Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-21T20:13:41.279665Z
Paper Citation Record · LEDGER
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning
As of 1 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2511.06714.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-07-31T06:34:12.847434+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
18 of 18 outbound references displayed
- verified exact2
- verified fuzzy16
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation e8083b43-e75f-44e3-a915-b9fee94d25f5 · outbound
This paper cites Cyber-physical system security for the electric power grid.
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning Cyber-physical system security for the electric power grid
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T20:14:20.545444Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 84d79c4d-9a5b-49fc-82d0-6fe656dfbb7d · outbound
This paper cites Trends in smart grid cyber-physical security: Components, threats, and solutions.
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning Trends in smart grid cyber-physical security: Components, threats, and solutions
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T20:14:20.541686Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation d07d03fa-5e9e-4e9f-b8b1-7e806c4f864f · outbound
This paper cites Cyber physical attack- resilient wide-area monitoring, protection, and control for the power grid.
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning Cyber physical attack- resilient wide-area monitoring, protection, and control for the power grid
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T20:14:20.537606Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation ecf27773-20f2-4efe-92e7-6adc9e39d922 · outbound
This paper cites Scpse: Security-oriented cyber-physical state estimation for power grid critical infrastructures.
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning Scpse: Security-oriented cyber-physical state estimation for power grid critical infrastructures
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T20:14:20.514886Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 3f011150-dbd2-411f-b2cf-ad1084f33526 · outbound
This paper cites Influence of inverter-based resources on microgrid protection: Part 1: Microgrids in radial distribution systems.
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning Influence of inverter-based resources on microgrid protection: Part 1: Microgrids in radial distribution systems
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T20:14:20.521505Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 3963ba45-2f52-497b-8ec2-3556fcc2a4bf · outbound
This paper cites Challenges in microgrid protection.
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning Challenges in microgrid protection
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T20:14:20.516848Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation d5944a07-4014-45ce-b675-01d26eea7cc5 · outbound
This paper cites Machine learning– based intrusion detection for smart grid computing: A survey.
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning Machine learning– based intrusion detection for smart grid computing: A survey
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T20:14:20.533520Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 3d82cd31-ebfb-4854-a524-966e455f98d3 · outbound
This paper cites Identification and classification for multiple cyber attacks in power grids based on deep capsule convolutional neural network.
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning Identification and classification for multiple cyber attacks in power grids based on deep capsule convolutional neural network
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T20:14:20.535651Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation ed98a3ce-1f5d-42f3-b623-cc2708ac906e · outbound
This paper cites Ensemble learning methods for anomaly intrusion detection system in smart grid.
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning Ensemble learning methods for anomaly intrusion detection system in smart grid
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T20:14:20.543542Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation bd0bde0a-b174-413f-9cbc-103cdf787984 · outbound
This paper cites Ensemble voting-based anomaly detection for a smart grid communication infrastructure.
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning Ensemble voting-based anomaly detection for a smart grid communication infrastructure
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T20:14:20.519451Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation cbc19a22-53c8-4516-bb30-0a41119fb442 · outbound
This paper cites A real-time deep learning- based fault diagnosis framework in power distribution system with pvs.
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning A real-time deep learning- based fault diagnosis framework in power distribution system with pvs
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T20:14:20.529305Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 34e7684a-93a7-4a79-9489-6f2275dba51d · outbound
This paper cites Anomaly identification in power systems using dynamic state estimation and deep learning.
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning Anomaly identification in power systems using dynamic state estimation and deep learning
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T20:14:20.527390Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 73bdbb12-a349-4a33-b173-dc1cee05748f · outbound
This paper cites Machine learning for power system disturbance and cyber- attack discrimination.
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning Machine learning for power system disturbance and cyber- attack discrimination
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T20:14:20.525417Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 9b308733-d356-4f81-a13d-01f71e9c8823 · outbound
This paper cites Active Distribution System Coordinated Control Method via Artificial Intelligence.
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning Active Distribution System Coordinated Control Method via Artificial Intelligence
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T20:14:20.307403Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 88d1d332-2aeb-4509-b38a-0a97945697ea · outbound
This paper cites Rte dse protection demonstration.
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning Rte dse protection demonstration
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T20:14:20.539595Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 0bd92e6f-41cf-4fbe-8224-6e58c8e29149 · outbound
This paper cites T4tech: Open dataset and code for power system fault and cyber-attack classification.
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning T4tech: Open dataset and code for power system fault and cyber-attack classification
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T20:14:20.531556Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 2284ca52-0629-486a-9ef4-c16d16407e9a · outbound
This paper cites Dynamic estimation-based protection and hidden failure detection and identifica- tion: Inverter-dominated power systems.
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning Dynamic estimation-based protection and hidden failure detection and identifica- tion: Inverter-dominated power systems
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T20:14:20.523557Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation cc6d37b3-6444-4e56-ab48-d4d95055955d · outbound
This paper cites Centralized Dynamic State Estimation Algorithm for Detecting and Distinguishing Faults and Cyber Attacks in Power Systems.
The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning Centralized Dynamic State Estimation Algorithm for Detecting and Distinguishing Faults and Cyber Attacks in Power Systems
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T20:14:20.310882Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Pith citing papers
No inbound Pith citation observations are available.