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The proliferation of phishing sites and emails poses significant challenges to existing cybersecurity efforts.
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Zhuo, S., Biddle, R., Koh, Y.S., Lottridge, D.M., Russello, G.: Sok: Human-centered phishing susceptibility. ACM Trans. Priv. Secur. 26
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2024
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Jayakrishnan, G., Banahatti, V., Lodha, S.: Pickmail: a serious game for email phishing awareness training. In: Usable Security and Privacy (USEC) Symposium (2022)
2022
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Kashapov, A., Wu, T., Abuadbba, S., Rudolph, C.: Email summarization to assist users in phishing identification. In: ASIA CCS ’22 (2022)
2022
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Kojima, T., Gu, S.S., Reid, M., Matsuo, Y., Iwasawa, Y.: Large language models are zero-shot reasoners. In: NeurIPS (2022)
2022
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Li, Q., Cheng, M., Wang, J., Sun, B.: LSTM based phishing detection for big email data. IEEE Trans. Big Data 8
2022
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Mughaid, A., AlZu’bi, S., Hnaif, A., Taamneh, S., Alnajjar, A., Elsoud, E.A.: An intelligent cyber security phishing detection system using deep learning techniques. Clust. Comput. 25
2022
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Qachfar, F.Z., Verma, R.M., Mukherjee, A.: Leveraging synthetic data and PU learning for phishing email detection. In: CODASPY ’22: Twelveth ACM Conference on Data and Application Security and Privacy (2022)
2022
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Saka, T., Vaniea, K., Kökciyan, N.: Context-based clustering to mitigate phishing attacks. In: AISec 2022 (2022)
2022
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Wei, J., Wang, X., Schuurmans, D., Bosma, M., Ichter, B., Xia, F., Chi, E.H., Le, Q.V., Zhou, D.: Chain-of-thought prompting elicits reasoning in large language models. In: NeurIPS (2022)
2022
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Enron Email Dataset. https://www.cs.cmu.edu/~enron/ (2024)
2024
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mo-messidi/Email-Phishing-Attempts-Detection-using-NLP. https://github.com/mo-messidi/Email-Phishing-Attempts-Detection-using-NLP (2024)
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rf-peixoto/phishing_pot. https://github.com/rf-peixoto/phishing_pot (2024)
2024
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SpamAssassin public mail corpus. https://spamassassin.apache.org/old/publiccorpus/ (2024)
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VirusTotal. https://www.virustotal.com/ (2024)
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Chataut, R., Gyawali, P.K., Usman, Y.: Can AI keep you safe? A study of large language models for phishing detection. In: Paul, R., Kundu, A. (eds.) 14th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2024, Las Vegas, NV, USA, January 8-10, 2024. pp. 548–554. IEEE (2024). https://doi.org/10.1109/CCWC60891.2024.10427626, https://doi.org/10.1109/CCWC60891.2024.10427626
2024
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Google Cloud: Gemini API. https://cloud.google.com/vertex-ai/docs/generative-ai/model-reference/gemini (2024)
2024
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Google Workspace Blog: An overview of Gmail’s spam filters. https://workspace.google.com/blog/identity-and-security/an-overview-of-gmails-spam-filters?hl=en (2024)
2024
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Heiding, F., Schneier, B., Vishwanath, A., Bernstein, J., Park, P.S.: Devising and detecting phishing emails using large language models. IEEE Access 12
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Microsoft Azure: Azure OpenAI Service. https://azure.microsoft.com/en-us/products/ai-services/openai-service (2024)
2024
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Microsoft Support: Overview of the Junk Email Filter. https://support.microsoft.com/en-us/office/overview-of-the-junk-email-filter-5ae3ea8e-cf41-4fa0-b02a-3b96e21de089 (2024)
2024
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