Paper Citation Record · LEDGER

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification

As of 14 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 1 inbound Pith citation observation for arXiv:2506.07882.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.07882 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:27:33.471056Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T04:26:13.161162Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

44 of 44 outbound references displayed

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verified fuzzy39
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2bd0d563-fe91-4724-8dab-9bb2a73fb169 · outbound

This paper cites A performance analysis of snort and suricata network intrusion detection and prevention engines,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification A performance analysis of snort and suricata network intrusion detection and prevention engines,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.356676Z

Source-reported events for the cited work

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Observation b43fa7ab-0ba3-4a90-be44-7c6696411838 · outbound

This paper cites In-depth feature selection for the statistical machine learning-based botnet detection in IoT networks,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification In-depth feature selection for the statistical machine learning-based botnet detection in IoT networks,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.341283Z

Source-reported events for the cited work

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Observation 70a5d87a-6eab-4040-a1b7-9b77496464c6 · outbound

This paper cites Explaining Network Intrusion Detection System Using Explainable AI Framework.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Explaining Network Intrusion Detection System Using Explainable AI Framework

Reference 3

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Source-reported events for the cited work

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Observation 125dda1e-db72-44c2-9630-6f1d9a0ec3ea · outbound

This paper cites A detailed analysis of the KDD CUP 99 data set,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification A detailed analysis of the KDD CUP 99 data set,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.326186Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3449391b-00fd-4622-8961-a081fd14ab08 · outbound

This paper cites Recent advances in trustworthy explainable artificial intelligence: Status, challenges, and perspectives,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Recent advances in trustworthy explainable artificial intelligence: Status, challenges, and perspectives,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.311101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d08e70e0-0420-4420-bf2d-44b8df12f73f · outbound

This paper cites Evaluation metrics in explainable artificial intelligence (XAI),.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Evaluation metrics in explainable artificial intelligence (XAI),

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.296298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d05e51e5-447a-4dfc-aa53-3eef93cfa3dc · outbound

This paper cites Outmet: A new metric for prioritising intrusion alerts using correlation and outlier analysis,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Outmet: A new metric for prioritising intrusion alerts using correlation and outlier analysis,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.280896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d7a808b9-a49e-4ba5-bc2b-94506c939ac1 · outbound

This paper cites A review of anomaly based intrusion detection systems,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification A review of anomaly based intrusion detection systems,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.265953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 67486354-b499-48b1-8f70-0f13babe0b41 · outbound

This paper cites Cloud service oriented architecture (CSoA) for agriculture through internet of things (IoT) and big data,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Cloud service oriented architecture (CSoA) for agriculture through internet of things (IoT) and big data,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.250607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1b03aaf3-d79c-42c9-9e88-ba40e5a909e2 · outbound

This paper cites XAI-CF–Examining the Role of Explainable Artificial Intelligence in Cyber Forensics,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification XAI-CF–Examining the Role of Explainable Artificial Intelligence in Cyber Forensics,

Reference 10

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Source-reported events for the cited work

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Observation 64f69072-a10b-4b97-9aeb-117af3448889 · outbound

This paper cites Explainable intrusion detection for cyber defences in the internet of things: Opportunities and solutions,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Explainable intrusion detection for cyber defences in the internet of things: Opportunities and solutions,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.235004Z

Source-reported events for the cited work

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Observation fadefd8c-61ef-47d1-b8c2-3e36c002a309 · outbound

This paper cites Enhancing IoT Botnet Attack Detection in SOCs with an Explainable Active Learning Framework,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Enhancing IoT Botnet Attack Detection in SOCs with an Explainable Active Learning Framework,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.219544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ac279ea9-4c93-478a-982a-2d0f79b81880 · outbound

This paper cites Featureless discovery of correlated and false intrusion alerts,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Featureless discovery of correlated and false intrusion alerts,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.204118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4ea9c8c6-a243-49d4-8391-c7bc9af7f39e · outbound

This paper cites Deepcase: Semi-supervised contextual analysis of security events,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Deepcase: Semi-supervised contextual analysis of security events,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.188211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c55de301-65ac-491b-8075-a50866378ca3 · outbound

This paper cites Breaking alert fatigue: AI-assisted SIEM framework for effective incident response,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Breaking alert fatigue: AI-assisted SIEM framework for effective incident response,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.173669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation cb1afe21-1ac4-4c47-a2fd-d4d8bc80aaa3 · outbound

This paper cites Platform design and implementation for flexible data processing and building ML models of IDS alerts,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Platform design and implementation for flexible data processing and building ML models of IDS alerts,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.158173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 449b7e23-b201-4042-8c04-a9c892856fa7 · outbound

This paper cites A user-centric machine learning framework for cyber security operations center,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification A user-centric machine learning framework for cyber security operations center,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.142457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b428c5ff-6a82-4313-89e5-59b5302fed63 · outbound

This paper cites Identifying truly suspicious events and false alarms based on alert graph,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Identifying truly suspicious events and false alarms based on alert graph,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.127848Z

Source-reported events for the cited work

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Observation 12a69946-cffa-4e80-af9a-c81cf3ea02c6 · outbound

This paper cites Combat security alert fatigue with AI-assisted techniques,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Combat security alert fatigue with AI-assisted techniques,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.112916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3c03fa02-fb31-4d10-9043-3e3a955c9e97 · outbound

This paper cites A stream clustering algorithm for classifying network IDS alerts,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification A stream clustering algorithm for classifying network IDS alerts,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.098066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ad21ddd3-c382-4f21-95a9-290be4a21840 · outbound

This paper cites How to Build a SOC on a Budget,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification How to Build a SOC on a Budget,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.082158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fe54b887-4717-499d-bef3-014f8290313a · outbound

This paper cites Stream clustering guided supervised learning for classifying NIDS alerts,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Stream clustering guided supervised learning for classifying NIDS alerts,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.066858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b4822205-fe0f-4bb5-b701-2480cfcb07e8 · outbound

This paper cites Axiomatic attribution for deep networks,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Axiomatic attribution for deep networks,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.051481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 94de5eee-4447-45d5-b074-4ed3dd32b156 · outbound

This paper cites Learning important features through propagating activation differences,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Learning important features through propagating activation differences,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.035256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6d4f5432-5f74-46cc-bbb2-ccd50ae13164 · outbound

This paper cites Why should I trust you? Explaining the predictions of any classifier,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Why should I trust you? Explaining the predictions of any classifier,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.019304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0b604c5d-317f-45bf-aae7-ede25d3274b0 · outbound

This paper cites A unified approach to interpreting model predictions,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification A unified approach to interpreting model predictions,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:34.004027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9da6aa83-0977-4ae6-bf6f-847a686fa870 · outbound

This paper cites Leveraging Latent Features for Local Explanations.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Leveraging Latent Features for Local Explanations

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:27:33.640321Z

Source-reported events for the cited work

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Observation 8a72a560-60e0-4b12-8460-51cc06b22979 · outbound

This paper cites Evaluating and Aggregating Feature-based Model Explanations.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Evaluating and Aggregating Feature-based Model Explanations

Reference 28

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Source-reported events for the cited work

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Observation b27f2f8f-38b9-420a-a47b-b993ca54f937 · outbound

This paper cites CLEVR-XAI: A benchmark dataset for the ground truth evaluation of neural network explanations,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification CLEVR-XAI: A benchmark dataset for the ground truth evaluation of neural network explanations,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:33.989360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 218f289d-fb0c-4ac0-b6cb-13fefde5db21 · outbound

This paper cites Improving Transparency and Explainability of Deep Learning Based IoT Botnet Detection Using Explainable Artificial Intelligence (XAI),.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Improving Transparency and Explainability of Deep Learning Based IoT Botnet Detection Using Explainable Artificial Intelligence (XAI),

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:33.973671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 27fa64e0-5700-4142-b4d6-126e471b21d5 · outbound

This paper cites European Union regulations on algorithmic decision-making and a “right to explanation.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification European Union regulations on algorithmic decision-making and a “right to explanation

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:33.958344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f50d7fc2-aec1-4652-b007-9b23cf07b16c · outbound

This paper cites Achieving explainability of intrusion detection system by hybrid oracle-explainer approach,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Achieving explainability of intrusion detection system by hybrid oracle-explainer approach,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:33.942955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 17184845-2956-427a-8200-b3419cfbcf32 · outbound

This paper cites Deceiving Post-hoc Explainable AI (XAI) Methods in Network Intrusion Detection,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Deceiving Post-hoc Explainable AI (XAI) Methods in Network Intrusion Detection,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:33.927364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 56bf0913-84aa-42be-96ef-82fa57635786 · outbound

This paper cites Improving IoT Security With Explainable AI: Quantitative Evaluation of Explainability for IoT Botnet Detection,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Improving IoT Security With Explainable AI: Quantitative Evaluation of Explainability for IoT Botnet Detection,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:33.910673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 22f56ee2-f5d1-4ec5-bfbb-02a8323d9fdb · outbound

This paper cites Robust network anomaly detection using ensemble learning approach and explainable artificial intelligence (XAI),.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Robust network anomaly detection using ensemble learning approach and explainable artificial intelligence (XAI),

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:33.892384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a0e289e3-636b-4294-8004-bb5a24d03c2f · outbound

This paper cites NSL-KDD | Datasets | Research | Canadian Institute for Cybersecurity | UNB,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification NSL-KDD | Datasets | Research | Canadian Institute for Cybersecurity | UNB,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:33.877045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4dc08b2c-f3ae-474b-85b1-199785219e2b · outbound

This paper cites Evaluating The Explainability of State-of-the-Art Machine Learning- based IoT Network Intrusion Detection Systems,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Evaluating The Explainability of State-of-the-Art Machine Learning- based IoT Network Intrusion Detection Systems,

Reference 37

Resolution: verified exact; raw_fallback, observed 2026-08-07T05:27:33.597001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 160f20cb-b77e-4ce6-85e1-243d97e60ffa · outbound

This paper cites Trust XAI: Model-agnostic explanations for AI with a case study on IIoT security,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Trust XAI: Model-agnostic explanations for AI with a case study on IIoT security,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:33.860588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e0c62abb-f2aa-48db-894b-2741d36a96da · outbound

This paper cites The UNSW-NB15 Dataset | UNSW Research,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification The UNSW-NB15 Dataset | UNSW Research,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:33.843455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 36f90006-37ae-43cd-8bdd-10d432aebdc5 · outbound

This paper cites Intrusion detection by machine learning: A review,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Intrusion detection by machine learning: A review,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:33.825634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b49f1338-65ca-4cfc-9aa6-b2214c2e8b73 · outbound

This paper cites How can I choose an explainer? An application-grounded evaluation of post-hoc explanations,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification How can I choose an explainer? An application-grounded evaluation of post-hoc explanations,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:33.807548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6c681d49-4648-4e4c-8b71-f8e7b924fe4d · outbound

This paper cites Statistical comparisons of classifiers over multiple data sets,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Statistical comparisons of classifiers over multiple data sets,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:33.790490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4bfe6973-3bfa-49f9-9ac6-4339b086877e · outbound

This paper cites Wilcoxon signed-rank test,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Wilcoxon signed-rank test,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:33.775108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1602b0e6-da5a-4a13-87ac-576fe3026b12 · outbound

This paper cites Explainable Federated Learning for Botnet Detection in IoT Networks,.

Evaluating explainable AI for deep learning-based network intrusion detection system alert classification Explainable Federated Learning for Botnet Detection in IoT Networks,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:27:33.758847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

Observation 37dc099e-fcd2-4487-a97e-c0d91b673189 · inbound

Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework cites this paper.

Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework Evaluating explainable AI for deep learning-based network intrusion detection system alert classification

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T04:26:13.161162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.