通过机器学习对黑客进行心理分析,实现可持续的网络安全

IF 2.4 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Frontiers in Computer Science Pub Date : 2024-04-08 DOI:10.3389/fcomp.2024.1381351
Umema Hani, Osama Sohaib, Khalid Khan, Asma Aleidi, Noman Islam
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引用次数: 0

摘要

本研究解决了基于 "五大人格特质 "模型(OCEAN)的黑客分类框架所面临的挑战,并探索了人格特质与黑客类型之间的关联。该方法的应用预测性能在两组学生中进行了评估:这两组人分别是:有黑客经验并打算从事信息安全和道德黑客工作的学生,以及从事白帽黑客工作的业内专业人士。这些专业人员还根据其行为倾向进行了进一步分类,其中包括 "灰帽子 "特征。k-means 算法分析了簇内的依赖关系,阐明了不同簇内的变化及其与 "灰帽子 "类型的相关性。该研究在将聚类与 "帽子 "类型进行映射方面达到了 88% 的准确率,从而有效地识别了网络犯罪行为。研究还讨论了网络安全领域人格分析方法中有关隐私和偏见的伦理考虑因素,强调了数据管理实践中知情同意、透明度和问责制的重要性。此外,研究还强调了可持续网络安全实践的必要性,将环境和社会影响纳入安全框架。本研究旨在通过提高人们的意识和道德考量,优先考虑隐私、公平和可持续原则,推动负责任的网络安全实践。
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Psychological profiling of hackers via machine learning toward sustainable cybersecurity
This research addresses a challenge of the hacker classification framework based on the “big five personality traits” model (OCEAN) and explores associations between personality traits and hacker types. The method's application prediction performance was evaluated in two groups: Students with hacking experience who intend to pursue information security and ethical hacking and industry professionals who work as White Hat hackers. These professionals were further categorized based on their behavioral tendencies, incorporating Gray Hat traits. The k-means algorithm analyzed intra-cluster dependencies, elucidating variations within different clusters and their correlation with Hat types. The study achieved an 88% accuracy in mapping clusters with Hat types, effectively identifying cyber-criminal behaviors. Ethical considerations regarding privacy and bias in personality profiling methodologies within cybersecurity are discussed, emphasizing the importance of informed consent, transparency, and accountability in data management practices. Furthermore, the research underscores the need for sustainable cybersecurity practices, integrating environmental and societal impacts into security frameworks. This study aims to advance responsible cybersecurity practices by promoting awareness and ethical considerations and prioritizing privacy, equity, and sustainability principles.
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来源期刊
Frontiers in Computer Science
Frontiers in Computer Science COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
4.30
自引率
0.00%
发文量
152
审稿时长
13 weeks
期刊最新文献
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