Paper Citation Record · LEDGER

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection

As of 20 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 1 inbound Pith citation observation for arXiv:2412.19830.

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

pith.paper-citation-record.v1
2412.19830 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:30:13.860530Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:50:59.882257Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-16T04:50:59.942260Z

Reference resolution

32 of 32 outbound references displayed

verified exact1
verified fuzzy20
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5a663f88-514e-442d-b9a9-f23640e99fc3 · outbound

This paper cites Internet of things (iot)—statistics & facts,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Internet of things (iot)—statistics & facts,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.473615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8471fc77-42a8-4c54-ba89-bc7e9b813d56 · outbound

This paper cites RAG based Question-Answering for Contextual Response Prediction System.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection RAG based Question-Answering for Contextual Response Prediction System

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T11:30:13.704000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c90db96-a34f-4763-a788-d4ebaab9d654 · outbound

This paper cites Improving language models by retrieving from trillions of tokens,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Improving language models by retrieving from trillions of tokens,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.457321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ec1b7349-14cb-4d9d-94eb-b7ec208e95d2 · outbound

This paper cites Atlas: Few-shot learning with retrieval augmented language models,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Atlas: Few-shot learning with retrieval augmented language models,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.440472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 55f5650f-59fa-44cd-846f-59af8c971b84 · outbound

This paper cites Retrieval- augmented generation for knowledge-intensive nlp tasks,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Retrieval- augmented generation for knowledge-intensive nlp tasks,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T11:30:13.720038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c6a9bd0-3c4e-40b2-aa69-8424484b0d2f · outbound

This paper cites Generalization through Memorization: Nearest Neighbor Language Models.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Generalization through Memorization: Nearest Neighbor Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T11:30:13.725097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 259ccb4c-0a95-4a78-a581-c588a607aa05 · outbound

This paper cites Retrieval-Augmented Multimodal Language Modeling.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Retrieval-Augmented Multimodal Language Modeling

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T11:30:13.730797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 324b3d1e-32f0-46d5-af59-df79a6a2eaec · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T11:30:13.735536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 789f776f-22be-477e-9339-ed205286b253 · outbound

This paper cites Edge-iiotset: A new comprehensive realistic cyber security dataset of iot and iiot applications for centralized and federated learning,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Edge-iiotset: A new comprehensive realistic cyber security dataset of iot and iiot applications for centralized and federated learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.394967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8b61ad6b-befd-48cd-a54f-a4d614c5ea03 · outbound

This paper cites F-bids: Federated-blending based intrusion detection system,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection F-bids: Federated-blending based intrusion detection system,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.376169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b32d3156-2b7e-4c07-83e8-441b162df2ac · outbound

This paper cites An automatic and efficient malware traffic classification method for secure internet of things,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection An automatic and efficient malware traffic classification method for secure internet of things,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.358714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d2101d52-91a2-4c36-90fe-9b74e1a492dd · outbound

This paper cites 2df-ids: Decentralized and differentially private federated learning-based intrusion detection system for industrial iot,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection 2df-ids: Decentralized and differentially private federated learning-based intrusion detection system for industrial iot,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.341848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 26799f4c-9d9a-4949-a868-1d80e2153c6d · outbound

This paper cites A deep learning integrated blockchain framework for securing industrial iot,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection A deep learning integrated blockchain framework for securing industrial iot,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.319933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7fe7be24-10dd-4f0b-ace9-8a03c2c71a61 · outbound

This paper cites Felids: Federated learning-based intrusion detection system for agricultural internet of things,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Felids: Federated learning-based intrusion detection system for agricultural internet of things,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.299473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 162b447e-8b5d-4d4f-be30-59c58fac461d · outbound

This paper cites Deepak-iot: An effective deep learning model for cyberattack detection in iot networks,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Deepak-iot: An effective deep learning model for cyberattack detection in iot networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.282970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8ee45219-4229-490a-b839-48b1bac5b174 · outbound

This paper cites A hybrid cnn- lstm model for iiot edge privacy-aware intrusion detection,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection A hybrid cnn- lstm model for iiot edge privacy-aware intrusion detection,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.266752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 921c820b-c9ff-4b9a-be00-7bdeca2389f6 · outbound

This paper cites Generative ai for cyber threat-hunting in 6g-enabled iot networks,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Generative ai for cyber threat-hunting in 6g-enabled iot networks,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.250105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c7741b22-d53c-4b69-8cee-e1d6d0ea662f · outbound

This paper cites Revolutionizing cyber threat detection with large language models: A privacy-preserving bert- based lightweight model for iot/iiot devices,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Revolutionizing cyber threat detection with large language models: A privacy-preserving bert- based lightweight model for iot/iiot devices,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.232795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6f64a462-cba6-405b-8db0-d699e506131a · outbound

This paper cites Iot-llm: Enhancing real- world iot task reasoning with large language models,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Iot-llm: Enhancing real- world iot task reasoning with large language models,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T11:30:13.790981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23d997f4-7278-4ccf-8ca5-237d507bbbb7 · outbound

This paper cites Penetrative ai: Making llms comprehend the physical world,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Penetrative ai: Making llms comprehend the physical world,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T11:30:13.795589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5390954d-e5b9-45a3-89dc-4b8c6589d8a3 · outbound

This paper cites IoT-LM: Large Multisensory Language Models for the Internet of Things.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection IoT-LM: Large Multisensory Language Models for the Internet of Things

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T11:30:13.800029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1589ea16-d55e-40f6-94e1-555bed5a89a9 · outbound

This paper cites Efficient Prompting for LLM-based Generative Internet of Things.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Efficient Prompting for LLM-based Generative Internet of Things

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T11:30:13.805537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca1d02ff-796a-4e5e-aa19-374bdae07624 · outbound

This paper cites When IoT Meet LLMs: Applications and Challenges.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection When IoT Meet LLMs: Applications and Challenges

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T11:30:13.810621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation febf3397-6652-4ee5-951a-15a888ab2ab4 · outbound

This paper cites Pllm-cs: Pre-trained large language model (llm) for cyber threat detection in satellite networks,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Pllm-cs: Pre-trained large language model (llm) for cyber threat detection in satellite networks,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.204728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3ffb8b27-ad62-4c18-bdf0-02cfbedaaf71 · outbound

This paper cites Detecting command injection vulnerabilities in linux- based embedded firmware with llm-based taint analysis of library functions,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Detecting command injection vulnerabilities in linux- based embedded firmware with llm-based taint analysis of library functions,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.187632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8e189384-342d-4a96-a9b6-63f4f65d0165 · outbound

This paper cites Can- bert do it? controller area network intrusion detection system based on bert language model,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Can- bert do it? controller area network intrusion detection system based on bert language model,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.172053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation aa0fbc79-07c3-47b2-9259-dd993f117ec9 · outbound

This paper cites Malbert: Malware detection using bidirectional encoder representations from transformers,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Malbert: Malware detection using bidirectional encoder representations from transformers,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.157237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b02bd977-9de3-428c-9abe-1f1733ab3936 · outbound

This paper cites Bert-log: Anomaly detection for system logs based on pre-trained language model,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Bert-log: Anomaly detection for system logs based on pre-trained language model,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T11:30:13.838951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7368f821-d0d2-4061-a1b6-c691e39fec6e · outbound

This paper cites Efficient Federated Intrusion Detection in 5G ecosystem using optimized BERT-based model.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Efficient Federated Intrusion Detection in 5G ecosystem using optimized BERT-based model

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-11T11:30:13.908371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8a99a3ae-cc86-4c44-8de0-a43fc8e7416a · outbound

This paper cites Pac-gpt: A novel approach to generating synthetic network traffic with gpt-3,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Pac-gpt: A novel approach to generating synthetic network traffic with gpt-3,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.133174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0ff35a7d-7bd8-4423-82fb-4367eeb2e6bd · outbound

This paper cites Cybert: Contextu- alized embeddings for the cybersecurity domain,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection Cybert: Contextu- alized embeddings for the cybersecurity domain,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.117566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 40409ca5-069a-4fe8-ad5a-09e9e3803046 · outbound

This paper cites A lightweight iot intrusion detection model based on improved bert-of-theseus,.

A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection A lightweight iot intrusion detection model based on improved bert-of-theseus,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:30:14.101739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

Observation 39260d82-b304-44bc-8a72-f4250e0e2008 · inbound

LLM-Based Threat Detection and Prevention Framework for IoT Ecosystems cites this paper.

LLM-Based Threat Detection and Prevention Framework for IoT Ecosystems A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-16T04:50:59.948178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.