PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models | Paper Citation Record

Observation 52eebfe3-609c-4c74-b422-9fa2d6063a36 · outbound

This paper cites Fighting against phishing attacks: state of the art and future challenges,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Fighting against phishing attacks: state of the art and future challenges,

Reference 1

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Observation dc61b9cc-ef0a-4db4-a8b9-983fadd7dd60 · outbound

This paper cites Apwg 2024 phishing report,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Apwg 2024 phishing report,

Reference 2

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Observation 094b0d39-da07-4b02-be10-8ad344a71100 · outbound

This paper cites A systematic literature review on phishing email detection using natural language processing techniques,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models A systematic literature review on phishing email detection using natural language processing techniques,

Reference 3

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Observation 795c7db4-9b49-4ba4-a0af-9dc9a342f6ef · outbound

This paper cites Applying machine learn- ing and natural language processing to detect phishing email,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Applying machine learn- ing and natural language processing to detect phishing email,

Reference 4

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Observation 76bd6ce2-4460-4f49-9fb0-42ef6ed91a85 · outbound

This paper cites ChatSpamDetector: Leveraging Large Language Models for Effective Phishing Email Detection.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models ChatSpamDetector: Leveraging Large Language Models for Effective Phishing Email Detection

Reference 5

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This paper cites A survey of large language models for cyber threat detection,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models A survey of large language models for cyber threat detection,

Reference 6

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Observation 4db3bd31-35db-4b6a-9012-678d8486b5cb · outbound

This paper cites Towards security threats of deep learning systems: A survey,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Towards security threats of deep learning systems: A survey,

Reference 7

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This paper cites Privacy engineering in the wild: Understanding the practitioners’ mindset, organizational aspects, and current practices,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Privacy engineering in the wild: Understanding the practitioners’ mindset, organizational aspects, and current practices,

Reference 8

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Observation a2857ce2-7dc5-493a-bc18-dbcd2d562449 · outbound

This paper cites Sok: a comprehensive reexamination of phishing research from the security perspective,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Sok: a comprehensive reexamination of phishing research from the security perspective,

Reference 9

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Observation 8d43f7ec-2517-4d07-b131-4faf3e9822bf · outbound

This paper cites Phish- ing email detection using natural language processing techniques: a literature survey,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Phish- ing email detection using natural language processing techniques: a literature survey,

Reference 10

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Observation 6b2786e1-129e-4272-b169-5d32a7ad72d5 · outbound

This paper cites Text Data Augmentation: Towards better detection of spear-phishing emails.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Text Data Augmentation: Towards better detection of spear-phishing emails

Reference 11

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Observation 4532749d-1862-4a17-91a5-87f06b3adf5b · outbound

This paper cites Ad- versarial sampling attacks against phishing detection,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Ad- versarial sampling attacks against phishing detection,

Reference 12

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Observation 08deb28f-f7eb-4f8b-a391-e50e17bdc346 · outbound

This paper cites Enhancing detection of arabic social spam using data augmentation and machine learning,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Enhancing detection of arabic social spam using data augmentation and machine learning,

Reference 13

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Observation 51c34854-171b-4835-b823-65d4984b24cb · outbound

This paper cites Data augmenta- tion methods for enhancing robustness in text classifica- tion tasks,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Data augmenta- tion methods for enhancing robustness in text classifica- tion tasks,

Reference 14

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Observation 58ae4c0d-50c6-4424-93a8-d733fcd8c317 · outbound

This paper cites Adversarial examples generation method for chinese text classification,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Adversarial examples generation method for chinese text classification,

Reference 15

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Observation 994e753e-8a57-405f-a28c-7f4d72b7cac0 · outbound

This paper cites Rule-based adversarial sample generation for text classification,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Rule-based adversarial sample generation for text classification,

Reference 16

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Observation 3c9e0dab-8486-4e1e-86cd-1b7ec442b2de · outbound

This paper cites An empirical survey of data augmentation for limited data learning in nlp,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models An empirical survey of data augmentation for limited data learning in nlp,

Reference 17

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Observation 4fc64b81-a4b4-4c6e-992d-0518752df25b · outbound

This paper cites Adversarial robustness of phishing email detection models,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Adversarial robustness of phishing email detection models,

Reference 18

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Observation 8bc3622b-6998-4367-a3fe-30691ec5d7c2 · outbound

This paper cites Data augmentation in classification and segmentation: A survey and new strategies,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Data augmentation in classification and segmentation: A survey and new strategies,

Reference 19

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Observation 12be2dc7-9fc1-4369-b474-3602008268e5 · outbound

This paper cites Analysis and prevention of ai-based phishing email attacks,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Analysis and prevention of ai-based phishing email attacks,

Reference 20

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Observation 81b90e9d-778d-4742-bf91-c86c6facde1a · outbound

This paper cites Phishing or not phishing? a survey on the detection of phishing websites,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Phishing or not phishing? a survey on the detection of phishing websites,

Reference 21

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Observation 806280cb-86dd-4b30-bca0-a3ebccd5b5a8 · outbound

This paper cites Devising and Detecting Phishing: Large Language Models vs. Smaller Human Models.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Devising and Detecting Phishing: Large Language Models vs. Smaller Human Models

Reference 22

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Observation c3ca37bd-1410-4c7a-9780-79451661701b · outbound

This paper cites Lateral Phishing With Large Language Models: A Large Organization Comparative Study.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Lateral Phishing With Large Language Models: A Large Organization Comparative Study

Reference 23

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Observation e50ce6e2-821a-46c2-9c0b-490dd6602de2 · outbound

This paper cites A survey on explainable anomaly detection,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models A survey on explainable anomaly detection,

Reference 24

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Observation 5da470cf-63f7-485e-a4b4-27472e435a90 · outbound

This paper cites Detection of ai-generated emails-a case study,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Detection of ai-generated emails-a case study,

Reference 25

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This paper cites Phishing and social engineering attack prevention with llms,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Phishing and social engineering attack prevention with llms,

Reference 26

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PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Unresolved cited work

Reference 27

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This paper cites Gemini: A Family of Highly Capable Multimodal Models.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Gemini: A Family of Highly Capable Multimodal Models

Reference 28

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Observation 86c9c4b2-1b95-4993-bf66-c7394fb5a341 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models LoRA: Low-Rank Adaptation of Large Language Models

Reference 29

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This paper cites Bi-lstm model to increase accuracy in text classification: Combining word2vec cnn and attention mechanism,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Bi-lstm model to increase accuracy in text classification: Combining word2vec cnn and attention mechanism,

Reference 30

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Observation 80a51a50-155a-4745-b468-ae2c27c94391 · outbound

This paper cites An Explainable Transformer-based Model for Phishing Email Detection: A Large Language Model Approach.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models An Explainable Transformer-based Model for Phishing Email Detection: A Large Language Model Approach

Reference 31

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Observation 4a683be3-42d8-44a4-837f-40c904c3fb68 · outbound

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PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Chain-of-thought prompting elicits reasoning in large language models,

Reference 32

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Observation 038dcbc6-dfec-490d-8903-2cb65b719335 · outbound

This paper cites Isolation forest,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Isolation forest,

Reference 33

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This paper cites Latent dirichlet allocation,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Latent dirichlet allocation,

Reference 34

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Observation d4a16c91-b51f-4702-a5bd-db28849b363b · outbound

This paper cites The science of persuasion,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models The science of persuasion,

Reference 35

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This paper cites Concept induction: Analyzing unstructured text with high-level concepts using lloom,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Concept induction: Analyzing unstructured text with high-level concepts using lloom,

Reference 36

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Observation 20741667-1779-4d82-b6e7-1887605950b3 · outbound

This paper cites The development and psychometric properties of liwc-22,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models The development and psychometric properties of liwc-22,

Reference 37

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Observation 6594b9b5-999f-4226-90b7-e7147e8acefc · outbound

This paper cites Optimizing semantic coherence in topic models,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Optimizing semantic coherence in topic models,

Reference 38

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Observation 1a9ea117-a2bc-4f22-ae75-8c9356fe60f4 · outbound

This paper cites Class-based n-gram models of natural language,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Class-based n-gram models of natural language,

Reference 39

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This paper cites Interpreting tf-idf term weights as making relevance decisions,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Interpreting tf-idf term weights as making relevance decisions,

Reference 40

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Observation 9b133c9a-c425-44a3-beca-b01e00ed3d90 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Explaining and Harnessing Adversarial Examples

Reference 41

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This paper cites Machine literature searching viii. operational criteria for designing information retrieval systems,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Machine literature searching viii. operational criteria for designing information retrieval systems,

Reference 42

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Observation 7d9e5658-1dc4-4084-bcfc-880bd47a00fa · outbound

This paper cites Iwspa phishing dataset,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Iwspa phishing dataset,

Reference 43

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Observation 1aad8c3b-6ba3-48d2-aae5-1b90177859ff · outbound

This paper cites Nazario phishing dataset,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Nazario phishing dataset,

Reference 44

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Observation 010805cb-29b1-435f-8468-c0068298df8f · outbound

This paper cites Miller smiles phishing dataset,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Miller smiles phishing dataset,

Reference 45

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Observation f7b7a90b-4904-4582-b955-56350f24548e · outbound

This paper cites Phish bowl phishing dataset,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Phish bowl phishing dataset,

Reference 46

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This paper cites Nigerian fraud dataset,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Nigerian fraud dataset,

Reference 47

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Observation e1836623-8c72-4a2a-abc7-c8fb779500c0 · outbound

This paper cites An improved transformer-based model for detecting phishing, spam and ham emails: A large language model approach,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models An improved transformer-based model for detecting phishing, spam and ham emails: A large language model approach,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:42.302181Z

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Observation 7144e5d8-9ce1-4c11-ac9a-185ae0f97100 · outbound

This paper cites The psychological meaning of words: Liwc and computerized text analysis methods,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models The psychological meaning of words: Liwc and computerized text analysis methods,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:42.284201Z

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Observation 1b6f42fe-f64d-44d0-bc52-6a7c56c1e160 · outbound

This paper cites Changing others’ beliefs online: Online comments’ persuasiveness,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Changing others’ beliefs online: Online comments’ persuasiveness,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:42.265494Z

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This paper cites Cognitive triaging of phishing attacks,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Cognitive triaging of phishing attacks,

Reference 51

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Observation 098a2e7b-b673-4821-beef-98e6c52dfa41 · outbound

This paper cites The development and psychometric properties of liwc2015,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models The development and psychometric properties of liwc2015,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:42.231202Z

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Observation f8eb5c3d-3cb5-488b-aa7f-4c70ee035436 · outbound

This paper cites InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective

Reference 53

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Observation 20668650-a631-44d9-b9fa-9a8db1d143e8 · outbound

This paper cites Generating nat- ural language adversarial examples through probability weighted word saliency,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Generating nat- ural language adversarial examples through probability weighted word saliency,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:42.214504Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f4bf9bb6-2251-4f7f-8c11-71b92cf0e99a · outbound

This paper cites Combating Adversarial Misspellings with Robust Word Recognition.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Combating Adversarial Misspellings with Robust Word Recognition

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-12T18:39:41.306847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86f85598-28a7-4237-b0df-d041620a112a · outbound

This paper cites Black-box generation of adversarial text sequences to evade deep learning classifiers,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Black-box generation of adversarial text sequences to evade deep learning classifiers,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:42.197184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1dbde074-7a50-4f6b-99ae-7efa81fc7f48 · outbound

This paper cites Chatgpt and a new academic reality: Arti- ficial intelligence-written research papers and the ethics of the large language models in scholarly publishing,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Chatgpt and a new academic reality: Arti- ficial intelligence-written research papers and the ethics of the large language models in scholarly publishing,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:42.179947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8c680be2-342f-403a-a74b-4a740335df54 · outbound

This paper cites Social engineering in cybersecurity: Effect mechanisms, human vulnerabilities and attack methods,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Social engineering in cybersecurity: Effect mechanisms, human vulnerabilities and attack methods,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:42.163516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4e498037-3c7e-48a9-917d-485cfcf4edb8 · outbound

This paper cites Udh: Universal deep hiding for steganography, water- marking, and light field messaging,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Udh: Universal deep hiding for steganography, water- marking, and light field messaging,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:42.146765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 953bcc34-2c45-4aae-8861-a482e637827c · outbound

This paper cites Towards adversarial phishing detection,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Towards adversarial phishing detection,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:42.130034Z

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Observation cb435f40-9737-4873-a9d9-a353caa279bf · outbound

This paper cites Hooked: A Real-World Study on QR Code Phishing.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Hooked: A Real-World Study on QR Code Phishing

Reference 61

Resolution: verified exact; local_arxiv, observed 2026-08-12T18:39:41.570766Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4a1c88b9-2786-4faa-9229-c014a8dbfae7 · outbound

This paper cites An image is worth a thousand toxic words: A metamorphic testing framework for content moderation software,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models An image is worth a thousand toxic words: A metamorphic testing framework for content moderation software,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:42.113311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a5d29b2f-5e2b-431c-87e2-442db2712b54 · outbound

This paper cites {KnowPhish}: Large lan- guage models meet multimodal knowledge graphs for enhancing {Reference-Based} phishing detection,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models {KnowPhish}: Large lan- guage models meet multimodal knowledge graphs for enhancing {Reference-Based} phishing detection,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:42.095491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f130d1d3-16cc-4651-ac58-609dfbab8fd9 · outbound

This paper cites From chatbots to phishbots?: Phishing scam generation in commercial large language models,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models From chatbots to phishbots?: Phishing scam generation in commercial large language models,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:42.077017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ff071e10-7593-484b-a28b-60f79d68adae · outbound

This paper cites Chatgpt’s security risks and benefits: of- fensive and defensive use-cases, mitigation measures, and future implications,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Chatgpt’s security risks and benefits: of- fensive and defensive use-cases, mitigation measures, and future implications,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:42.057344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d21a6dae-35de-42ab-a19f-5b801ba2af03 · outbound

This paper cites A survey on dataset quality in machine learning,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models A survey on dataset quality in machine learning,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:42.038508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8e6a8c87-880e-44e8-8279-27b1c42e91ae · outbound

This paper cites Generating optimal attack paths in generative adversarial phishing,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Generating optimal attack paths in generative adversarial phishing,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:42.020780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ca6f4505-373e-46a4-b538-1f22275790c0 · outbound

This paper cites Weaponizing data science for social engineering: Automated e2e spear phishing on twitter,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Weaponizing data science for social engineering: Automated e2e spear phishing on twitter,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:42.002936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e5e2031d-3ca6-420c-be97-b984434d745f · outbound

This paper cites Is bert really robust? a strong baseline for natural language attack on text classification and entailment,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Is bert really robust? a strong baseline for natural language attack on text classification and entailment,

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-12T18:39:41.380768Z

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Observation 1f4f1b29-d783-4968-a3bd-5f9b869bbe0e · outbound

This paper cites Social engineering in cybersecurity: The evolution of a concept,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Social engineering in cybersecurity: The evolution of a concept,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:41.975456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation aa3bcd12-4813-43b3-afe5-c31cb5cd805c · outbound

This paper cites Defining social engineer- ing in cybersecurity,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Defining social engineer- ing in cybersecurity,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:41.959531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2216b263-2f0c-47cd-8657-06460f1457d0 · outbound

This paper cites Email summarization to assist users in phishing iden- tification,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Email summarization to assist users in phishing iden- tification,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:41.942058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e5f25af4-262e-4669-95fa-3f6b8a1cc229 · outbound

This paper cites Email phishing and signal detection: How persuasion principles and personality influence response patterns and accuracy,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Email phishing and signal detection: How persuasion principles and personality influence response patterns and accuracy,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:41.922358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4a6da0a2-010d-4217-9c01-ca7f0fb10e2d · outbound

This paper cites Detection method of phish- ing email based on persuasion principle,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Detection method of phish- ing email based on persuasion principle,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:41.905775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2eec8388-374a-486a-8ef1-621b4f4666e6 · outbound

This paper cites Utilizing large language models with human feedback integration for generating dedicated warning for phishing emails,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Utilizing large language models with human feedback integration for generating dedicated warning for phishing emails,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:41.889090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5245d107-19be-4100-95f3-099899bfdf88 · outbound

This paper cites Digital Deception: Generative Artificial Intelligence in Social Engineering and Phishing.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Digital Deception: Generative Artificial Intelligence in Social Engineering and Phishing

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-12T18:39:41.419279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a1a05e6-5607-4f49-973d-b8445b6a248d · outbound

This paper cites Social engineering at- tacks: A survey,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Social engineering at- tacks: A survey,

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:41.872099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 74a0f2c4-e3cf-4a1b-8a91-ad495a96bcbc · outbound

This paper cites Ai2tale: An innovative information theory-based approach for learning to localize phishing attacks,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Ai2tale: An innovative information theory-based approach for learning to localize phishing attacks,

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:41.855218Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 03dee996-bbb4-4ca1-af87-3273fbd90921 · outbound

This paper cites Generative adversarial nets,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Generative adversarial nets,

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-12T18:39:41.435087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a78484e5-beec-42f1-9e1a-74dbd407442d · outbound

This paper cites Conditional Generative Adversarial Nets.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Conditional Generative Adversarial Nets

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-12T18:39:41.440306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8054ac3-3206-4fa8-b86b-8599eaeef13f · outbound

This paper cites an unresolved cited work.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Unresolved cited work

Reference 81

Resolution: unresolved; raw_fallback, observed 2026-08-12T18:39:41.827141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c98282c8-1aab-44c1-9715-e45de82ee1a7 · outbound

This paper cites Evaluating ChatGPT's Performance for Multilingual and Emoji-based Hate Speech Detection.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Evaluating ChatGPT's Performance for Multilingual and Emoji-based Hate Speech Detection

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-12T18:39:41.450816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 429f8a9e-6e80-4d63-88bb-9f217533fadf · outbound

This paper cites Is chatgpt better than human annotators? potential and limitations of chatgpt in explaining implicit hate speech,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Is chatgpt better than human annotators? potential and limitations of chatgpt in explaining implicit hate speech,

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:41.810918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bcb0d1f9-8ed2-41de-bd17-5c6149c80de8 · outbound

This paper cites Cross-validation methods,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Cross-validation methods,

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:39:41.792595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 29c487e1-ef66-4e23-a5ab-1d268dd5d915 · outbound

This paper cites Language models are unsupervised multitask learners,.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Language models are unsupervised multitask learners,

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-12T18:39:41.466730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33a439d9-b607-413c-bf89-039db150184a · outbound

This paper cites Nigerian.

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models Nigerian

Reference 86

Resolution: malformed identifier; raw_fallback, observed 2026-08-12T18:39:41.764849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers