论文标题
系统文献综述:反钓鱼防御及其在点击的网络钓鱼电子邮件检测中的应用
Systematic Literature Review: Anti-Phishing Defences and Their Application to Before-the-click Phishing Email Detection
论文作者
论文摘要
大多数对反钓鱼防御的研究都认为,MAL-ACTOR试图收获最终用户的个人身份信息或登录凭据,因此着重于检测网络钓鱼网站。这种类型的攻击的防御措施通常在链接上的最终用户点击之后会激活,此时检查了链接。这被称为点击检测。但是,更复杂的网络钓鱼攻击(例如矛式捕捞和捕鲸)很少被设计为让最终用户访问网站。取而代之的是,他们试图让最终用户执行其他行动,例如将钱从其银行帐户转移到Mal-Actors帐户。这些攻击更罕见,并且在单击的防守次数少于点击后的防守。为了更好地整合和将这些研究与整体反向钓鱼研究相结合,本文介绍了对拟议的反向钓鱼防御措施的系统文献综述。从总共6330篇论文中,发现并检查了21项主要研究和335项二级研究。当前的研究分为六个主要类别,分组列表/允许列表,启发式,内容,视觉,人工智能/机器学习和积极主动,以及不适合任何主要类别的检测技术的其他类别的“其他”类别。然后,它讨论了在最终用户阅读电子邮件之前,使用这些技术检测网络钓鱼电子邮件的性能和适用性。最后,它建议一些有希望的领域进行进一步研究。
Most research into anti-phishing defence assumes that the mal-actor is attempting to harvest end-users' personally identifiable information or login credentials and, hence, focuses on detecting phishing websites. The defences for this type of attack are usually activated after the end-user clicks on a link, at which point the link is checked. This is known as after-the-click detection. However, more sophisticated phishing attacks (such as spear-phishing and whaling) are rarely designed to get the end-user to visit a website. Instead, they attempt to get the end-user to perform some other action, for example, transferring money from their bank account to the mal-actors account. These attacks are rarer, and before-the-click defence has been investigated less than after-the-click defence. To better integrate and contextualize these studies in the overall anti-phishing research, this paper presents a systematic literature review of proposed anti-phishing defences. From a total of 6330 papers, 21 primary studies and 335 secondary studies were identified and examined. The current research was grouped into six primary categories, blocklist/allowlist, heuristics, content, visual, artificial intelligence/machine learning and proactive, with an additional category of "other" for detection techniques that do not fit into any of the primary categories. It then discusses the performance and suitability of using these techniques for detecting phishing emails before the end-user even reads the email. Finally, it suggests some promising areas for further research.