kind":"arxiv_version","alias_value":"2505.11532v2","created_at":"2026-07-05T11:08:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.11532","created_at":"2026-07-05T11:08:20Z"},{"alias_kind":"pith_short_12","alias_value":"RKACRBSRZ4MW","created_at":"2026-07-05T11:08:20Z"},{"alias_kind":"pith_short_16","alias_value":"RKACRBSRZ4MW7H2X","created_at":"2026-07-05T11:08:20Z"},{"alias_kind":"pith_short_8","alias_value":"RKACRBSR","created_at":"2026-07-05T11:08:20Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:RKACRBSRZ4MW7H2XXSGYUEC7NR","target":"record","payload":{"canonical_record":{"source":{"id":"2505.11532","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-05-14T02:05:34Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"a42a67c0662238369e9916d1e9fa2f1174b7b238725ad0a6ba230b6ccec339bf","abstract_canon_sha256":"545396f63bb2e96fa265b455b58c5f728b22039712815d676c9db70d71d4c4f6"},"schema_version":"1.0"},"canonical_sha256":"8a80288651cf196f9f57bc8d8a105f6c449d4f1f4ddecd089964e635fae45cbf","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:08:20.681932Z","signature_b64":"0EIYcrq9p/+Z+TbwQvMFz/oahSHXbecBj/ee9nb8dIK56osFh95mbVk5u5NQ3BRRSngOrUnm2XLLDwifoVd6DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8a80288651cf196f9f57bc8d8a105f6c449d4f1f4ddecd089964e635fae45cbf","last_reissued_at":"2026-07-05T11:08:20.681435Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:08:20.681435Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.11532","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:08:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P/RVm9V2aw9zP9mVnZGb6uWsmmMFI5vwunWNi3bgIyv2+jU9p6m5ms3hEcy1G7eOxf46I5WyqaWRhAxuWwHIDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T17:25:49.254885Z"},"content_sha256":"1426d424d3edc680502fa27890427a74e01cec0c2dd51b09b60c21ba269f73f5","schema_version":"1.0","event_id":"sha256:1426d424d3edc680502fa27890427a74e01cec0c2dd51b09b60c21ba269f73f5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:RKACRBSRZ4MW7H2XXSGYUEC7NR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Revisiting Adversarial Perception Attacks and Defense Methods on Autonomous Driving Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR"],"primary_cat":"cs.RO","authors_text":"Cheng Chen, Nafis S Munir, Xiangwei Zhou, Xugui Zhou, Yuhong Wang","submitted_at":"2025-05-14T02:05:34Z","abstract_excerpt":"Autonomous driving systems (ADS) increasingly rely on deep learning-based perception models, which remain vulnerable to adversarial attacks. In this paper, we revisit adversarial attacks and defense methods, focusing on road sign recognition and lead object detection and prediction (e.g., relative distance). Using a Level-2 production ADS, OpenPilot by Comma$.$ai, and the widely adopted YOLO model, we systematically examine the impact of adversarial perturbations and assess defense techniques, including adversarial training, image processing, contrastive learning, and diffusion models. Our exp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.11532","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/2505.11532/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":"2026-07-05T11:08:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MnitcEyLNRn6wahTbMuVCiQIOFC5unPvTb3E7eglCjHE6FAX4upBfsQCrS46B20k9IGsRejcUkXgAU7twU1NDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T17:25:49.255810Z"},"content_sha256":"803285cdd08f2498fd289408d285a96eadf4b2471e0890825c8a329f33714974","schema_version":"1.0","event_id":"sha256:803285cdd08f2498fd289408d285a96eadf4b2471e0890825c8a329f33714974"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RKACRBSRZ4MW7H2XXSGYUEC7NR/bundle.json","state_url":"https://pith.science/pith/RKACRBSRZ4MW7H2XXSGYUEC7NR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RKACRBSRZ4MW7H2XXSGYUEC7NR/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":"2026-08-14T17:25:49Z","links":{"resolver":"https://pith.science/pith/RKACRBSRZ4MW7H2XXSGYUEC7NR","bundle":"https://pith.science/pith/RKACRBSRZ4MW7H2XXSGYUEC7NR/bundle.json","state":"https://pith.science/pith/RKACRBSRZ4MW7H2XXSGYUEC7NR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RKACRBSRZ4MW7H2XXSGYUEC7NR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:RKACRBSRZ4MW7H2XXSGYUEC7NR","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":"545396f63bb2e96fa265b455b58c5f728b22039712815d676c9db70d71d4c4f6","cross_cats_sorted":["cs.CR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-05-14T02:05:34Z","title_canon_sha256":"a42a67c0662238369e9916d1e9fa2f1174b7b238725ad0a6ba230b6ccec339bf"},"schema_version":"1.0","source":{"id":"2505.11532","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.11532","created_at":"2026-07-05T11:08:20Z"},{"alias_kind":"arxiv_version","alias_value":"2505.11532v2","created_at":"2026-07-05T11:08:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.11532","created_at":"2026-07-05T11:08:20Z"},{"alias_kind":"pith_short_12","alias_value":"RKACRBSRZ4MW","created_at":"2026-07-05T11:08:20Z"},{"alias_kind":"pith_short_16","alias_value":"RKACRBSRZ4MW7H2X","created_at":"2026-07-05T11:08:20Z"},{"alias_kind":"pith_short_8","alias_value":"RKACRBSR","created_at":"2026-07-05T11:08:20Z"}],"graph_snapshots":[{"event_id":"sha256:803285cdd08f2498fd289408d285a96eadf4b2471e0890825c8a329f33714974","target":"graph","created_at":"2026-07-05T11:08:20Z","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/2505.11532/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Autonomous driving systems (ADS) increasingly rely on deep learning-based perception models, which remain vulnerable to adversarial attacks. In this paper, we revisit adversarial attacks and defense methods, focusing on road sign recognition and lead object detection and prediction (e.g., relative distance). Using a Level-2 production ADS, OpenPilot by Comma$.$ai, and the widely adopted YOLO model, we systematically examine the impact of adversarial perturbations and assess defense techniques, including adversarial training, image processing, contrastive learning, and diffusion models. Our exp","authors_text":"Cheng Chen, Nafis S Munir, Xiangwei Zhou, Xugui Zhou, Yuhong Wang","cross_cats":["cs.CR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-05-14T02:05:34Z","title":"Revisiting Adversarial Perception Attacks and Defense Methods on Autonomous Driving Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.11532","kind":"arxiv","version":2},"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":"sha256:1426d424d3edc680502fa27890427a74e01cec0c2dd51b09b60c21ba269f73f5","target":"record","created_at":"2026-07-05T11:08:20Z","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":"545396f63bb2e96fa265b455b58c5f728b22039712815d676c9db70d71d4c4f6","cross_cats_sorted":["cs.CR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-05-14T02:05:34Z","title_canon_sha256":"a42a67c0662238369e9916d1e9fa2f1174b7b238725ad0a6ba230b6ccec339bf"},"schema_version":"1.0","source":{"id":"2505.11532","kind":"arxiv","version":2}},"canonical_sha256":"8a80288651cf196f9f57bc8d8a105f6c449d4f1f4ddecd089964e635fae45cbf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8a80288651cf196f9f57bc8d8a105f6c449d4f1f4ddecd089964e635fae45cbf","first_computed_at":"2026-07-05T11:08:20.681435Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:08:20.681435Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0EIYcrq9p/+Z+TbwQvMFz/oahSHXbecBj/ee9nb8dIK56osFh95mbVk5u5NQ3BRRSngOrUnm2XLLDwifoVd6DQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:08:20.681932Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.11532","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1426d424d3edc680502fa27890427a74e01cec0c2dd51b09b60c21ba269f73f5","sha256:803285cdd08f2498fd289408d285a96eadf4b2471e0890825c8a329f33714974"],"state_sha256":"bafe6cd8c4f2df479fa17120e5476883c8e4d17238d6af419b5a0e7ac03e1d26"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"K7QQyPv7S2LX7TVYptjlk4876f3X5mCPoaKg2DqhWrwud41pHxzBuTjsLlZpmkZv3P23eHtUjqkt4VG7xhoFCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T17:25:49.269388Z","bundle_sha256":"e1efeb803d323c43b581df9d4de58a095a82297c5a75bf1a41e5b146631a8c88"}}