{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:YGMOJ2WUFHGBVEQ2EWUY3ZXKQZ","short_pith_number":"pith:YGMOJ2WU","canonical_record":{"source":{"id":"2501.16638","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-28T02:20:34Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"1d214f8a5602b5818eef060a9901bfcf2788e6aabe541c968a47d62988ff8ab1","abstract_canon_sha256":"6d51e475359f340c08b076836ec1d4d235d7d156ba8f1355ce58f80a8da958c1"},"schema_version":"1.0"},"canonical_sha256":"c198e4ead429cc1a921a25a98de6ea8654ca6e4ab89ada211b9253b632dddbc8","source":{"kind":"arxiv","id":"2501.16638","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.16638","created_at":"2026-07-05T10:55:29Z"},{"alias_kind":"arxiv_version","alias_value":"2501.16638v1","created_at":"2026-07-05T10:55:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.16638","created_at":"2026-07-05T10:55:29Z"},{"alias_kind":"pith_short_12","alias_value":"YGMOJ2WUFHGB","created_at":"2026-07-05T10:55:29Z"},{"alias_kind":"pith_short_16","alias_value":"YGMOJ2WUFHGBVEQ2","created_at":"2026-07-05T10:55:29Z"},{"alias_kind":"pith_short_8","alias_value":"YGMOJ2WU","created_at":"2026-07-05T10:55:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:YGMOJ2WUFHGBVEQ2EWUY3ZXKQZ","target":"record","payload":{"canonical_record":{"source":{"id":"2501.16638","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-28T02:20:34Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"1d214f8a5602b5818eef060a9901bfcf2788e6aabe541c968a47d62988ff8ab1","abstract_canon_sha256":"6d51e475359f340c08b076836ec1d4d235d7d156ba8f1355ce58f80a8da958c1"},"schema_version":"1.0"},"canonical_sha256":"c198e4ead429cc1a921a25a98de6ea8654ca6e4ab89ada211b9253b632dddbc8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:55:29.817333Z","signature_b64":"XmIryKFt3mkzisZozw2xuB0erbJiJeVMUuLLqpkJ96RoFFtW8Coo49eQcLMzMDkJju9z/H6YnjSO85MGDaFtAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c198e4ead429cc1a921a25a98de6ea8654ca6e4ab89ada211b9253b632dddbc8","last_reissued_at":"2026-07-05T10:55:29.816824Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:55:29.816824Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.16638","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":"2026-07-05T10:55:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yhm2RymPfvSFP7lNKRWCPbpx1Uix3QrGKMgVzZjUeWD6Y21eLcQk81ibK7T77IsTVoiNYxViqFkMV/KBHpicBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T17:56:25.724738Z"},"content_sha256":"da7eebdf53ad4e232c627fe7a0ef6d006e3afc1c1e338541d9ea33ff62bdcc20","schema_version":"1.0","event_id":"sha256:da7eebdf53ad4e232c627fe7a0ef6d006e3afc1c1e338541d9ea33ff62bdcc20"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:YGMOJ2WUFHGBVEQ2EWUY3ZXKQZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Analysis of Zero Day Attack Detection Using MLP and XAI","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CR"],"primary_cat":"cs.LG","authors_text":"Ashim Dahal, Nick Rahimi, Prabin Bajgai","submitted_at":"2025-01-28T02:20:34Z","abstract_excerpt":"Any exploit taking advantage of zero-day is called a zero-day attack. Previous research and social media trends show a massive demand for research in zero-day attack detection. This paper analyzes Machine Learning (ML) and Deep Learning (DL) based approaches to create Intrusion Detection Systems (IDS) and scrutinizing them using Explainable AI (XAI) by training an explainer based on randomly sampled data from the testing set. The focus is on using the KDD99 dataset, which has the most research done among all the datasets for detecting zero-day attacks. The paper aims to synthesize the dataset "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.16638","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/2501.16638/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":"2026-07-05T10:55:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yd4Et888lTHsEYvlBjC3xDXm+RrVAdMtPOnfSe3UsWcOfD0hTqsdVpKqD4k2aZl0g8mzyIruMm054BwjZ4aJCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T17:56:25.725083Z"},"content_sha256":"35d60ec86348bc8ca9484acf94cf9f6b6d0b56ef2c43ba89880e74b3c55f0ea3","schema_version":"1.0","event_id":"sha256:35d60ec86348bc8ca9484acf94cf9f6b6d0b56ef2c43ba89880e74b3c55f0ea3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YGMOJ2WUFHGBVEQ2EWUY3ZXKQZ/bundle.json","state_url":"https://pith.science/pith/YGMOJ2WUFHGBVEQ2EWUY3ZXKQZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YGMOJ2WUFHGBVEQ2EWUY3ZXKQZ/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":"2026-08-19T17:56:25Z","links":{"resolver":"https://pith.science/pith/YGMOJ2WUFHGBVEQ2EWUY3ZXKQZ","bundle":"https://pith.science/pith/YGMOJ2WUFHGBVEQ2EWUY3ZXKQZ/bundle.json","state":"https://pith.science/pith/YGMOJ2WUFHGBVEQ2EWUY3ZXKQZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YGMOJ2WUFHGBVEQ2EWUY3ZXKQZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:YGMOJ2WUFHGBVEQ2EWUY3ZXKQZ","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":"6d51e475359f340c08b076836ec1d4d235d7d156ba8f1355ce58f80a8da958c1","cross_cats_sorted":["cs.CR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-28T02:20:34Z","title_canon_sha256":"1d214f8a5602b5818eef060a9901bfcf2788e6aabe541c968a47d62988ff8ab1"},"schema_version":"1.0","source":{"id":"2501.16638","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.16638","created_at":"2026-07-05T10:55:29Z"},{"alias_kind":"arxiv_version","alias_value":"2501.16638v1","created_at":"2026-07-05T10:55:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.16638","created_at":"2026-07-05T10:55:29Z"},{"alias_kind":"pith_short_12","alias_value":"YGMOJ2WUFHGB","created_at":"2026-07-05T10:55:29Z"},{"alias_kind":"pith_short_16","alias_value":"YGMOJ2WUFHGBVEQ2","created_at":"2026-07-05T10:55:29Z"},{"alias_kind":"pith_short_8","alias_value":"YGMOJ2WU","created_at":"2026-07-05T10:55:29Z"}],"graph_snapshots":[{"event_id":"sha256:35d60ec86348bc8ca9484acf94cf9f6b6d0b56ef2c43ba89880e74b3c55f0ea3","target":"graph","created_at":"2026-07-05T10:55:29Z","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/2501.16638/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Any exploit taking advantage of zero-day is called a zero-day attack. Previous research and social media trends show a massive demand for research in zero-day attack detection. This paper analyzes Machine Learning (ML) and Deep Learning (DL) based approaches to create Intrusion Detection Systems (IDS) and scrutinizing them using Explainable AI (XAI) by training an explainer based on randomly sampled data from the testing set. The focus is on using the KDD99 dataset, which has the most research done among all the datasets for detecting zero-day attacks. The paper aims to synthesize the dataset ","authors_text":"Ashim Dahal, Nick Rahimi, Prabin Bajgai","cross_cats":["cs.CR"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-28T02:20:34Z","title":"Analysis of Zero Day Attack Detection Using MLP and XAI"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.16638","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:da7eebdf53ad4e232c627fe7a0ef6d006e3afc1c1e338541d9ea33ff62bdcc20","target":"record","created_at":"2026-07-05T10:55:29Z","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":"6d51e475359f340c08b076836ec1d4d235d7d156ba8f1355ce58f80a8da958c1","cross_cats_sorted":["cs.CR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-28T02:20:34Z","title_canon_sha256":"1d214f8a5602b5818eef060a9901bfcf2788e6aabe541c968a47d62988ff8ab1"},"schema_version":"1.0","source":{"id":"2501.16638","kind":"arxiv","version":1}},"canonical_sha256":"c198e4ead429cc1a921a25a98de6ea8654ca6e4ab89ada211b9253b632dddbc8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c198e4ead429cc1a921a25a98de6ea8654ca6e4ab89ada211b9253b632dddbc8","first_computed_at":"2026-07-05T10:55:29.816824Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:55:29.816824Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XmIryKFt3mkzisZozw2xuB0erbJiJeVMUuLLqpkJ96RoFFtW8Coo49eQcLMzMDkJju9z/H6YnjSO85MGDaFtAw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:55:29.817333Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.16638","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:da7eebdf53ad4e232c627fe7a0ef6d006e3afc1c1e338541d9ea33ff62bdcc20","sha256:35d60ec86348bc8ca9484acf94cf9f6b6d0b56ef2c43ba89880e74b3c55f0ea3"],"state_sha256":"ebc8ad753075c9a723718da7417441d7f2c0f2046642485e07ecd7d14d05777f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"73WBB1R5n8DVMB9qoG0QWyE42xFvb09Pum2+ntTOf2ujN4AOQ/UPcafGFdOXEteH9fbpjvTWxXdo9mHywq+dAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T17:56:25.728516Z","bundle_sha256":"ba2a553ee4d2d8767aa7c486a28f81aa7b5ddfee3b6c0a236c08da29096454c6"}}