SBE TWC: Small: Collaborative: Pocket Security - Smartphone Cybercrime in the Wild

SBE TWC：小型：协作：袖珍安全 - 智能手机野外网络犯罪

• 批准号: 1617301
• 负责人: David Maimon
• 金额: $ 17.84万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-15 至 2019-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1617301&HistoricalAwards=false
• 关键词: SBE; TWC; Small; Collaborative; Pocket

Most of the world's internet access occurs through mobile devices such as smart phones and tablets. While these devices are convenient, they also enable crimes that intersect the physical world and cyberspace. For example, a thief who steals a smartphone can gain access to a person?s sensitive email, or someone using a banking app on the train may reveal account numbers to someone looking over her shoulder. This research will study how, when, and where people use smartphones and the relationship between these usage patterns and the likelihood of being a victim of cybercrime. This research is the first step to a better scientific understanding how the physical world surrounding smartphone use enables cybercrime. Tired users may be less cautious in browsing to unsafe websites, or distracted users may miss a critical pop-up that a virus has been detected. Once these unsafe patterns of behavior are identified, new techniques, tools, and training can be developed to help prevent smartphone users from becoming victims of cybercrime.This research expands existing theories of victimization in the domain of mobile devices, where both the criminal activity and the victimization occur online but may be affected by the offline environment. This research collects sensor data from the smartphones of 160 volunteers, such as GPS location, call frequency, and app usage. The smartphone sensor data is combined with questionnaires, demographic data from the U.S. Census, and neighborhood condition data from Google Street view. This research also provides a baseline of smartphone security threats stemming from behavioral and social factors, and applies new methods for social science research using mobile sensor data to unobtrusively observe the daily activities of subjects. Finally, this research adds to the body of knowledge on the fundamental limitations of sensor-based activity and context inferences, provides a unique corpus of smartphone sensor data that is freely available to the scientific community, and a set of open source tools for collecting and analyzing the data.

世界上大多数Internet访问都是通过智能手机和平板电脑等移动设备进行的。尽管这些设备很方便，但它们还可以使犯罪与物理世界和网络空间相交。例如，一个偷智能手机的小偷可以访问一个人的敏感电子邮件，或者在火车上使用银行应用程序的人可能会向看着她肩膀的人揭示帐号。这项研究将研究人们如何，何时和何处使用智能手机以及这些使用模式之间的关系以及成为网络犯罪受害者的可能性。这项研究是更好地了解智能手机使用的物理世界如何实现网络犯罪的第一步。疲倦的用户在浏览不安全的网站时可能不太谨慎，或者分心的用户可能会错过检测到病毒的关键弹出窗口。一旦确定了这些不安全的行为模式，就可以开发新的技术，工具和培训，以防止智能手机用户成为网络犯罪的受害者。这项研究扩大了移动设备领域中现有的受害理论，在线犯罪活动和受害者都在网上发生，但可能会受到离线环境的影响。这项研究从160名志愿者的智能手机（例如GPS位置，呼叫频率和APP使用）中收集传感器数据。智能手机传感器数据与问卷，来自美国人口普查的人口统计数据以及Google Street View的邻里状况数据相结合。 这项研究还提供了源于行为和社会因素引起的智能手机安全威胁的基线，并使用移动传感器数据应用了社会科学研究的新方法，以毫不客气地观察受试者的日常活动。最后，这项研究增加了有关基于传感器的活动和上下文推断的基本局限性的知识，提供了独特的智能手机传感器数据库，该数据可供科学界自由使用，并提供了一套用于收集和分析数据的开源工具。