论文标题
使用击键动力学基于压力识别的内部威胁检测
Insider Threat Detection Based on Stress Recognition Using Keystroke Dynamics
论文作者
论文摘要
内部人士威胁是信息安全领域中最紧迫的威胁之一，因为它导致了公司的巨大财务损失。检测这种威胁的大多数提议的方法都需要昂贵且侵入性的设备，这使得它们在实践中很难使用。在本文中，我们提出了一种非侵入性方法，用于基于压力识别的内幕威胁，使用击键动力学，假设入侵者在做出非法行动过程中经历压力，从而影响行为特征。建议的方法同时使用监督和无监督的机器学习算法。结果表明，压力可以为内部威胁检测提供高度有价值的信息。
Insider threat is one of the most pressing threats in the field of information security as it leads to huge financial losses by the companies. Most of the proposed methods for detecting this threat require expensive and invasive equipment, which makes them difficult to use in practice. In this paper, we present a non-invasive method for detecting insider threat based on stress recognition using keystroke dynamics assuming that intruder experiences stress during making illegal actions, which affects the behavioral characteristics. Proposed method uses both supervised and unsupervised machine learning algorithms. As the results show, stress can provide highly valuable information for insider threat detection.
