{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:S2I4IIIM4LMSKEBKNDHUJMLHBK","short_pith_number":"pith:S2I4IIIM","canonical_record":{"source":{"id":"2101.02559","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2021-01-04T20:06:56Z","cross_cats_sorted":["cs.AI","cs.AR","cs.LG","cs.SY","eess.SY"],"title_canon_sha256":"df9b0de7d7b931569c3c6ca45c61d75aef005a0ad0e92439f37df1e6a3eb6864","abstract_canon_sha256":"8ed0a667f951494704e5d9965f17dcf8b039b43c86fd786d074e91ade239240e"},"schema_version":"1.0"},"canonical_sha256":"9691c4210ce2d925102a68cf44b1670a9a05da6eeacaa6a8d3d481e45d2b0994","source":{"kind":"arxiv","id":"2101.02559","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2101.02559","created_at":"2026-07-05T02:05:15Z"},{"alias_kind":"arxiv_version","alias_value":"2101.02559v1","created_at":"2026-07-05T02:05:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2101.02559","created_at":"2026-07-05T02:05:15Z"},{"alias_kind":"pith_short_12","alias_value":"S2I4IIIM4LMS","created_at":"2026-07-05T02:05:15Z"},{"alias_kind":"pith_short_16","alias_value":"S2I4IIIM4LMSKEBK","created_at":"2026-07-05T02:05:15Z"},{"alias_kind":"pith_short_8","alias_value":"S2I4IIIM","created_at":"2026-07-05T02:05:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:S2I4IIIM4LMSKEBKNDHUJMLHBK","target":"record","payload":{"canonical_record":{"source":{"id":"2101.02559","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2021-01-04T20:06:56Z","cross_cats_sorted":["cs.AI","cs.AR","cs.LG","cs.SY","eess.SY"],"title_canon_sha256":"df9b0de7d7b931569c3c6ca45c61d75aef005a0ad0e92439f37df1e6a3eb6864","abstract_canon_sha256":"8ed0a667f951494704e5d9965f17dcf8b039b43c86fd786d074e91ade239240e"},"schema_version":"1.0"},"canonical_sha256":"9691c4210ce2d925102a68cf44b1670a9a05da6eeacaa6a8d3d481e45d2b0994","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:05:15.051202Z","signature_b64":"W7Wt5ZTFWkFEjoTL3yFjTsp9j7A6po4MA91kC5dwdUft1HqLLomAaCWR8m9mkbdnEh2u0jDY5I4qvANnvTlfCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9691c4210ce2d925102a68cf44b1670a9a05da6eeacaa6a8d3d481e45d2b0994","last_reissued_at":"2026-07-05T02:05:15.050786Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:05:15.050786Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2101.02559","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":"2026-07-05T02:05:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"o/52dNWBKUbbG1uGGmKnrpzT5JQtj4JHceI2kIP/aldYgTbRZZBYQRSWd8Wsfo54ZFSVGLKB7NOM4QzLZ57dAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T00:53:08.565380Z"},"content_sha256":"60ab29c9ff3c8bb1be022d7ed0c6a995ec728322bac3429a830f01304fde29d8","schema_version":"1.0","event_id":"sha256:60ab29c9ff3c8bb1be022d7ed0c6a995ec728322bac3429a830f01304fde29d8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:S2I4IIIM4LMSKEBKNDHUJMLHBK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.AR","cs.LG","cs.SY","eess.SY"],"primary_cat":"cs.CR","authors_text":"Christos Kyrkou, Jungwook Choi, Lois Orosa, Mahum Naseer, Muhammad Shafique, Onur Mutlu, Theocharis Theocharides","submitted_at":"2021-01-04T20:06:56Z","abstract_excerpt":"Machine Learning (ML) techniques have been rapidly adopted by smart Cyber-Physical Systems (CPS) and Internet-of-Things (IoT) due to their powerful decision-making capabilities. However, they are vulnerable to various security and reliability threats, at both hardware and software levels, that compromise their accuracy. These threats get aggravated in emerging edge ML devices that have stringent constraints in terms of resources (e.g., compute, memory, power/energy), and that therefore cannot employ costly security and reliability measures. Security, reliability, and vulnerability mitigation t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2101.02559","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/2101.02559/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":"2026-07-05T02:05:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rezz2E/env1pxBkRA3Eydk7yq1+DHHk59gPf7saqcuapeLbNEZPQcVhm1RTMoixjef3LpmDoYK2i3Af1OK3kAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T00:53:08.566313Z"},"content_sha256":"2b76431b446c06aa3dc5f376d18ee09bf90a1a958d6ef26fcecae909126b52d4","schema_version":"1.0","event_id":"sha256:2b76431b446c06aa3dc5f376d18ee09bf90a1a958d6ef26fcecae909126b52d4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/S2I4IIIM4LMSKEBKNDHUJMLHBK/bundle.json","state_url":"https://pith.science/pith/S2I4IIIM4LMSKEBKNDHUJMLHBK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/S2I4IIIM4LMSKEBKNDHUJMLHBK/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":"2026-08-07T00:53:08Z","links":{"resolver":"https://pith.science/pith/S2I4IIIM4LMSKEBKNDHUJMLHBK","bundle":"https://pith.science/pith/S2I4IIIM4LMSKEBKNDHUJMLHBK/bundle.json","state":"https://pith.science/pith/S2I4IIIM4LMSKEBKNDHUJMLHBK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/S2I4IIIM4LMSKEBKNDHUJMLHBK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:S2I4IIIM4LMSKEBKNDHUJMLHBK","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":"8ed0a667f951494704e5d9965f17dcf8b039b43c86fd786d074e91ade239240e","cross_cats_sorted":["cs.AI","cs.AR","cs.LG","cs.SY","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2021-01-04T20:06:56Z","title_canon_sha256":"df9b0de7d7b931569c3c6ca45c61d75aef005a0ad0e92439f37df1e6a3eb6864"},"schema_version":"1.0","source":{"id":"2101.02559","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2101.02559","created_at":"2026-07-05T02:05:15Z"},{"alias_kind":"arxiv_version","alias_value":"2101.02559v1","created_at":"2026-07-05T02:05:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2101.02559","created_at":"2026-07-05T02:05:15Z"},{"alias_kind":"pith_short_12","alias_value":"S2I4IIIM4LMS","created_at":"2026-07-05T02:05:15Z"},{"alias_kind":"pith_short_16","alias_value":"S2I4IIIM4LMSKEBK","created_at":"2026-07-05T02:05:15Z"},{"alias_kind":"pith_short_8","alias_value":"S2I4IIIM","created_at":"2026-07-05T02:05:15Z"}],"graph_snapshots":[{"event_id":"sha256:2b76431b446c06aa3dc5f376d18ee09bf90a1a958d6ef26fcecae909126b52d4","target":"graph","created_at":"2026-07-05T02:05:15Z","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/2101.02559/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Machine Learning (ML) techniques have been rapidly adopted by smart Cyber-Physical Systems (CPS) and Internet-of-Things (IoT) due to their powerful decision-making capabilities. However, they are vulnerable to various security and reliability threats, at both hardware and software levels, that compromise their accuracy. These threats get aggravated in emerging edge ML devices that have stringent constraints in terms of resources (e.g., compute, memory, power/energy), and that therefore cannot employ costly security and reliability measures. Security, reliability, and vulnerability mitigation t","authors_text":"Christos Kyrkou, Jungwook Choi, Lois Orosa, Mahum Naseer, Muhammad Shafique, Onur Mutlu, Theocharis Theocharides","cross_cats":["cs.AI","cs.AR","cs.LG","cs.SY","eess.SY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2021-01-04T20:06:56Z","title":"Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2101.02559","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":"sha256:60ab29c9ff3c8bb1be022d7ed0c6a995ec728322bac3429a830f01304fde29d8","target":"record","created_at":"2026-07-05T02:05:15Z","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":"8ed0a667f951494704e5d9965f17dcf8b039b43c86fd786d074e91ade239240e","cross_cats_sorted":["cs.AI","cs.AR","cs.LG","cs.SY","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2021-01-04T20:06:56Z","title_canon_sha256":"df9b0de7d7b931569c3c6ca45c61d75aef005a0ad0e92439f37df1e6a3eb6864"},"schema_version":"1.0","source":{"id":"2101.02559","kind":"arxiv","version":1}},"canonical_sha256":"9691c4210ce2d925102a68cf44b1670a9a05da6eeacaa6a8d3d481e45d2b0994","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9691c4210ce2d925102a68cf44b1670a9a05da6eeacaa6a8d3d481e45d2b0994","first_computed_at":"2026-07-05T02:05:15.050786Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:05:15.050786Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"W7Wt5ZTFWkFEjoTL3yFjTsp9j7A6po4MA91kC5dwdUft1HqLLomAaCWR8m9mkbdnEh2u0jDY5I4qvANnvTlfCw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:05:15.051202Z","signed_message":"canonical_sha256_bytes"},"source_id":"2101.02559","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:60ab29c9ff3c8bb1be022d7ed0c6a995ec728322bac3429a830f01304fde29d8","sha256:2b76431b446c06aa3dc5f376d18ee09bf90a1a958d6ef26fcecae909126b52d4"],"state_sha256":"ba1473e5a8ec056807248e968b65ccab5e01ffda8546ecab23093eff23249dde"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GxyQ4kWtQiNRXC+HFyc7W9r95LDV+YDACdMicB4ff2x86CZCRxY0FImzIZ3PAJJL6kszVyUD3GI4ORWbTRCfDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T00:53:08.572942Z","bundle_sha256":"09cbe1fecf6cbcdcb299f0017a7b2ac42f152bfe72afa595d1156e70e75474ca"}}