Paper Citation Record · LEDGER

The importance of the clustering model to detect new types of intrusion in data traffic

As of 13 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2411.14550.

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

pith.paper-citation-record.v1
2411.14550 v2

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:12:11.815883Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

verified exact20
verified fuzzy6
unresolved3
parse uncertain0
malformed identifier3
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 04b45652-493b-4fc2-aff9-f084d46fc19e · outbound

This paper cites K -means Clustering Algorithms: A Comprehensive Review, Variants Analysis, and Advances in the Era of Big Data.

The importance of the clustering model to detect new types of intrusion in data traffic K -means Clustering Algorithms: A Comprehensive Review, Variants Analysis, and Advances in the Era of Big Data

Reference 1

Resolution: verified exact; doi, observed 2026-08-12T15:12:12.180578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8ace7eea-df3d-4eee-bbb8-9ccdcfaf384a · outbound

This paper cites A Survey on the Use of Data Clustering for Intrusion Detection System in Cybersecurity.

The importance of the clustering model to detect new types of intrusion in data traffic A Survey on the Use of Data Clustering for Intrusion Detection System in Cybersecurity

Reference 2

Resolution: verified exact; raw_fallback, observed 2026-08-12T15:12:39.187636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f217e613-1741-435b-9a6c-f4873b89c201 · outbound

This paper cites A Review on Cybersecurity Datasets for Machine Learning Algorithms.

The importance of the clustering model to detect new types of intrusion in data traffic A Review on Cybersecurity Datasets for Machine Learning Algorithms

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T15:12:11.676433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f17e6370-b762-433e-9200-b482a102a331 · outbound

This paper cites Network Intrusion Detection System Using Supervised Learning Paradigm.

The importance of the clustering model to detect new types of intrusion in data traffic Network Intrusion Detection System Using Supervised Learning Paradigm

Reference 4

Resolution: verified exact; doi, observed 2026-08-12T15:12:12.165030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f08ee6a8-4fc3-4725-bbc8-48c0e8c17a82 · outbound

This paper cites Cybersecurity Detection Model Using Machine Learning Techniques.

The importance of the clustering model to detect new types of intrusion in data traffic Cybersecurity Detection Model Using Machine Learning Techniques

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:12:39.297515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3946f014-97b8-4e34-9b0e-5864056da2c3 · outbound

This paper cites C SVM Classification and KNN Techniques for Cyber Crime Detection.

The importance of the clustering model to detect new types of intrusion in data traffic C SVM Classification and KNN Techniques for Cyber Crime Detection

Reference 6

Resolution: verified exact; doi, observed 2026-08-12T15:12:12.032178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f8c3071b-c285-4461-8dd0-8f860ba1fb2c · outbound

This paper cites A Deep Learning Methodology for Predicting Cybersecurity Attacks on the Internet of Things.

The importance of the clustering model to detect new types of intrusion in data traffic A Deep Learning Methodology for Predicting Cybersecurity Attacks on the Internet of Things

Reference 7

Resolution: verified exact; doi, observed 2026-08-12T15:12:12.014956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 155e1b5e-2253-42aa-a6c1-f480a2870aff · outbound

This paper cites A Survey on Intrusion Detection System: Feature Selection, Model, Performance Measures, Application Perspective, Challenges, and Future Research Directions.

The importance of the clustering model to detect new types of intrusion in data traffic A Survey on Intrusion Detection System: Feature Selection, Model, Performance Measures, Application Perspective, Challenges, and Future Research Directions

Reference 8

Resolution: verified exact; doi, observed 2026-08-12T15:12:11.999155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 21df3681-8ab8-4f33-b869-c4516459bc40 · outbound

This paper cites Data Security and Privacy Protection for Cloud Storage: A Survey.

The importance of the clustering model to detect new types of intrusion in data traffic Data Security and Privacy Protection for Cloud Storage: A Survey

Reference 9

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-12T15:12:39.018922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bff82df3-dd90-4cd5-bb90-29f446168b9e · outbound

This paper cites A Systematic Literature Review of Intrusion Detection System for Network Security: Research Trends, Datasets and Methods.

The importance of the clustering model to detect new types of intrusion in data traffic A Systematic Literature Review of Intrusion Detection System for Network Security: Research Trends, Datasets and Methods

Reference 10

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-12T15:12:34.503216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d331dd9c-8774-4e98-86e0-33fb38670e89 · outbound

This paper cites Machine Le arning and Cyber Security.

The importance of the clustering model to detect new types of intrusion in data traffic Machine Le arning and Cyber Security

Reference 11

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-12T15:12:30.781357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 63417c6d-9860-4a8b-867e-2ab90dcc7189 · outbound

This paper cites A Comparative Analysis of Supervised and Unsupervised Models for Detecting Attacks on the Intrusion Detection Systems.

The importance of the clustering model to detect new types of intrusion in data traffic A Comparative Analysis of Supervised and Unsupervised Models for Detecting Attacks on the Intrusion Detection Systems

Reference 12

Resolution: verified exact; doi, observed 2026-08-12T15:12:11.982848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e7b74be0-2a7a-429f-b2f8-13074a790485 · outbound

This paper cites Optimized Deep Learning with Binary PSO for Intrusion Detection on CSE-CIC-IDS2018 Dataset.

The importance of the clustering model to detect new types of intrusion in data traffic Optimized Deep Learning with Binary PSO for Intrusion Detection on CSE-CIC-IDS2018 Dataset

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:12:39.281777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a4b3cf2d-b275-49bf-88b3-54bdd83cbec6 · outbound

This paper cites An Effect ive Deep Learning Based Multi -Class Classification of DoS and DDoS Attack Detection.

The importance of the clustering model to detect new types of intrusion in data traffic An Effect ive Deep Learning Based Multi -Class Classification of DoS and DDoS Attack Detection

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:12:39.264820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1ad7537a-8aa3-4501-a4cd-251638205f39 · outbound

This paper cites A Novel Attention-Based Feature Learning and Optimal Deep Learning Approach for Network Intrusion Detection.

The importance of the clustering model to detect new types of intrusion in data traffic A Novel Attention-Based Feature Learning and Optimal Deep Learning Approach for Network Intrusion Detection

Reference 15

Resolution: verified exact; doi, observed 2026-08-12T15:12:11.967151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 83586fc5-2674-4435-b8fe-624a47da31e3 · outbound

This paper cites Evaluation of Machine Learning Algorithms in Network-Based Intrusion Detection System.

The importance of the clustering model to detect new types of intrusion in data traffic Evaluation of Machine Learning Algorithms in Network-Based Intrusion Detection System

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-12T15:12:27.472948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 374f3bce-fb2e-40ec-b87c-84da3174b4d4 · outbound

This paper cites High -Dimensional Pattern Regression Using Machine Learning: From Medical Images to Continuous Clini cal Variables.

The importance of the clustering model to detect new types of intrusion in data traffic High -Dimensional Pattern Regression Using Machine Learning: From Medical Images to Continuous Clini cal Variables

Reference 18

Resolution: verified exact; doi, observed 2026-08-12T15:12:11.950980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a0dea806-9f17-4749-9081-a8c414860830 · outbound

This paper cites Selection of Relevant Features and Examples in Machine Learning.

The importance of the clustering model to detect new types of intrusion in data traffic Selection of Relevant Features and Examples in Machine Learning

Reference 19

Resolution: malformed identifier; no resolver link, observed 2026-08-12T15:12:11.750140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d576e4fa-f640-40ce-8b1c-b72a758530d1 · outbound

This paper cites Introduction to the Data Mining Techniques in Cybersecurity.

The importance of the clustering model to detect new types of intrusion in data traffic Introduction to the Data Mining Techniques in Cybersecurity

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:12:39.248997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 964a969d-a65f-42d5-9c50-c53507156c29 · outbound

This paper cites A Clustering Method Based on K -Means Algorithm.

The importance of the clustering model to detect new types of intrusion in data traffic A Clustering Method Based on K -Means Algorithm

Reference 21

Resolution: verified exact; doi, observed 2026-08-12T15:12:11.924221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 349f1fa9-3118-4480-b70f-de2fcad81a3e · outbound

This paper cites Unsupervised K - Means Clustering Algorithm.

The importance of the clustering model to detect new types of intrusion in data traffic Unsupervised K - Means Clustering Algorithm

Reference 22

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-12T15:12:27.448429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ccc885d2-aace-461b-85be-b7812bad8152 · outbound

This paper cites Multi -View K-Means Clustering Algorithm Based on Redundant and Sparse Feature Learning.

The importance of the clustering model to detect new types of intrusion in data traffic Multi -View K-Means Clustering Algorithm Based on Redundant and Sparse Feature Learning

Reference 23

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-12T15:12:23.960601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a9d4cfda-c9ab-4902-81ba-3748c91dc333 · outbound

This paper cites A Study of Graph-Based System for Multi -View Clustering.

The importance of the clustering model to detect new types of intrusion in data traffic A Study of Graph-Based System for Multi -View Clustering

Reference 24

Resolution: verified exact; doi, observed 2026-08-12T15:12:11.908388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4f7d9e25-59cc-4d2c-81c0-fdc959d6fd8e · outbound

This paper cites Intrusion Detection System: A Comprehensive Review.

The importance of the clustering model to detect new types of intrusion in data traffic Intrusion Detection System: A Comprehensive Review

Reference 25

Resolution: verified exact; doi, observed 2026-08-12T15:12:11.892677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b4578c0a-d161-4fc6-a732-b12794f491fe · outbound

This paper cites A Clustering Met hod Based on K - Means Algorithm.

The importance of the clustering model to detect new types of intrusion in data traffic A Clustering Met hod Based on K - Means Algorithm

Reference 26

Resolution: malformed identifier; doi_truncated, observed 2026-08-12T15:12:11.876730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9233bde9-472e-4b24-8e9c-54e6ad485281 · outbound

This paper cites The K -Means Algor ithm: A Comprehensive Survey and Performance Evaluation.

The importance of the clustering model to detect new types of intrusion in data traffic The K -Means Algor ithm: A Comprehensive Survey and Performance Evaluation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T15:12:11.787931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06200917-b9a4-4c26-8f05-dff4b7026c1b · outbound

This paper cites Landslide Susceptibility Zonation Method Based on C5.0 Decision Tree and K - Means Cluster Algorithms to Improve the Efficiency of Risk Management.

The importance of the clustering model to detect new types of intrusion in data traffic Landslide Susceptibility Zonation Method Based on C5.0 Decision Tree and K - Means Cluster Algorithms to Improve the Efficiency of Risk Management

Reference 28

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-12T15:12:20.247792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 01b91870-7f1d-45db-8588-c902caf7db0b · outbound

This paper cites K -Means Tree: An Optimal Clustering Tree for Unsupervised Learning.

The importance of the clustering model to detect new types of intrusion in data traffic K -Means Tree: An Optimal Clustering Tree for Unsupervised Learning

Reference 29

Resolution: malformed identifier; no resolver link, observed 2026-08-12T15:12:11.797384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6b91baf-badb-4702-ac66-60f3a491f11e · outbound

This paper cites Detecting Cybersecurity Attacks Using Different Network Features with LightGBM and XGBoost Learners.

The importance of the clustering model to detect new types of intrusion in data traffic Detecting Cybersecurity Attacks Using Different Network Features with LightGBM and XGBoost Learners

Reference 30

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-12T15:12:13.138685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f6086e3d-4d1f-4124-8b9f-3fb24452bde1 · outbound

This paper cites Anomaly Detection Using XGBoost Ensemble of Deep Neural Network Models.

The importance of the clustering model to detect new types of intrusion in data traffic Anomaly Detection Using XGBoost Ensemble of Deep Neural Network Models

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:12:39.232922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 60c589ef-9e3c-49ce-937a-9c34f28c3f86 · outbound

This paper cites Network Intrusion Detection with XGBoost.

The importance of the clustering model to detect new types of intrusion in data traffic Network Intrusion Detection with XGBoost

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:12:39.217219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c3ab62c5-d113-4abb-889e-0898fdb8151b · outbound

This paper cites an unresolved cited work.

The importance of the clustering model to detect new types of intrusion in data traffic Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:12:39.202028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

No inbound Pith citation observations are available.