{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:T7TVTD72VIJ2GDP253MFRGOJSH","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":"4d49ccf819374a2c53853e6b9c4ec65196281d4ecfb13d3879187b5974bc30ee","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2023-05-18T15:32:32Z","title_canon_sha256":"6b52d8a9294eabb63c2522f8a92fd6c44f6bdb91cd1dc77a140c61f564938f4f"},"schema_version":"1.0","source":{"id":"2305.11039","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.11039","created_at":"2026-07-05T06:11:29Z"},{"alias_kind":"arxiv_version","alias_value":"2305.11039v1","created_at":"2026-07-05T06:11:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.11039","created_at":"2026-07-05T06:11:29Z"},{"alias_kind":"pith_short_12","alias_value":"T7TVTD72VIJ2","created_at":"2026-07-05T06:11:29Z"},{"alias_kind":"pith_short_16","alias_value":"T7TVTD72VIJ2GDP2","created_at":"2026-07-05T06:11:29Z"},{"alias_kind":"pith_short_8","alias_value":"T7TVTD72","created_at":"2026-07-05T06:11:29Z"}],"graph_snapshots":[{"event_id":"sha256:b8f63bc1448ea4a7cacb087387aff0e769b791078d414c15e88c75952c584f79","target":"graph","created_at":"2026-07-05T06:11:29Z","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/2305.11039/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advancements in artificial intelligence (AI) and machine learning (ML) algorithms, coupled with the availability of faster computing infrastructure, have enhanced the security posture of cybersecurity operations centers (defenders) through the development of ML-aided network intrusion detection systems (NIDS). Concurrently, the abilities of adversaries to evade security have also increased with the support of AI/ML models. Therefore, defenders need to proactively prepare for evasion attacks that exploit the detection mechanisms of NIDS. Recent studies have found that the perturbation of","authors_text":"Ankit Shah, Diwas Paudel, Jalal Ghadermazi, Nathaniel D. Bastian, Soumyadeep Hore, Tapas K. Das","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2023-05-18T15:32:32Z","title":"Deep PackGen: A Deep Reinforcement Learning Framework for Adversarial Network Packet Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.11039","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:a0a74e4b7997b3d768ec75aac515e34e6657997f65ec05f7957426f6e614d0e0","target":"record","created_at":"2026-07-05T06:11:29Z","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":"4d49ccf819374a2c53853e6b9c4ec65196281d4ecfb13d3879187b5974bc30ee","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2023-05-18T15:32:32Z","title_canon_sha256":"6b52d8a9294eabb63c2522f8a92fd6c44f6bdb91cd1dc77a140c61f564938f4f"},"schema_version":"1.0","source":{"id":"2305.11039","kind":"arxiv","version":1}},"canonical_sha256":"9fe7598ffaaa13a30dfaeed85899c991cf4d5a4d04e1fc4825b89ee96a4e0dbe","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9fe7598ffaaa13a30dfaeed85899c991cf4d5a4d04e1fc4825b89ee96a4e0dbe","first_computed_at":"2026-07-05T06:11:29.622244Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:11:29.622244Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yQv70omaduIKn+imL5VdHbdZ3pGuiNAQXyZmQitgmxU82lv5zsfNS60E+2+Gq7wJNYB45e+PmgC3don+5HvJBw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:11:29.622756Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.11039","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a0a74e4b7997b3d768ec75aac515e34e6657997f65ec05f7957426f6e614d0e0","sha256:b8f63bc1448ea4a7cacb087387aff0e769b791078d414c15e88c75952c584f79"],"state_sha256":"f454a4721c307df5411c6f6e2ce0145f14e0e64d5075b78ac1390a084fb2261c"}