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Paper Citation Record · LEDGER

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus

As of 23 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2603.15344.

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

pith.paper-citation-record.v1
2603.15344 v2

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-14T20:30:10.166113Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

48 of 48 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved47
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

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Outbound references

Observation 1a889c67-b237-465d-947e-e8df6550e796 · outbound

This paper cites An empirical study of deep learning-based ss7 attack detection,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus An empirical study of deep learning-based ss7 attack detection,

Reference 3

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Observation a7e379d6-61d8-45ce-beef-f959aa91adcd · outbound

This paper cites Diameter Security: An Auditor’s Viewpoint,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Diameter Security: An Auditor’s Viewpoint,

Reference 4

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Observation 8add5338-6561-43c6-9e5e-2a6626cda58f · outbound

This paper cites Protocol Misuse in Mobile Networks: Real-World Case Studies and Security Risks.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Protocol Misuse in Mobile Networks: Real-World Case Studies and Security Risks

Reference 5

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Observation 84bec248-f823-4aa3-a1b5-726feca09665 · outbound

This paper cites Enea Adaptive Signalling Firewall.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Enea Adaptive Signalling Firewall

Reference 6

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Observation 72df43dc-e732-4a1c-8e1c-361a55a80034 · outbound

This paper cites Network Intrusion Detection with Limited Labeled Data Using Self-supervision.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Network Intrusion Detection with Limited Labeled Data Using Self-supervision

Reference 7

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Observation fc54b8a4-9e97-468d-af2a-62a746729b11 · outbound

This paper cites Unsupervised Machine Learning Methods for Anomaly Detection in Network Packets,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Unsupervised Machine Learning Methods for Anomaly Detection in Network Packets,

Reference 8

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Observation 799cc195-577d-47cb-a17f-7b23c19d4a9d · outbound

This paper cites Survey of intrusion detection systems: techniques, datasets and challenges,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Survey of intrusion detection systems: techniques, datasets and challenges,

Reference 9

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Observation fc9d001f-0a27-4852-94e1-984865b83392 · outbound

This paper cites Overview on Intrusion Detection Systems for Computers Networking Security,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Overview on Intrusion Detection Systems for Computers Networking Security,

Reference 10

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Observation 4503239c-2beb-424d-8a6a-175e61bb9ac8 · outbound

This paper cites A survey of network-based intrusion detection data sets,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus A survey of network-based intrusion detection data sets,

Reference 11

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Observation 1c13249c-cf9f-4c38-b4c8-3123607a61e9 · outbound

This paper cites Unsupervised anomaly detection algorithms on real-world data: how many do we need?.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Unsupervised anomaly detection algorithms on real-world data: how many do we need?

Reference 12

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Observation 4f6de1bb-ebba-4cd8-b892-cd0b0345dceb · outbound

This paper cites Rule-based anomaly detection model with stateful correlation enhancing mobile network security.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Rule-based anomaly detection model with stateful correlation enhancing mobile network security

Reference 13

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Observation ecaab8d5-b38a-4cf3-89c7-dc9c538f045b · outbound

This paper cites Learning from what we know: How to perform vulnerability prediction using noisy historical data,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Learning from what we know: How to perform vulnerability prediction using noisy historical data,

Reference 14

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source=pdf_text observed=2026-07-14T20:30:10.166113Z digest=sha256:1e8708a48a7dac052a8c00463e4e62c96820800be5f5fb5dcee65853727a32e5

Observation a01ea820-1fa3-4dec-a9d8-76853123c350 · outbound

This paper cites Learning from What We Know: How to Perform Vulnerability Prediction using Noisy Historical Data.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Learning from What We Know: How to Perform Vulnerability Prediction using Noisy Historical Data

Reference 15

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Observation 84a1348a-b714-44ce-8e17-59c104824ff6 · outbound

This paper cites A cnn-based semi-supervised learning approach for the detection of ss7 attacks,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus A cnn-based semi-supervised learning approach for the detection of ss7 attacks,

Reference 16

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Observation 22e21322-6369-4fa7-b983-e39848d7163e · outbound

This paper cites Analysis and application of ss7 core net- work threat detection,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Analysis and application of ss7 core net- work threat detection,

Reference 17

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Observation 491cd9e0-4156-4a47-b4dc-f93fa5119538 · outbound

This paper cites Attacks to mobile networks using ss7 vulnerabilities: a real traffic analysis,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Attacks to mobile networks using ss7 vulnerabilities: a real traffic analysis,

Reference 18

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Observation 6afd9468-6f92-4903-966c-5ee32dfe9a04 · outbound

This paper cites Survey on threats and attacks on mobile networks,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Survey on threats and attacks on mobile networks,

Reference 19

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Observation b4d18d56-159a-4eb0-9102-ee07f3bad83c · outbound

This paper cites Security Penetration Test Framework for the Diameter Protocol.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Security Penetration Test Framework for the Diameter Protocol

Reference 20

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Observation 42849c76-6f3b-40a4-9ac2-60240a581e3e · outbound

This paper cites Diameter security: An auditor’s viewpoint,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Diameter security: An auditor’s viewpoint,

Reference 21

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Observation 5d5820ee-c996-4da4-ad9b-24d0c201c7dc · outbound

This paper cites Device-centric detection and mitigation of diameter signaling attacks against mobile core,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Device-centric detection and mitigation of diameter signaling attacks against mobile core,

Reference 22

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Observation e78bbba4-d689-4b12-a351-a0e8e50e4747 · outbound

This paper cites User location tracking attacks for lte networks using the interworking functionality,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus User location tracking attacks for lte networks using the interworking functionality,

Reference 23

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Observation 7e0e067e-fed6-4387-a189-a4cc0059e42c · outbound

This paper cites Real threats using gtp protocol and countermeasures on a 4g mobile grid computing environment,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Real threats using gtp protocol and countermeasures on a 4g mobile grid computing environment,

Reference 24

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Observation c53e623a-c777-4b9e-bb7d-f4aecb32d427 · outbound

This paper cites Detecting iot botnet in 5g core network using machine learning,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Detecting iot botnet in 5g core network using machine learning,

Reference 25

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Observation 11408828-9023-4d83-a80d-9608da38a27c · outbound

This paper cites Machine learning based signaling ddos detection system for 5g stand alone core network,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Machine learning based signaling ddos detection system for 5g stand alone core network,

Reference 26

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Observation 13aa8773-be40-4911-aa80-b6106bec1f54 · outbound

This paper cites Sdn- based gtp-u traffic analysis for 5g networks,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Sdn- based gtp-u traffic analysis for 5g networks,

Reference 27

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Observation fded1e77-52ba-403d-ae43-fdf21a202047 · outbound

This paper cites On the coupling between vulnerabilities and llm-generated mutants: A study on vul4j dataset,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus On the coupling between vulnerabilities and llm-generated mutants: A study on vul4j dataset,

Reference 28

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Observation 74a5ae27-d391-4982-b882-e2ff08e27b83 · outbound

This paper cites Q.713:Signalling connection control part formats and codes.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Q.713:Signalling connection control part formats and codes

Reference 29

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Observation 0b6fb159-c855-4299-8995-4fe568fe1031 · outbound

This paper cites Specification # 29.002.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Specification # 29.002

Reference 30

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Observation 3a7da677-f733-4b29-9f2a-4e3c91af1573 · outbound

This paper cites an unresolved cited work.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Unresolved cited work

Reference 31

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Observation 72985614-4778-45cf-98e2-76948792c891 · outbound

This paper cites Diameter Base Protocol,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Diameter Base Protocol,

Reference 32

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Observation e51c65f0-e04e-48b5-8af4-1c2e20e923b1 · outbound

This paper cites ETSI TS 129 272 V17.2.0 (2022-05) Universal Mobile Telecommunications.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus ETSI TS 129 272 V17.2.0 (2022-05) Universal Mobile Telecommunications

Reference 33

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Observation 0714e8cc-59e0-4bfc-8665-9c842daf4f38 · outbound

This paper cites Signalling Security in Telecom SS7/Diameter/5G|ENISA,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Signalling Security in Telecom SS7/Diameter/5G|ENISA,

Reference 34

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Observation e96c2861-2e05-4370-9986-ee31cfa1994c · outbound

This paper cites Available: https://www.enisa.europa.eu/publications/sig nalling-security-in-telecom-ss7-diameter-5g.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Available: https://www.enisa.europa.eu/publications/sig nalling-security-in-telecom-ss7-diameter-5g

Reference 35

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Observation 37300e48-7061-4f24-8566-49ac83b6b734 · outbound

This paper cites Q.704:Signalling network functions and messages.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Q.704:Signalling network functions and messages

Reference 36

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Observation 007462df-3e6a-44a8-b76c-07de2e12f4a5 · outbound

This paper cites Specification # 23.002.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Specification # 23.002

Reference 37

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Observation d5696dd4-b777-44b4-a8aa-97ebd94f40f8 · outbound

This paper cites Q.773:Transaction capabilities formats and encoding.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Q.773:Transaction capabilities formats and encoding

Reference 38

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source=pdf_text observed=2026-07-14T20:30:10.166113Z digest=sha256:2ec1ca4666393c4f78552d9fb0c1ca6885ca35d64ba1a66688d631165e6d75c9

Observation 095ad33e-6deb-4a3f-bd05-38b6a4bc29cf · outbound

This paper cites ETSI TS 129 274.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus ETSI TS 129 274

Reference 39

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This paper cites IR.88 EPS Roaming Guidelines Version 29.0,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus IR.88 EPS Roaming Guidelines Version 29.0,

Reference 40

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Observation e78c9825-2000-4fab-897b-d86f9ea1e44a · outbound

This paper cites Communications Security, Reliability, and Interoperability Council VI|Federal Communications Commission.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Communications Security, Reliability, and Interoperability Council VI|Federal Communications Commission

Reference 41

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This paper cites ETSI TS 129 281 V17.4.0 (2022-10) Universal Mobile Telecommunications.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus ETSI TS 129 281 V17.4.0 (2022-10) Universal Mobile Telecommunications

Reference 42

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Observation 69171b32-68e7-4138-9b4c-5549bad47cb3 · outbound

This paper cites an unresolved cited work.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Unresolved cited work

Reference 43

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This paper cites Enabling efficient assertion inference,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Enabling efficient assertion inference,

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Observation d5e9069b-9370-407c-965a-6954d4a45e72 · outbound

This paper cites Bge m3-embedding: Multi-lingual, multi-functionality, multi-granularity text embeddings through self-knowledge distillation,.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Bge m3-embedding: Multi-lingual, multi-functionality, multi-granularity text embeddings through self-knowledge distillation,

Reference 45

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Observation 5d62bea3-272d-4dc8-886f-7b8df74bb368 · outbound

This paper cites Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents

Reference 46

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Observation ec1c813c-fdc8-432e-91bf-561794b9e9c0 · outbound

This paper cites Introducing Nomic Embed: A Truly Open Embedding Model.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Introducing Nomic Embed: A Truly Open Embedding Model

Reference 47

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Observation d25d94a9-4970-4ad0-a6d8-fa4315b60298 · outbound

This paper cites snowflake-arctic-embed2:568m.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus snowflake-arctic-embed2:568m

Reference 48

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Observation 5232d542-003d-44c6-b39e-741d34e4cfc6 · outbound

This paper cites Snowflake launches text-embedding model for retrieval use cases.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus Snowflake launches text-embedding model for retrieval use cases

Reference 49

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Observation d59c70b2-4d6c-475e-80ee-9866671586b0 · outbound

This paper cites unclemusclez/jina-embeddings-v2-base-code:q8.

Unsupervised Cross-Protocol Anomaly Analysis in Mobile Core Networks via Multi-Embedding Models Consensus unclemusclez/jina-embeddings-v2-base-code:q8

Reference 50

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