Investigation of Phishing Susceptibility with Explainable Artificial Intelligence
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- Matthew Canham & Clay Posey & Delainey Strickland & Michael Constantino, 2021. "Phishing for Long Tails: Examining Organizational Repeat Clickers and Protective Stewards," SAGE Open, , vol. 11(1), pages 21582440219, January.
- Andronicus A. Akinyelu & Aderemi O. Adewumi, 2014. "Classification of Phishing Email Using Random Forest Machine Learning Technique," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-6, April.
- Michael Workman, 2008. "Wisecrackers: A theory‐grounded investigation of phishing and pretext social engineering threats to information security," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(4), pages 662-674, February.
- Padmalochan Panda & Alekha Kumar Mishra & Deepak Puthal, 2022. "A Novel Logo Identification Technique for Logo-Based Phishing Detection in Cyber-Physical Systems," Future Internet, MDPI, vol. 14(8), pages 1-17, August.
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Keywords
phishing susceptibility; cyber security; interpretable artificial intelligence; machine learning;All these keywords.
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