{"as_of":"2026-08-08T01:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b6d0bbea11d3a87b4e79f58c2c270ead24db79f74f0ebe5cf2d5f6c4955d387e","coverage":[{"denominator":30,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":30,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T04:26:13.203923Z","state":"measured"},{"denominator":30,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":30,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2602.13271/citation-record","integrity":"/paper/2602.13271/integrity","json":"/paper/2602.13271/citation-record.json","paper":"/paper/2602.13271"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:10.839151Z","title":"HDLNIDS: hybrid deep- learning-based network intrusion detection system,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:10.839151Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:2827fda25127773bbea94c72272ad2204b68e809a117b363273e54e440c553cf","observation_id":"26e0f655-8517-4e42-ab16-58af53a758e0","resolution":{"observed_at":"2026-08-03T04:26:10.839151Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:10.912532Z","title":"A novel two-stage deep learning model for network intrusion detection: LSTM- AE,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:10.912532Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:9a1f1c51e2ea29a9b4a4bfb788a95e2f1e87db6cc9451a23b307a7e7a2044c4a","observation_id":"10797bcf-12b2-4683-8c5c-177e78a69296","resolution":{"observed_at":"2026-08-03T04:26:10.912532Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:11.005228Z","title":"A novel deep learning-based intrusion detection system for IOT networks,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:11.005228Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:dd10f9f53258a6f7b0f04a6afc549948ef77936b0ca7a9379fd31a30ff1d0ccc","observation_id":"a818219d-601f-40e8-ace0-9ae2cb23d459","resolution":{"observed_at":"2026-08-03T04:26:11.005228Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:11.095831Z","title":"DCNNBiLSTM: An efficient hybrid deep learning-based intrusion detection system,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:11.095831Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:0eb5e8ab0236e4983cc39008daac0bd44eca9b461d071ce875a184cd2bfa5500","observation_id":"2aabff16-aa6d-435a-a213-bcf3a52baafc","resolution":{"observed_at":"2026-08-03T04:26:11.095831Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:11.166030Z","title":"A deep learning technique for intrusion detection system using a recurrent neural networks based framework,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:11.166030Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:50fc826bd8d6e6e0ec8ee2e80a99ea28cae5b19b68457e19a223c945dd3ef729","observation_id":"675324e4-f497-49de-9360-2ed530b913eb","resolution":{"observed_at":"2026-08-03T04:26:11.166030Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:11.257199Z","title":"NIDS-CNNLSTM: Network intrusion detection classification model based on deep learning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:11.257199Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:741a54b72124910dde29add9bdd3d2fe06e6e4fd1af0b9ec7cf5c63e9803f103","observation_id":"e49eb32f-d1c7-415c-9f41-ca893e8fce5f","resolution":{"observed_at":"2026-08-03T04:26:11.257199Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:11.339464Z","title":"Snort: Lightweight intrusion detection for networks.,","venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:11.339464Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:c1ebd09f5a59b7a336ae74960e629933f36f54277de5475d6d77ac8c8979b172","observation_id":"37fd3083-178a-4242-af76-4b469e06262b","resolution":{"observed_at":"2026-08-03T04:26:11.339464Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:11.443177Z","title":"Design and implementation of a lightweight intrusion detection and prevention system,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:11.443177Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:1ef5401e1e018bd1de1ada660566959a3f7d1c4d37cab0d3a7e61234ade67c68","observation_id":"6db8d716-e57e-441e-9e31-eba2d2019883","resolution":{"observed_at":"2026-08-03T04:26:11.443177Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:11.518761Z","title":"Intrusion detection framework for internet of things with rule induction for model explana- tion,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:11.518761Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:70a71b44eb3f4800287b9e3c34bbeb19502a87f47051eef09ac3de1b0dc02f45","observation_id":"e89a031a-bfcb-47a5-ac16-8674e527a9ba","resolution":{"observed_at":"2026-08-03T04:26:11.518761Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:11.591960Z","title":"An efficient intrusion detection system based on hypergraph-genetic algorithm for parameter optimization and feature selection in support vector machine,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:11.591960Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:f2ba2f001baefd1e0fafcbb2a4402fd832a807cd13ea0afa1ad9db50714fbf42","observation_id":"69dc584d-d1f1-4d19-afba-516a892c8b2d","resolution":{"observed_at":"2026-08-03T04:26:11.591960Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:11.662604Z","title":"A lightweight framework to secure iot devices with limited resources in cloud environments,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:11.662604Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:5e65f4ef7a3b5cd2fc489f16bcafd72d1045af5a2c98b8ff75997489524e5851","observation_id":"9c1f52c1-ea8e-41bf-af52-825255919a58","resolution":{"observed_at":"2026-08-03T04:26:11.662604Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:11.762881Z","title":"Erbm: A machine learning-driven rule-based model for intrusion detection in iot environments.,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:11.762881Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:389ccdd20846596711f9487930fcfd1bea380c4422f197c97159e24736513586","observation_id":"90b8d665-652f-4007-8139-7f31ebf80830","resolution":{"observed_at":"2026-08-03T04:26:11.762881Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:11.875477Z","title":"Gradient-based learning applied to document recognition,","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:11.875477Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:4863d8e867f20162e515862cca0186324cfa95b295439a1f68517a035635ddd3","observation_id":"daa27c70-bd64-4b7a-adc4-0a3dcf4abf74","resolution":{"observed_at":"2026-08-03T04:26:11.875477Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:11.956190Z","title":"Long short-term memory,","venue":null,"work_id":null,"year":1997},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:11.956190Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:0d586666fea3d7c11311c56491bd34289e1f81608105f3f0482ac5409a7e594c","observation_id":"de9729e3-c86e-483b-92f9-4e6fd6672caa","resolution":{"observed_at":"2026-08-03T04:26:11.956190Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:12.013322Z","title":"Long-term traffic flow forecasting using a hybrid CNN-BiLSTM model,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:12.013322Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:817f312f22b6c10242a80eb31d8b23f91754b1d484844bfe142fd69574d25ad9","observation_id":"6f987243-1c57-4199-a42d-9a53cb17345f","resolution":{"observed_at":"2026-08-03T04:26:12.013322Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:12.113744Z","title":"An overview of XAI Algorithms,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:12.113744Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:529e3eead210e018d888f7096ad3b5886c799149d4bb2da39c9f4557d3af76a9","observation_id":"58ccece1-bc00-4d2a-bfc8-24a246afb300","resolution":{"observed_at":"2026-08-03T04:26:12.113744Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:12.224652Z","title":"A detailed analysis on NSL-KDD dataset using various machine learning techniques for intrusion detection,","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:12.224652Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:3ffeea19c76601cbc4f862f0ce58bd6d221f5b45ab02224ce6059a08446cbb78","observation_id":"bdb34be2-83eb-4f5e-98f3-3bf4fa6fb23a","resolution":{"observed_at":"2026-08-03T04:26:12.224652Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:12.285905Z","title":"A detailed analysis of the KDD CUP 99 data set,","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:12.285905Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:29417d0869ef99544a1579bc008ced4c4ddcf52aceb69b78bd4d651a8086700f","observation_id":"f6b1fa59-3387-4d1d-9b49-1c2c9b704f5e","resolution":{"observed_at":"2026-08-03T04:26:12.285905Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:12.362160Z","title":"An improved long short term memory network for intrusion detection,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:12.362160Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:8a6f21b2f1668fc468ce4072b671e959958f96815cfbd33575ac27fb4b0854eb","observation_id":"cb7b87a8-6f18-4f8c-9b85-19fbb3bfbfea","resolution":{"observed_at":"2026-08-03T04:26:12.362160Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:12.440965Z","title":"Theoretical analysis of an alphabetic confusion matrix,","venue":null,"work_id":null,"year":1971},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:12.440965Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:8ef498af62cd08cc3c4498fed85bf9bcf37d2ecf554632d1158c07aef972fe7d","observation_id":"76a1e402-bc03-4b9e-82a6-6d744c115c98","resolution":{"observed_at":"2026-08-03T04:26:12.440965Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:12.525625Z","title":"A new multi-classification task accuracy evaluation method based on confusion matrix,","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:12.525625Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:d4c4bf054e739d10a14f5dea7db9f2a0fd85fa76cd095bc0a9320dd6a6f3632d","observation_id":"3361083c-3c52-4550-98ef-1a416f310f0a","resolution":{"observed_at":"2026-08-03T04:26:12.525625Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:12.615724Z","title":"MLCM: Multi-label confusion matrix,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:12.615724Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:8085270e4f761b5deca1c23f18bfcfae97b8c3e65b426264b1e0499c14afb41c","observation_id":"c557e52a-e826-49b1-a62f-474ce246ac0d","resolution":{"observed_at":"2026-08-03T04:26:12.615724Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:12.702724Z","title":"Evaluating deep learning models for network intrusion detection: A comparative analysis,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:12.702724Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:9b6e74a03924f6c5253317d90323ec1de8a36324b2b89cfa150502b2ba756b7f","observation_id":"c2709138-363b-4834-aea5-60c4430af345","resolution":{"observed_at":"2026-08-03T04:26:12.702724Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:12.775870Z","title":"The Mini-IPIP6: Validation and extension of a short measure of the Big-Six factors of personality in New Zealand.,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:12.775870Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:57456e41c7a18709fae37075de9bc9d9895341ce5951e2c3f4f4dfbae4916d8f","observation_id":"7a026ba6-12d5-4160-b0a0-f4cba5342e92","resolution":{"observed_at":"2026-08-03T04:26:12.775870Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:12.826361Z","title":"Effect of confidence and explanation on accuracy and trust calibration in ai-assisted decision mak- ing,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:12.826361Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:6eb92cc0efe798d18c9ae6b7dce441101548e78fb8f1161ed7205bdcbfbb85d2","observation_id":"c5c5543b-1dc7-4b28-bad4-39e760abfc0a","resolution":{"observed_at":"2026-08-03T04:26:12.826361Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:12.913500Z","title":"Monitoring oral health remotely: ethical considerations when using ai among vulnerable populations,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:12.913500Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:22eb9feb7670ee5bd44777e25a290df9f0c213431e2d2daf9e2e4123f33fcc84","observation_id":"4bdef399-1a37-4f3f-8729-f72e6cc8a537","resolution":{"observed_at":"2026-08-03T04:26:12.913500Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:13.000175Z","title":"Theoretical considerations and development of a question- naire to measure trust in automation,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:13.000175Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:eaaa2aac396f0ce89a0c3f478429c62c53c97166bfee5814e2c05b6411cc1409","observation_id":"bb4f55d2-0231-46ca-8d31-92d98a8c4f90","resolution":{"observed_at":"2026-08-03T04:26:13.000175Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:13.083870Z","title":"Sus-a quick and dirty usability scale,","venue":null,"work_id":null,"year":1996},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:13.083870Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:ee98eac8d199dc521795187fdf2cddca9c539b2a08ce6a6e2795122ba083285b","observation_id":"5c5fbd28-bc22-458d-920a-45434c601b67","resolution":{"observed_at":"2026-08-03T04:26:13.083870Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.07882","last_updated":"2025-06-09T15:53:30Z","snapshot_observed_at":"2026-08-07T05:20:47.530572Z","submitted_at":"2025-06-09T15:53:30Z","title":"Evaluating explainable AI for deep learning-based network intrusion detection system alert classification","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.07882","snapshot_observed_at":"2026-08-03T04:26:13.161162Z","title":"Evaluating explain- able ai for deep learning-based network intrusion detection system alert classification,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:13.161162Z"},"links":{"cited_paper":"/paper/2506.07882","citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:7fce77ec21287492a3417e8913748ea67900730d37c76546ecb84e39d13f4e51","observation_id":"37dc099e-fcd2-4487-a97e-c0d91b673189","resolution":{"observed_at":"2026-08-03T04:26:13.161162Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T04:26:13.203923Z","title":"A novel explainable method based on grad-cam for network intrusion detection,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-03T04:26:13.203923Z"},"links":{"citing_paper":"/paper/2602.13271"},"observation_digest":"sha256:3aed3a79dfb5ce58c4b51c92b070f702cf38c8edb66835dfba802a3538b9171d","observation_id":"7e49da97-0af3-4ca5-9703-1f6d1bb52f6b","resolution":{"observed_at":"2026-08-03T04:26:13.203923Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2602.13271","last_updated":"2026-02-04T20:33:27Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-07T00:24:56.940867Z","submitted_at":"2026-02-04T20:33:27Z","title":"Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework"},"reference_resolution":{"displayed":30,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":30,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":30},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2602.13271."}