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Phishing email is a serious cyber threat that tries to deceive users by sending false emails with the intention of stealing confidential information or causing financial harm.
Using feature selection and classification scheme for automating phishing email detection,
I. R. A. Hamid, J. Abawajy, T. Kim, · 2013
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Phishing dynamic evolving neural fuzzy framework for online detection zero-day phishing email,
A. Almomani, B. B. Gupta, T.-C. Wan, A. Altaher, S. Manickam, · 2013
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An intelligent classification model for phishing email detection,
A. Yasin, A. Abuhasan, · 2016
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” why should i trust you?” explaining the predictions of any classifier,
M. T. Ribeiro, S. Singh, C. Guestrin, · 2016
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Phishing detection method based on borderline-smote deep belief network,
J. Zhang, X. Li, · 2017
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Classifying phishing urls using recurrent neural networks,
A. C. Bahnsen, E. C. Bohorquez, S. Villegas, J. Vargas, F. A. González, · 2017
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Decoupled weight decay regularization,
I. Loshchilov, F. Hutter, · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding,
J. Devlin, M.-W. Chang, K. Lee, K. Toutanova, · 2018
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Metrics for explainable ai: Challenges and prospects,
R. R. Hoffman, S. T. Mueller, G. Klein, J. Litman, · 2018
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A machine learning approach towards phishing email detection,
N. Harikrishnan, R. Vinayakumar, K. Soman, · 2018
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Detection of online phishing email using dynamic evolving neural network based on reinforcement learning,
S. Smadi, N. Aslam, L. Zhang, · 2018
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Albert: A lite bert for self-supervised learning of language representations,
Z. Lan, M. Chen, S. Goodman, K. Gimpel, P. Sharma, R. Soricut, · 2019
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Roberta: A robustly optimized bert pretraining approach,
Y. Liu, M. Ott, N. Goyal, J. Du, M. Joshi, D. Chen, O. Levy, M. Lewis, L. Zettlemoyer, V. Stoyanov, · 2019
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Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter,
V. Sanh, L. Debut, J. Chaumond, T. Wolf, · 2019
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Explainable ai: A brief survey on history, research areas, approaches and challenges,
F. Xu, H. Uszkoreit, Y. Du, W. Fan, D. Zhao, J. Zhu, · 2019
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Phishing email detection using improved rcnn model with multilevel vectors and attention mechanism,
Y. Fang, C. Zhang, C. Huang, L. Liu, Y. Yang, · 2019
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Tinybert: Distilling bert for natural language understanding,
X. Jiao, Y. Yin, L. Shang, X. Jiang, X. Chen, L. Li, F. Wang, Q. Liu, · 2019
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Phishing web site detection using diverse machine learning algorithms,
A. Zamir, H. U. Khan, T. Iqbal, N. Yousaf, F. Aslam, A. Anjum, M. Hamdani, · 2020
Cited alongside, same era.
Catbert: Context-aware tiny bert for detecting social engineering emails,
Y. Lee, J. Saxe, R. Harang, · 2020
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Phishing email detection using natural language processing techniques: a literature survey,
S. Salloum, T. Gaber, S. Vadera, K. Shaalan, · 2021
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A comprehensive survey of ai-enabled phishing attacks detection techniques,
A. Basit, M. Zafar, X. Liu, A. R. Javed, Z. Jalil, K. Kifayat, · 2021
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Transformer in transformer,
K. Han, A. Xiao, E. Wu, J. Guo, C. Xu, Y. Wang, · 2021
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Bert: a review of applications in natural language processing and understanding,
S. Jamal, H. Wimmer, I. Sarker, · 2023
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A survey of large language models,
W. X. Zhao, K. Zhou, J. Li, T. Tang, X. Wang, Y. Hou, Y. Min, B. Zhang, J. Zhang, Z. Dong, et al., · 2023
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A survey on large language model (llm) security and privacy: The good, the bad, and the ugly,
Y. Yao, J. Duan, K. Xu, Y. Cai, E. Sun, Y. Zhang, · 2023
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Interpretable bangla sarcasm detection using bert and explainable ai,
R. Anan, T. S. Apon, Z. T. Hossain, E. A. Modhu, S. Mondal, M. G. R. Alam, · 2023
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The role of machine learning in cybersecurity,
G. Apruzzese, P. Laskov, E. Montes de Oca, W. Mallouli, L. Brdalo Rapa, A. V. Grammatopoulos, F. Di Franco, · 2023
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M. Koroteev, · 2021
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Sentiment analysis on the impact of coronavirus in social life using the bert model,
M. Singh, A. K. Jakhar, S. Pandey, · 2021
Cited alongside, same era.
Email classification for forensic analysis by information gain technique,
D. E. Salhi, A. Tari, M. T. Kechadi, · 2021
Cited alongside, same era.
Applying machine learning and natural language processing to detect phishing email,
A. Alhogail, A. Alsabih, · 2021
Cited alongside, same era.
Urltran: Improving phishing url detection using transformers,
P. Maneriker, J. W. Stokes, E. G. Lazo, D. Carutasu, F. Tajaddodianfar, A. Gururajan, · 2021
Cited alongside, same era.
Survey of bert-base models for scientific text classification: Covid-19 case study,
M. Khadhraoui, H. Bellaaj, M. B. Ammar, H. Hamam, M. Jmaiel, · 2022
Cited alongside, same era.
Phish responder: A hybrid machine learning approach to detect phishing and spam emails,
M. Dewis, T. Viana, · 2022
Cited alongside, same era.
Later among the works it cites.
Intelligent deep learning based cybersecurity phishing email detection and classification.,
R. Brindha, S. Nandagopal, H. Azath, V. Sathana, G. P. Joshi, S. W. Kim, · 2023
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Evaluation of federated learning in phishing email detection,
C. Thapa, J. W. Tang, A. Abuadbba, Y. Gao, S. Camtepe, S. Nepal, M. Almashor, Y. Zheng, · 2023
Later among the works it cites.
Phishing email detection model using deep learning,
S. Atawneh, H. Aljehani, · 2023
Later among the works it cites.
Bert-based models for phishing detection,
M. Songailaitė, E. Kankevičiūtė, B. Zhyhun, J. Mandravickaitė, · 2023
Later among the works it cites.
A large-scale pretrained deep model for phishing url detection,
Y. Wang, W. Zhu, H. Xu, Z. Qin, K. Ren, W. Ma, · 2023
Later among the works it cites.
I. H. Sarker, AI-driven cybersecurity and threat intelligence: cyber automation, intelligent decision-making and explainability, Springer, 2024
2024
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Explainable ai for cybersecurity automation, intelligence and trustworthiness in digital twin: Methods, taxonomy, challenges and prospects,
I. H. Sarker, H. Janicke, A. Mohsin, A. Gill, L. Maglaras, · 2024
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Hybrid quantum-inspired resnet and densenet for pattern recognition with completeness analysis,
A. Chen, H.-L. Yin, Z.-B. Chen, S. Wu, · 2024
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Llm potentiality and awareness: a position paper from the perspective of trustworthy and responsible ai modeling,
I. H. Sarker, · 2024
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Explainabledetector: Exploring transformer-based language modeling approach for sms spam detection with explainability analysis,
M. A. Uddin, M. N. Islam, L. Maglaras, H. Janicke, I. H. Sarker, · 2025
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A survey of phishing email filtering techniques,
A. Almomani, B. B. Gupta, S. Atawneh, A. Meulenberg, E. Almomani, · 2090
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