4.6 Article

Digital Forensics for E-IoT Devices in Smart Cities

Journal

ELECTRONICS
Volume 12, Issue 15, Pages -

Publisher

MDPI
DOI: 10.3390/electronics12153233

Keywords

E-IoT forensics; smart cities; digital forensics; network security; mobile forensics; hardware forensics

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With the global expansion of urban infrastructure and development of 5G communication technology, advanced information and communications technology has been applied to power systems and smart grids. In this study, digital forensics is applied to identify vulnerabilities in the Energy Internet of Things (E-IoT) device systems, which are used for efficient energy management but also present potential security threats. A digital forensic test bed was built using E-IoT devices supplied to Korean power systems, and a methodology for E-IoT data acquisition and analysis was proposed.
With the global expansion of urban infrastructure and development of 5G communication technology, advanced information and communications technology has been applied to power systems and the use of smart grids has increased. Smart grid systems collect energy data using Internet-of-Things (IoT) devices, such as data concentrator units (DCUs) and smart meters, to effectively manage energy. Services and functions for energy management are being incorporated into home IoT devices. In this paper, the IoT for energy management in smart cities and smart homes is referred to as the E-IoT. Systems that use the E-IoT can efficiently manage data, but they present many potential security threats, because the E-IoT devices in such homes and enterprises are networked for energy management. Therefore, in this study, to identify vulnerabilities in the E-IoT device systems, digital forensics is applied to the E-IoT device systems. E-IoT devices supplied to Korean power systems were used to build a digital forensic test bed similar to actual E-IoT environments. For digital forensics application, E-IoT data acquisition and analysis methodology was proposed. The proposed methodology consisted of three methods-network packet data analysis, hardware interface analysis, and mobile device paired with E-IoT-which were applied to a DCU, smart meter, smart plug, smart heat controller, smart microwave, and smart monitoring system. On analyzing the user and system data acquired, artifacts such as the device name and energy consumption were derived. User accounts and passwords and energy-usage logs were obtained, indicating the possibility of leakage of personal information and the vulnerabilities of E-IoT devices.

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