Qifan Deng , Mohammad Goudarzi , Arash Shaghaghi , Majid Sarvi , Rajkumar Buyya
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引用次数: 0
Abstract
The integration of edge and cloud computing combines low latency with high computational power, addressing the constraints of edge resources and high access latency inherent in cloud environments. This is essential for deploying Internet of Things (IoT) applications, which are mainly developed by Containers within these heterogeneous environments. However, the open, multi-user nature of edge computing, compounded by a lack of standardized practices, introduces substantial security challenges with severe economic implications. In response, we propose SecConEC, an economically driven framework designed to secure the deployment and execution of containerized IoT applications. We conducted systematic threat modeling using the STRIDE framework, explicitly incorporating quantitative economic risk assessment to identify and prioritize security threats based on their potential economic impacts. We particularly focus on tampering and resource hijacking threats. SecConEC implements robust yet lightweight mitigation and detection mechanisms informed by the MITRE ATT&CK framework through a Security Information and Event Management (SIEM) system. Also, SecConEC introduces a dynamic, security-aware scheduling mechanism that balances performance and security considerations, proactively mitigating economic risks associated with potential security threats. Extensive performance evaluation shows that SecConEC significantly mitigates prioritized threats, effectively securing IoT application deployment and execution in edge-cloud environments, while maintaining low service latency with a minimal performance overhead of 1.7%.
期刊介绍:
Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications.
Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration.
Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.