Utilizing Large Language Models with Human Feedback Integration for Generating Dedicated Warning for Phishing Emails-Reference-Cited by-同舟云学术

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Utilizing Large Language Models with Human Feedback Integration for Generating Dedicated Warning for Phishing Emails

Published:2024-07-02 Issue: Volume: Page:35-46
ISSN:
Container-title:Proceedings of the 2nd ACM Workshop on Secure and Trustworthy Deep Learning Systems
language:
Short-container-title:

Author:

Nguyen Quan Hong¹^ORCID,Wu Tingmin²^ORCID,Nguyen Van¹^ORCID,Yuan Xingliang³^ORCID,Xue Jason⁴^ORCID,Rudolph Carsten¹^ORCID

Affiliation:

1. Monash University, Clayton, VIC, AUS

2. CSIRO's Data61, Clayton, VIC, AUS

3. The University of Melbourne, Melbourne, VIC, AUS

4. CSIRO's Data61, Marsfield, NSW, AUS

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3665451.3665531

Reference57 articles.

1. VisualPhishNet: Zero-Day Phishing Website Detection by Visual Similarity

2. APWG Phishing Trends Reports. [n. d.]. http://www.antiphishing.org [Online; accessed 4-October-2023].

3. A Comparison of Natural Language Processing and Machine Learning Methods for Phishing Email Detection

4. Don’t Forget the Human: a Crowdsourced Approach to Automate Response and Containment Against Spear Phishing Attacks

5. Why people keep falling for phishing scams: The effects of time pressure and deception cues on the detection of phishing emails

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