Forensic Analysis for Cybersecurity of Smart Home Environments with Smart Wallpads

Author:

Kim Sungbum1ORCID,Bang Jewan2,Shon Taeshik3

Affiliation:

1. Department of Artificial Intelligence Convergence Network, Ajou University, 206, World cup-ro, Suwon-si 16499, Republic of Korea

2. Investigation Bureau, National Office of Investigation, Korean National Police Agency, 97, Tongil-ro, Sedaemun-gu, Seoul 03739, Republic of Korea

3. Department of Cybersecurity, Ajou University, 206, World cup-ro, Suwon-si 16499, Republic of Korea

Abstract

Various smart home companies are adding displays to smart home control devices and are also releasing smart home control functions for devices with displays. Since smart home management devices with displays are multifunctional, they can store more digital evidence than traditional management devices. Therefore, we propose a smart home environment forensic methodology focused on wallpads, which are smart home management devices with displays. And we validate the proposed methodology by building a smart home environment centered around wallpads and conducting tests with three vendors (Samsung, Kocom, and Commax). Following the proposed methodology, we identified the software and hardware specifications of devices within the testbed, particularly the wallpads. Based on this, we were able to extract network packets, disk images, and individual files stored internally using methods such as packet capture, vulnerability exploits, serial ports, and chip-off. Through analysis, we confirmed that significant user-related information and videos are stored in these control devices. The digital evidence obtained through the proposed methodology can be used as critical legal evidence, and this study contributes to efficiently analyzing important security issues and evidential data in various smart home IoT environments.

Funder

Korea government

Publisher

MDPI AG

Reference35 articles.

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3. Kim, H. (2024, June 03). Man Nabbed for Hacking Built-in Home cameras of 400,000 Households. Yonhap News Agency(blog), 20 December 2022. Available online: https://en.yna.co.kr/view/AEN20221220009100315.

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5. Kim, H., Shin, Y., Kim, S., Jo, W., Kim, M., and Shon, T. (2022). Digital forensic analysis to improve user privacy on Android. Sensors, 22.

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