The increasing sophistication of cyber threats necessitates innovative approaches to cybersecurity. In this paper, we explore the potential of psychological profiling techniques, particularly focusing on the utilization of Large Language Models (LLMs) and psycholinguistic features. We investigate the intersection of psychology and cybersecurity, discussing how LLMs can be employed to analyze textual data for identifying psychological traits of threat actors. We explore the incorporation of psycholinguistic features, such as linguistic patterns and emotional cues, into cybersecurity frameworks. \iffalse Through case studies and experiments, we discuss the effectiveness of these methods in enhancing threat detection and mitigation strategies.\fi Our research underscores the importance of integrating psychological perspectives into cybersecurity practices to bolster defense mechanisms against evolving threats.

本研究探索了心理分析技术的潜力，特别关注于大型语言模型和心理语言学特征的利用，研究心理学与网络安全的交叉领域，讨论了如何利用大型语言模型分析文本数据以识别威胁行为者的心理特征，并探讨了将心理语言学特征融入网络安全框架的方法。通过案例研究和实验，证明了这些方法在增强威胁检测和缓解策略方面的有效性。我们的研究强调了将心理学视角纳入网络安全实践的重要性，以加强对不断演变的威胁的防御机制。

网络安全中的心理分析：对LLMs和心理语言学特征的研究