Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-08T17:11:05.621676Z
Paper Citation Record · LEDGER
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems
As of 6 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2605.05275.
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 2026-08-06T06:34:29.942622+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
29 of 29 outbound references displayed
- verified exact0
- verified fuzzy29
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 10d330fe-b175-46f6-b332-19f00e326936 · outbound
This paper cites Evaluating large language models effectiveness for flow-based intrusion detection: a comparative study with ml and dl baselines.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Evaluating large language models effectiveness for flow-based intrusion detection: a comparative study with ml and dl baselines
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.456172Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 87cc01f6-0962-48e5-bff0-b5f10fbd2dc9 · outbound
This paper cites A self-adaptive intrusion detection system for zero-day attacks using deep q-networks.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems A self-adaptive intrusion detection system for zero-day attacks using deep q-networks
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.467739Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 8e852744-8159-455c-90b3-bd30def5c0a4 · outbound
This paper cites Lstm- 1dresnet: An intrusion detection model for connected and autonomous vehicles based on deep learning.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Lstm- 1dresnet: An intrusion detection model for connected and autonomous vehicles based on deep learning
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.464900Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 223220cb-cad4-4bd6-aafb-bb937866ffc0 · outbound
This paper cites Dati- ids: Domain adaptation and time-series imaging-based intrusion detec- tion system for connected autonomous vehicles.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Dati- ids: Domain adaptation and time-series imaging-based intrusion detec- tion system for connected autonomous vehicles
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.508183Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 23bd88ce-f5a0-4a1e-b180-c7a1d8172a96 · outbound
This paper cites Fsl-ids: Feder- ated semi-supervised learning intrusion detection system for in-vehicle networks.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Fsl-ids: Feder- ated semi-supervised learning intrusion detection system for in-vehicle networks
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.462256Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 590b71c6-e0ec-459e-a1dc-acd59602194e · outbound
This paper cites Ieee standard for floating-point arithmetic.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Ieee standard for floating-point arithmetic
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.459632Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 61079363-7c1a-4feb-8bcc-f9f314871f5e · outbound
This paper cites A detailed analysis of the kdd cup 99 data set.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems A detailed analysis of the kdd cup 99 data set
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.504934Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0f9d4a24-c926-459a-9a92-659ba334a36e · outbound
This paper cites Unsw-nb15: a comprehensive data set for network intrusion detection systems (unsw-nb15 network data set).
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Unsw-nb15: a comprehensive data set for network intrusion detection systems (unsw-nb15 network data set)
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.511226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 47955860-76f8-4e3e-962e-25d8c22f13cf · outbound
This paper cites Hae-hrl: A network intrusion detection system utilizing a novel autoencoder and a hybrid enhanced lstm-cnn- based residual network.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Hae-hrl: A network intrusion detection system utilizing a novel autoencoder and a hybrid enhanced lstm-cnn- based residual network
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.514759Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7a53bd99-2f64-4e36-b9d4-ff6826730064 · outbound
This paper cites Optimized detection of cyber-attacks on iot networks via hybrid deep learning models.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Optimized detection of cyber-attacks on iot networks via hybrid deep learning models
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.453330Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 55eb9174-c128-437d-83c1-d2822de04447 · outbound
This paper cites Ais-nids: An intelli- gent and self-sustaining network intrusion detection system.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Ais-nids: An intelli- gent and self-sustaining network intrusion detection system
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.470737Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e7e8230a-0c88-4925-a668-6184b856397c · outbound
This paper cites An enhanced ai-based network intrusion detection system using generative adversarial networks.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems An enhanced ai-based network intrusion detection system using generative adversarial networks
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.499580Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2d7b7f75-f9b1-4cdf-b961-2390570ff617 · outbound
This paper cites Information system security rein- forcement with wgan-gp for detection of zero-day attacks.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Information system security rein- forcement with wgan-gp for detection of zero-day attacks
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.502432Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ad2dd4cf-5284-4863-a183-40fa7e63f820 · outbound
This paper cites Senet-i: An approach for detecting network intrusions through serialized network traffic images.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Senet-i: An approach for detecting network intrusions through serialized network traffic images
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.496970Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation be4570df-5bc1-4cc4-a039-2bbd793f75cd · outbound
This paper cites An optimized cnn- based intrusion detection system for reducing risks in smart farming.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems An optimized cnn- based intrusion detection system for reducing risks in smart farming
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.525028Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 737063a2-f65c-4891-9da9-53c47b553744 · outbound
This paper cites A cognitive security framework for detecting intrusions in iot and 5g utilizing deep learning.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems A cognitive security framework for detecting intrusions in iot and 5g utilizing deep learning
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.530549Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4f8dfcac-c0c9-4f36-aa7f-755a2c73841c · outbound
This paper cites Intrusion detection in iot and wireless networks using image-based neural network classification.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Intrusion detection in iot and wireless networks using image-based neural network classification
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.493845Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b923280d-56ea-4385-ae31-65d0220ab1d8 · outbound
This paper cites Gcb-ppo2: A hybrid deep reinforcement learning intrusion detection system for under- represented attack categories in sdn.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Gcb-ppo2: A hybrid deep reinforcement learning intrusion detection system for under- represented attack categories in sdn
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.490677Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d3285b69-2fb5-4ac2-b9cd-833846bc5ba8 · outbound
This paper cites Towards real-time network intrusion detection with image-based sequential packets representation.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Towards real-time network intrusion detection with image-based sequential packets representation
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.527812Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f837ff6d-f155-4a5c-8685-f9cbf5f0be62 · outbound
This paper cites Network intrusion detection via flow-to-image conversion and vision transformer classification.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Network intrusion detection via flow-to-image conversion and vision transformer classification
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.536519Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ff059a62-e828-430f-b35f-c59ba13ebf03 · outbound
This paper cites A feature selection algorithm for intrusion detection system based on the enhanced heuristic opti- mizer.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems A feature selection algorithm for intrusion detection system based on the enhanced heuristic opti- mizer
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.482879Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 8e7fc89d-184f-4234-a5cd-f0207158a957 · outbound
This paper cites Tier-based optimization for synthesized network intrusion detection system.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Tier-based optimization for synthesized network intrusion detection system
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.485536Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4e8e85c7-4db9-4e0d-b8a6-231d25fdac68 · outbound
This paper cites A deep-learned embedding technique for categorical features encoding.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems A deep-learned embedding technique for categorical features encoding
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.476810Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a47a989c-6781-43e0-adff-e07e203ad439 · outbound
This paper cites Repre- sentation learning for tabular data: A comprehensive survey.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Repre- sentation learning for tabular data: A comprehensive survey
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.473809Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 72eb5f4a-8795-46f2-aa91-67e7cd218a86 · outbound
This paper cites A hybrid cnn-lstm approach for intelligent cyber intrusion detection system.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems A hybrid cnn-lstm approach for intelligent cyber intrusion detection system
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.533041Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation fc95149f-0ac1-489b-b97a-4199e21ac5de · outbound
This paper cites Lightweight cnn-bilstm based intrusion detection systems for resource-constrained iot devices.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Lightweight cnn-bilstm based intrusion detection systems for resource-constrained iot devices
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.488105Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e1b2869f-6756-477d-a62f-2007f8d9fb98 · outbound
This paper cites Intrusion detection algorithm based on multi-scale feature fusion.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Intrusion detection algorithm based on multi-scale feature fusion
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.479769Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 8eb507c4-7e63-4de5-8523-88de0498a78f · outbound
This paper cites Tmg-gan: Generative adversarial networks-based imbalanced learning for network intrusion detection.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Tmg-gan: Generative adversarial networks-based imbalanced learning for network intrusion detection
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.518176Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4618a8a5-982b-473d-98c0-5339252a6db8 · outbound
This paper cites Gma-sawgan-gp: A novel data generative framework to enhance ids detection performance.
A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems Gma-sawgan-gp: A novel data generative framework to enhance ids detection performance
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T08:21:58.522136Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Pith citing papers
No inbound Pith citation observations are available.