使用网络态势感知预测网络攻击：独立电力生产商（IPP）的案例
Predicting Cyber-Attack using Cyber Situational Awareness: The Case of Independent Power Producers (IPPs)
摘要：
对物联网（IoT）的日益严重的依赖引发了安全问题;多年来，其在发电关键基础设施（CI）上的应用受到了大规模的网络攻击。以前的研究工作，以了解网络安全从网络态势感知（CSA）的角度未能批判性地考虑各种网络态势感知（CSA）的安全漏洞，从人类行为的角度与CI。该研究评估了CSA元素，以预测发电行业的网络攻击。本研究文章的数据是使用调查方法从IPP收集的。分析方法采用偏最小二乘结构方程模型（PLS-SEM），以评估所提出的模型。结果显示，对人和网络攻击的负面影响，但在预测网络攻击显着。该研究还表明，信息处理是重要的，并积极影响网络攻击。研究还发现，人与攻击和信息与攻击之间的关联没有中介作用。这可能是由于独立发电商实施了有效的网络安全控制。最后，该研究还没有显示网络基础设施网络攻击预测的迹象。原因可能是独立发电厂的管理人员制定了适当的准入政策和安全措施。
英文摘要：
The increasing critical dependencies on Internetof-Things (IoT) have raised security concerns; its application on the critical infrastructures (CIs) for power generation has come under massive cyber-attack over the years. Prior research efforts to understand cybersecurity from Cyber Situational Awareness (CSA) perspective fail to critically consider the various Cyber Situational Awareness (CSA) security vulnerabilities from a human behavioural perspective in line with the CI. This study evaluates CSA elements to predict cyber-attacks in the power generation sector. Data for this research article was collected from IPPs using the survey method. The analysis method was employed through Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the proposed model. The results revealed negative effects on people and cyber-attack, but significant in predicting cyber-attacks. The study also indicated that information handling is significant and positively influences cyber-attack. The study also reveals no mediation effect between the association of People and Attack and Information and Attack. It could result from an effective cyber security control implemented by the IPPs. Finally, the study also shows no sign of network infrastructure cyber-attack predictions. The reasons could be because managers of IPPs had adequate access policies and security measures in place.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
