3.8 Proceedings Paper

An Assurance-Based Risk Management Framework for Distributed Systems

出版社

IEEE
DOI: 10.1109/ICWS53863.2021.00068

关键词

Risk Management; Assurance; Network Flows; Security; Testing

资金

  1. EC H2020 Project [CONCORDIA GA 830927]
  2. Universita degli Studi di Milano under the program Piano sostegno alla ricerca

向作者/读者索取更多资源

The emergence of cloud computing and Internet of Things has drastically changed IT systems, requiring new risk management frameworks to adapt to the complexity of modern systems. The proposed assurance-based risk management framework, integrating risk monitoring and risk mitigation computation, is suitable for modern distributed systems.
The advent of cloud computing and Internet of Things (IoT) has deeply changed the design and operation of IT systems, affecting mature concepts like trust, security, and privacy. The benefits in terms of new services and applications come at a price of new fundamental risks, and the need of adapting risk management frameworks to properly understand and address them. While research on risk management is an established practice that dates back to the 90s, many of the existing frameworks do not even come close to address the intrinsic complexity and heterogeneity of modern systems. They rather target static environments and monolithic systems thus undermining their usefulness in real-world use cases. In this paper, we present an assurance-based risk management framework that addresses the requirements of risk management in modern distributed systems. The proposed framework implements a risk management process integrated with assurance techniques. Assurance techniques monitor the correct behavior of the target system, that is, the correct working of the mechanisms implemented by the organization to mitigate the risk. Flow networks compute risk mitigation and retrieve the residual risk for the organization. The performance and quality of the framework are evaluated in a simulated industry 4.0 scenario.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

3.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据