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Operator Suspicion and Decision Responses to Cyber-Attacks on Unmanned Ground Vehicle Systems

机译:操作员对无人机系统网络攻击的怀疑和决策响应

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Cyber-attacks against cyber-physical systems (CPS), such as unmanned vehicles, are emergent threats with potentially catastrophic impacts, and this issue has drawn considerable interest by military agencies. Abundant body of research has attempted to address the physical security aspects of CPS; however, research addressing the human dimensions of cyber-attack detection and responses from an operator and operational perspective is sparse. This research has provided a novel probe into the human factors affecting operator resilience in responding to cyber-attacks, which are situations characterized by uncertainty and malicious intent. The variability of individual operators makes it improbable to grasp the full range of factors contributing to operator performance; however, the application of Suspicion Theory as proposed by Bobko et al. (2013), provides a starting point to aid in understanding operator performance in situations involving malicious intent (e.g. a cyber-attack). According to the theory, malicious intent is a critical component of operator suspicion, which is a key factor in operator response to cyber-attacks. The current research explored this human dimension through scenario-based, human-in-the-loop simulation experiments with Air Force personnel. It included both abstract and empirical assessments of the application of Suspicion Theory to operator detection and responses to cyber-attacks against an unmanned vehicle system, and it took a systems-oriented approach to the problem by considering the interaction of a Human-Machine Team (HMT) in the response. The HMT here refers to an operator and a Sentinel, which is an automated cyber-attack detection aid. The study evaluated the effects of suspicion, as well as the effects of perceived consequence, on the operator, and the resulting HMT quality of performance in responding to alerts, including both false alarms and properly detected cyber-attack scenarios. The findings show that Sentinel alerts alone do not create operator suspicion. Instead, alerts can serve as a catalyst for a wider information search by the operator, which, on a situational basis can lead to formation of increased operator suspicion. The analysis of experimental results pointed to a negative correlation between operator suspicion and performance score that measured the quality of a response to the given scenario. In addition, a strong correlation between HMT performance score and task response time was noted.
机译:对无人驾驶车辆等网络物理系统(CPS)的网络攻击是紧急威胁,具有潜在的灾难性影响,这个问题引起了军事机构的极大关注。大量的研究试图解决CPS的物理安全问题。但是,从操作人员和操作角度解决网络攻击检测和响应的人为因素的研究很少。这项研究为影响操作员应对网络攻击的弹性的人为因素提供了新颖的探索,这些因素具有不确定性和恶意意图。各个操作员的可变性使得难以掌握影响操作员绩效的所有因素。然而,Bobko等人提出的怀疑理论的应用。 (2013),提供了一个起点来帮助理解操作员在涉及恶意意图(例如网络攻击)的情况下的性能。根据该理论,恶意意图是操作员怀疑的关键组成部分,这是操作员对网络攻击做出响应的关键因素。当前的研究通过与空军人员进行基于场景的在环仿真实验来探索这种人的维度。它包括对怀疑理论在无人驾驶车辆系统中对操作员检测和对网络攻击的响应的应用的抽象和实证评估,并且通过考虑人机团队之间的互动,采用了面向系统的方法解决此问题( HMT)。这里的HMT指的是操作员和前哨,这是一种自动的网络攻击检测辅助工具。该研究评估了怀疑的影响以及感知结果对操作员的影响,以及由此产生的HMT在响应警报(包括错误警报和正确检测到的网络攻击场景)方面的性能质量。调查结果表明,仅Sentinel警报不会引起操作员的怀疑。取而代之的是,警报可以充当操作员进行更广泛信息搜索的催化剂,在某些情况下,这可能导致形成更多的操作员怀疑。对实验结果的分析表明,操作员的怀疑与绩效得分之间存在负相关关系,后者衡量了对给定情况的响应质量。此外,还注意到HMT性能得分与任务响应时间之间有很强的相关性。

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