EAGER: Cybercrime Susceptibility in the Sociotechnical System: Exploration of Integrated Micro- and Macro-Level Sociotechnical Models of Cybersecurity

EAGER：社会技术系统中的网络犯罪敏感性：网络安全的微观和宏观综合社会技术模型的探索

• 批准号: 1343430
• 负责人: Saman Zonouz
• 金额: $ 20万
• 依托单位: University of Miami
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2015-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1343430&HistoricalAwards=false
• 关键词: EAGER; Cybercrime; Susceptibility; Sociotechnical; System

This project develops a holistic approach to sociotechnical system security that combines innovations in both criminology and engineering/computer science. We design unified sociotechnical security models that capture how sociotechnical intrusions against social as well as technical aspects of the system (i.e., modeled as hidden sequences of system security states) result in observed hard data such as security sensor alerts and soft data produced by human/social sensors such as reports about slow machines. To model the social aspect of the sociotechnical security models, (1) we collect extensive social survey data from one specific subpopulation (employees) nested within one sociotechnical system (the university campus); (2) we identify various social and social-psychological factors reducing susceptibility to victimization by computer-focused crime drawing on several criminological and sociological theories; (3) we supplement social survey data with organizational-level data to explore influences of characteristics of organizational units on individual-level employee victimization by computer-focused crimes as well as rates of such cybercrime threats in organizational units. We analyze the collected data by applying unique integrated sociotechnical analytical approaches that encapsulate the adversarial actions and subsequent rewards/costs using stochastic Markov decisions processes and probabilistic data production models. Our research provides guidelines for other researchers looking to incorporate social science methods and models into engineering systems, with the criminological/sociological aspect of the study of use to many other researchers. This work will transform how researchers approach the problem of sociotechnical security, in that our holistic view cognizant of both social and technical factors will become widespread.

该项目开发了一个整体的方法，以社会技术系统的安全，结合在犯罪学和工程/计算机科学的创新。我们设计了统一的社会技术安全模型，这些模型捕捉了社会技术入侵对系统的社会和技术方面的影响（即，被建模为系统安全状态的隐藏序列）导致观察到的硬数据（诸如安全传感器警报）和由人类/社会传感器产生的软数据（诸如关于慢机器的报告）。为了对社会技术安全模型的社会方面进行建模，（1）我们从一个特定的亚人群中收集了广泛的社会调查数据（雇员）嵌套在一个社会技术系统中（大学校园）;（2）我们根据几种犯罪学和社会学理论，确定了各种社会和社会心理因素，这些因素降低了计算机犯罪的受害敏感性;（3）在社会调查数据的基础上补充组织层面的数据，探讨组织单位的特征对个人层面的员工受计算机犯罪侵害的影响，以及组织单位中此类网络犯罪威胁的发生率。我们通过应用独特的综合社会技术分析方法来分析收集到的数据，这些方法使用随机马尔可夫决策过程和概率数据生产模型来封装对抗行为和随后的奖励/成本。我们的研究为其他希望将社会科学方法和模型纳入工程系统的研究人员提供了指导方针，并为许多其他研究人员提供了犯罪学/社会学方面的研究。这项工作将改变研究人员如何处理社会技术安全问题，因为我们对社会和技术因素的整体认识将变得普遍。