Towards New Security Paradigms for User Authentication and Traffic Inspection: Harnessing Implicit Mistakes and Auditory Sense

这个研究项目研究了两个新的安全范例，它们通过内隐认知和听觉利用人类的大脑来应对对计算机系统的已知的、正在出现的、或许是不可预见的攻击。一种范例处理基于隐式错误的用户身份验证，另一种范例处理网络流量的音频检查。通常，身份验证依赖于用户知道、拥有、正在做或做的事情，例如密码、访问卡、指纹或语音。该研究项目研究了一种新的身份验证机制，该机制依赖于用户的无意识的显著错误，我们将其称为“内隐错误”，以匹配认知心理学中的术语。在过去的几十年里，认知心理学的一些研究人员报告了利用人的潜意识进行实验的情况，而近年来，一些公司将脑电(EEG)技术应用到商业读心器设备中，这些设备带有不同的应用程序，并提供开发软件套件和在线商店，以促进软件的生产和分发。瓦尔加斯·马丁博士在2010年提出了内隐认知认证的想法，标志着利用脑电设备和认知心理学的进步来进行认证的提议开始高涨。关于流量检查，Vargas Martin致力于研究适当的技术，利用音乐理论来确定网络流量的特征，这些特征表明入侵行为。特别是，这个研究项目测试了音乐和声在网络、服务器或简单计算机中传达活动信息的有效性。这种方法的一个关键方面是识别和有效解释特征，当这些特征被用作集合时，可以向人类传达有意义的信息。无论是在特征提取技术方面，还是在音乐声音生成方面，可能性都是巨大的。

This research program studies two new security paradigms that exploit the human mind via implicit cognition and the auditory sense to cope with known, emerging, and perhaps unforeseen attacks on computer systems. One paradigm deals with user authentication based on implicit mistakes and the other one with audio inspection of network traffic. Typically, authentication relies on something the user knows, has, is, or does, such as a password, access card, fingerprints, or voice, respectively. This research program studies a novel authentication mechanism that relies on the user's unconscious distinctive mistakes which we call "implicit mistakes" to match terminology in cognitive psychology. Over the past decades, a number of researchers in cognitive psychology have reported on experiments that tap into a person's unconscious, while in recent years some companies have adopted electroencephalogram (EEG) technology into commercial mind reader devices that ship with diverse applications and provide development software kits and online stores to facilitate the production and distribution of software. Dr. Vargas Martin proposed the idea of implicit cognition authentication in 2010, marking the beginning of an upsurge of authentication proposals leveraging EEG devices and advances in cognitive psychology. With regards to traffic inspection, Vargas Martin works on appropriate techniques to harness music theory to sonificate features of network traffic that are indicative of intrusions. In particular, this research program tests the effectiveness of music harmony to convey information about the activity in a network, server, or a simple computer. A key aspect of this approach is the identification and effective interpretation of features that, when used as aggregates can convey meaningful information to a human being. The possibilities are vast, both in terms of the feature extraction techniques, and in terms of musical sound generation.