Analysis of Malicious Email Detection using Cialdini’s Principles

Hiroki Nishikawa, Takumi Yamamoto, B. Harsham, Ye Wang, Kota Uehara, Chiori Hori, Aiko Iwasaki, Kiyoto Kawauchi, M. Nishigaki
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引用次数: 2

Abstract

This research proposes a technique for identifying the persuasion methods of attackers that are likely to appear in targeted emails. A “persuasion method” is a technique (such as impersonating a person of authority, or appealing to scarcity) which makes the recipient more psychologically willing to obey the will of the attacker. Estimating the presence of persuasion methods in email bodies using machine learning is expected to find application as an effective feature for detecting malicious email, and in tools for warning users that they are being persuaded.
利用Cialdini原理分析恶意邮件检测
本研究提出了一种技术,用于识别可能出现在目标电子邮件中的攻击者的说服方法。“说服方法”是一种技巧(如冒充权威人士,或诉诸稀缺),使接受者在心理上更愿意服从攻击者的意志。使用机器学习估计电子邮件正文中说服方法的存在,有望成为检测恶意电子邮件的有效功能,并在警告用户他们被说服的工具中得到应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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