In the era of the Internet of Things, it is essential to ensure that data collected by sensors and smart devices are reliable and that they are aggregated and transmitted securely to computational components. This has significant effects on the software that manages critical decisions and actuations of IoT systems, with possibly serious consequences when linked to essential services. The development of IoT applications requires suitable techniques to understand and evaluate the complexity of the design process. Here we adopt a software engineering approach where IoT applications are formally specified (specifically in the IOT-LYSA process calculus) and a Control Flow Analysis (CFA) is exploited to statically predict how data will flow through the system. Hence, the CFA builds on a kind of supply chain for subsequent aggregations and use. Based on the analysis prediction, we propose a risk analysis that captures the dependencies between collected and aggregated data and critical decisions.

Risk Estimation in IoT Systems

Galletta, Letterio;
2023-01-01

Abstract

In the era of the Internet of Things, it is essential to ensure that data collected by sensors and smart devices are reliable and that they are aggregated and transmitted securely to computational components. This has significant effects on the software that manages critical decisions and actuations of IoT systems, with possibly serious consequences when linked to essential services. The development of IoT applications requires suitable techniques to understand and evaluate the complexity of the design process. Here we adopt a software engineering approach where IoT applications are formally specified (specifically in the IOT-LYSA process calculus) and a Control Flow Analysis (CFA) is exploited to statically predict how data will flow through the system. Hence, the CFA builds on a kind of supply chain for subsequent aggregations and use. Based on the analysis prediction, we propose a risk analysis that captures the dependencies between collected and aggregated data and critical decisions.
2023
9789811996009
9789811996016
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11771/26418
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