Pith. sign in

Paper Citation Record · LEDGER

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things

As of 16 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2505.06636.

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

pith.paper-citation-record.v1
2505.06636 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:42:26.931338Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

38 of 38 outbound references displayed

  • verified exact1
  • verified fuzzy30
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f701e653-91cd-4347-8f5d-131bbad8fa90 · outbound

This paper cites Internet of robotic things intelligent connectivity and platforms,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Internet of robotic things intelligent connectivity and platforms,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.662142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.738896Z digest=sha256:b28a63a6de12a76c446fba7a0f40b91965230f612bc840e0a6a3a6c7983e3e20

Observation 44b9e044-52f2-43a3-adcf-904908e0e763 · outbound

This paper cites Multi- objective resource allocation for edge cloud based robotic workflow in smart factory,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Multi- objective resource allocation for edge cloud based robotic workflow in smart factory,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.646223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.744391Z digest=sha256:54fb3ea4ec6e221fb663437aded5dc0d8a460df686bae37e27858b20f9e2dc88

Observation 41025a09-b43b-432d-a0fe-4681223a8a14 · outbound

This paper cites Internet of robotic things– converging sensing/actuating, hyperconnectivity, artificial intelligence and iot platforms,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Internet of robotic things– converging sensing/actuating, hyperconnectivity, artificial intelligence and iot platforms,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.630595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.749968Z digest=sha256:7fc7d92ab6cf0d201e86963ba1a98af9e508e2ba020cdcaec34e85b45ccd0e2f

Observation 1565b416-7a7d-4f41-9cc4-5058b42bf52b · outbound

This paper cites A novel multi-module integrated intrusion detection system for high-dimensional imbalanced data,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things A novel multi-module integrated intrusion detection system for high-dimensional imbalanced data,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.615391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.758548Z digest=sha256:2584e4081bd09f6015985247d62e62de06632f3529e044fb430db5147c1d3aa0

Observation 50b8bfdb-3a24-4d73-acc8-56d2d439332b · outbound

This paper cites Big data manage- ment algorithms, deep learning-based object detection technologies, and geospatial simulation and sensor fusion tools in the internet of robotic things,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Big data manage- ment algorithms, deep learning-based object detection technologies, and geospatial simulation and sensor fusion tools in the internet of robotic things,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.596928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.763738Z digest=sha256:1f9167bb6ad3374d17706cd8c9e6032a21f8d26e8c8cb42160b6024a4933172f

Observation b43fa2bc-3ea9-4e9f-aa68-1a94d6988640 · outbound

This paper cites Automatic robot manoeuvres detection using computer vision and deep learning techniques: a perspective of internet of robotics things (iort),.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Automatic robot manoeuvres detection using computer vision and deep learning techniques: a perspective of internet of robotics things (iort),

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.578048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.770031Z digest=sha256:e20e985908b5060e760e3046fa02b36d9e1a1ea30653c64ad737c3a9fe0fedf5

Observation fd8971ed-ed7d-4f15-95e8-cbf106912feb · outbound

This paper cites Internet of things applications, security challenges, attacks, intrusion detection, and future visions: A system- atic review,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Internet of things applications, security challenges, attacks, intrusion detection, and future visions: A system- atic review,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.560853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.775296Z digest=sha256:0f2c6fbce1c10b8b1ebcc42e7daaa004ef3b97d8493dca485cfe1d9ada75beab

Observation 72cbaf64-b947-4c0b-bdd8-40fe78591ef0 · outbound

This paper cites Attack and anomaly detection in iot sensors in iot sites using machine learning approaches,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Attack and anomaly detection in iot sensors in iot sites using machine learning approaches,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.543038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.780655Z digest=sha256:1d87c134a73b710140495dd883001c9c5084380328aa91a3c27f4fa6aa9cc67e

Observation 461e51b6-45c1-4fb1-be82-d6c82012fd80 · outbound

This paper cites Internet of things intrusion detection: Centralized, on-device, or federated learning?.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Internet of things intrusion detection: Centralized, on-device, or federated learning?

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.522339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.785871Z digest=sha256:a64a0242db20882ea3157e995e6735620158f8300cb951c84ca87c9a2d1e7c4c

Observation ce82b4f1-eeba-4dca-8d7a-4791de04019a · outbound

This paper cites Communication- efficient learning of deep networks from decentralized data,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Communication- efficient learning of deep networks from decentralized data,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.496542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.791237Z digest=sha256:a613577235384bf6ff4f778fa7380e4a3b078705e957f33ed55d460cdb470b18

Observation 62a68ef9-8647-417f-88ad-4a4f3a7a7b92 · outbound

This paper cites Unsupervised data augmentation for consistency training,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Unsupervised data augmentation for consistency training,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.472336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.797868Z digest=sha256:5689637f175d2ff4407cf7cccac769b8aa250bb518e55169dcdc916b7a05d7fa

Observation 53f44bcc-083e-4c7d-b4b1-54ee1a439a73 · outbound

This paper cites Mixmatch: A holistic approach to semi-supervised learning,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Mixmatch: A holistic approach to semi-supervised learning,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.454132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.804273Z digest=sha256:30248e1e164dc7062b94ea6bf4abe254f5aad9aa69fb8f3f953465f89a90c6f5

Observation 63212abf-5e42-4f2b-ab33-564351ec6158 · outbound

This paper cites Fixmatch: Simplifying semi- supervised learning with consistency and confidence,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Fixmatch: Simplifying semi- supervised learning with consistency and confidence,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.435499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.809395Z digest=sha256:748e9bd21e38d801aaabbe6b3bd5654ca2bb225e141326cb4d09bcd641d9af37

Observation bffdd539-0fe7-4f72-be67-212026379f68 · outbound

This paper cites Federated cycling (fedcy): Semi-supervised federated learning of surgical phases,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Federated cycling (fedcy): Semi-supervised federated learning of surgical phases,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.419082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.814078Z digest=sha256:337fc9b21681d11c3dbc89b1c918cd28cf5ca6573691d53e947dd886f9f24f89

Observation 7dc2e81c-8c68-4983-9685-61c1ce512e19 · outbound

This paper cites Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-15T22:42:26.819526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:42:26.819526Z digest=sha256:bc7a7d0c168b1082ca10dcb02e32fbba0cd8857398f1c850c1e980558d619cc1

Observation cd023e6b-0067-4618-a910-59441e281002 · outbound

This paper cites Improving semi-supervised federated learning by reducing the gradient diversity of models,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Improving semi-supervised federated learning by reducing the gradient diversity of models,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.402467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.824130Z digest=sha256:d3c1d614ed12573105a14760f7f88573267de32d481f2bc797c5421a2720101a

Observation 8172724e-4678-4093-8439-e9b8274d2e50 · outbound

This paper cites FedCon: A Contrastive Framework for Federated Semi-Supervised Learning.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things FedCon: A Contrastive Framework for Federated Semi-Supervised Learning

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-15T22:42:26.829101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:42:26.829101Z digest=sha256:c408f08b2491cc04c7ca2a987d0e3a17d89ca10df70d1bc03eae6a6185dc81e3

Observation bb7e5c6d-f29b-471f-812b-f7c9659d5f73 · outbound

This paper cites A simple frame- work for contrastive learning of visual representations,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things A simple frame- work for contrastive learning of visual representations,

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-15T22:42:26.834302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:42:26.834302Z digest=sha256:4bf7387db1582702b1ecd6f44ac018988bb1009bd7ff39c940b5673caefbede4

Observation 7dc25a2e-48a8-4486-a37d-197ab80840d7 · outbound

This paper cites Bootstrap your own latent-a new approach to self-supervised learning,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Bootstrap your own latent-a new approach to self-supervised learning,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.373736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.839034Z digest=sha256:de53a74c4fb12fbdc4af7d81c33935e99c528b5ee38b2daa34215800767d2c86

Observation f64546ab-d214-4ddc-a3aa-5ce5a6cdcbf2 · outbound

This paper cites Perfect Alignment May be Poisonous to Graph Contrastive Learning.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Perfect Alignment May be Poisonous to Graph Contrastive Learning

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-08-15T22:42:26.994555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.843572Z digest=sha256:8625932871df6d38e8310afae9c229e74e209887685cf3922605aafe297ae717

Observation 2a5aa01a-5648-4b52-8f57-685ef96c2c1d · outbound

This paper cites SimCSE: Simple Contrastive Learning of Sentence Embeddings.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things SimCSE: Simple Contrastive Learning of Sentence Embeddings

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-15T22:42:26.848421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:42:26.848421Z digest=sha256:5909d1f3168a96ebdaf665763a9da9f781ac2fe626c717820202fa13d0d4da7e

Observation ee644ab4-9e90-499c-bd80-a23701dc206e · outbound

This paper cites A detailed analysis of the kdd cup 99 data set,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things A detailed analysis of the kdd cup 99 data set,

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-15T22:42:26.853512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:42:26.853512Z digest=sha256:c356083b07572f56205af874fdbea5f2cbae5a7a409d015ae622df0402dc55c5

Observation 8cf49843-fb85-482e-9ae5-3e7e993c43fd · outbound

This paper cites A smart anomaly-based intrusion detection system for the internet of things (iot) network using gwo–pso–rf model,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things A smart anomaly-based intrusion detection system for the internet of things (iot) network using gwo–pso–rf model,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.343065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.857986Z digest=sha256:9c651140f511402e8a8750fe293d43375d8dcceda2fadf7acd16c3355bdaf2dd

Observation 662a5ae1-dfb3-4d3f-820f-920cec1e6339 · outbound

This paper cites Machine learning-driven intru- sion detection for contiki-ng-based iot networks exposed to nsl-kdd dataset,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Machine learning-driven intru- sion detection for contiki-ng-based iot networks exposed to nsl-kdd dataset,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.326801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.862317Z digest=sha256:b0c97b82dc1f01c9a017a72e5d03a1db710332f8f0ab8f1bdb63e8fe5140b709

Observation dcaa01e1-1dc8-4332-b8d4-7616eb7d8032 · outbound

This paper cites Anomaly-based intrusion detection system for iot application,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Anomaly-based intrusion detection system for iot application,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.303323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.866775Z digest=sha256:b560698196bff27d3f5260c0e6faa25ab79ae952e1e2b9860401fad2dc2e7802

Observation ae08323b-e5f0-457d-a455-9aa3a61d1fa9 · outbound

This paper cites Iot intrusion detection using machine learning with a novel high performing feature selection method,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Iot intrusion detection using machine learning with a novel high performing feature selection method,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.284664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.872278Z digest=sha256:655b03790d2b4c9122ab7209b921b2dc4fe4127a1c168a066778dc19eb18f19d

Observation 7a91cf87-1d96-415b-b6f0-a0023dd175a1 · outbound

This paper cites Uids: a unified intrusion detection system for iot environment,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Uids: a unified intrusion detection system for iot environment,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.267298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.876955Z digest=sha256:5def6ae92646482416b040c9c3252b75f575a21d4ed21bf4824d23849a413d66

Observation d04008bc-cdfc-465f-8b1e-52648b8ada24 · outbound

This paper cites Momentum contrast for unsupervised visual representation learning,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Momentum contrast for unsupervised visual representation learning,

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-15T22:42:26.882665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:42:26.882665Z digest=sha256:4402f6ab90652fc6e50d22b0f5b7ed9bb9ca478ba7a45b5c8d46158a34ac5e39

Observation 79c8e883-ecc8-4ef7-a239-47dbfef29012 · outbound

This paper cites Visualizing data using t-sne.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Visualizing data using t-sne

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-15T22:42:26.887438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:42:26.887438Z digest=sha256:17ec950b6814da252935928a5d63f77c07924f5371fe9d94e6f236524d6cf8d2

Observation 1eb0790e-1081-4d20-84e6-a065c30ff12e · outbound

This paper cites Temporal ensembling for semi-supervised learning,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Temporal ensembling for semi-supervised learning,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.230023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.891997Z digest=sha256:53e64a07b223893a6bb3a4deb5cb7ec5f04db152fb268650ccca6b87916f1156

Observation d879e53e-b40d-41c0-a706-b2bc8403afa3 · outbound

This paper cites On convergence of fedprox: Local dissimilarity invariant bounds, non-smoothness and beyond,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things On convergence of fedprox: Local dissimilarity invariant bounds, non-smoothness and beyond,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.211287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.896536Z digest=sha256:b238404e1e2a737a198766378eef3d1e9e81bf173b1d627eae5098967eb911e6

Observation ae937533-3284-4f50-b7df-a06d2b42d2f4 · outbound

This paper cites Intrusion detection system for nsl-kdd dataset using convolutional neural networks,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Intrusion detection system for nsl-kdd dataset using convolutional neural networks,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.191304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.901402Z digest=sha256:a641b3576316785f27fd77ffc9ae9822def5f00c18751f776606e944d7ec5124

Observation e251b527-dec9-4b51-b50c-e111c3fa515f · outbound

This paper cites A soft actor-critic reinforcement learning algorithm for network intrusion detection,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things A soft actor-critic reinforcement learning algorithm for network intrusion detection,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.172727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.906049Z digest=sha256:f4981eac817704a620085de9c8e0df97ffbda6f7b99b54d67d5506583245cd1d

Observation 38561716-3d10-4f5c-9535-f4e3db34506d · outbound

This paper cites Gan augmen- tation to deal with imbalance in imaging-based intrusion detection,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Gan augmen- tation to deal with imbalance in imaging-based intrusion detection,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.154221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.912084Z digest=sha256:c3a628c4a3ba417cc66f8eb5f5c4071bcd5fc484c4b8266c77b182f03629a99d

Observation cd128543-e521-4d80-ab5f-da4c29083ce9 · outbound

This paper cites A two stage lightweight approach for intrusion detection in internet of things,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things A two stage lightweight approach for intrusion detection in internet of things,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.138204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.916774Z digest=sha256:a5ded952900e3dc36665b02767570968c1ca711ee96a2fe84ebe6208115ea21e

Observation 1d91f054-a643-4ab2-875d-63282f0505a6 · outbound

This paper cites Optimized intrusion detection in iot and fog computing using ensemble learning and advanced feature selection,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things Optimized intrusion detection in iot and fog computing using ensemble learning and advanced feature selection,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.122030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.922201Z digest=sha256:a5bd717479f5234b502cdff69ab381bc7bcc75422600c184ad87efb0958ad8ef

Observation f20f4d5b-5c67-443b-b0e2-f58787d0a418 · outbound

This paper cites A multiscale intrusion detection system based on pyramid depthwise separable convolution neural network,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things A multiscale intrusion detection system based on pyramid depthwise separable convolution neural network,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.076250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.926886Z digest=sha256:2fcc3bca75a84a459b681432f85b20ac5a412d493dbb88aadcf2e521c7ce5436

Observation 6ae0d931-8146-4c40-8cde-18d5aedec0da · outbound

This paper cites A deep learning approach for intrusion detection systems in cloud computing environments,.

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things A deep learning approach for intrusion detection systems in cloud computing environments,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:42:27.059377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T22:42:26.931338Z digest=sha256:93c91d3f040641b81d02280fca275986ebcb79dd28c5b3ea3b55291a8ad8bdfb

Pith citing papers

No inbound Pith citation observations are available.