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.

The Android platform accounts for 85% of the global smartphone operating-system market share, and recently, it has also been installed on Internet-of-Things (IoT) devices such as wearable devices and vehicles. These Android-based devices store various personal information such as user IDs, addresses, and payment information and device usage data when providing convenient functions to users. Insufficient security for the management and deletion of data stored in the device can lead to various cyber security threats such as personal information leakage and identity theft. Therefore, research on the protection of personal information stored in the device is very important. However, there is a limitation that the current research for protection of personal information on the existing Android platform was only conducted on Android platform 6 or lower. In this paper, we analyze the deleted data remaining on the device and the possibility of recovery to improve user privacy for smartphones using Android platforms 9 and 10. The deleted data analysis is performed based on three data deletion scenarios: data deletion using the app’s own function, data deletion using the system app’s data and cache deletion function, and uninstallation of installed apps. It demonstrates the potential user privacy problems that can occur when using Android platforms 9 and 10 due to the leakage of recovered data. It also highlights the need for improving the security of personal user information by erasing the traces of deleted data that remain in the journal area and directory entry area of the filesystem used in Android platforms 9 and 10.

Introduction: With the increase of older adult population, late life depression is emerging as a major problem in many countries as it significantly deteriorates function and quality of life in older adults. Late life depression is a multidimensional disease that requires intervention in biopsychosocial perspective. Recent reduction in family size and rapid simplification of generations are making this decrease more dramatic. Thus, single older households are becoming general type of household in late life, emphasizing the importance of social engagement in late life depressionObjectives: the purpose of this study is to assess the correlation between the frequency of face-to-face and non-face-to-face contact with non-cohabitating adult children and late life depression after the COVID-19 pandemic. Additionally, we hypothesized 10 possible moderators and evaluated the moderation effect of each moderator on the correlation. By identifying groups of older adults that are more affected by contact with their children, the understanding of the relationship between late life depression and family contact in older adults might provide insights to set intervention targets in the community.Methods: Older adults who completed the Living Profiles of Older People Survey in Korea were included. In total, 7,573 participants were analyzed by measuring their contact frequency and depression symptoms. Regression analysis was done adjusting covariates. Process macro was used to verify the moderating effects of variables.Results: Multivariable logistic regression analysis showed that both infrequent face-to-face (OR=1.87, 95% CI=1.56-2.23) and non-face-to-face contact (OR=1.22, 95% CI=1.03-1.44) with non-cohabitating adult children group was associated with higher risk of late life depression compared to a frequent contact group. Further linear regression analysis, which viewed depressive symptoms as SGDS-K score, indicated consistent results in face-to-face and non-face-to-face contact (estimate=0.468, standard error [SE]=0.091, p<0.001 and estimate=0.262, standard error [SE]=0.079, p<0.001, respectively). Finally, using moderation analysis, association with late life depression and frequency of face-to-face contact was moderated by age, quartiles of household income, number of chronic diseases, frequency of physical activity, existence of spouse, and nutritional status (NSI) whether effect of frequency of non-face-to-face contact on late life depression was increased by participation in social activity, frequent physical activity, and good cognitive function (MMSE-DS score)(p for interaction<0.05).Conclusions: Frequent contact of non-cohabitating children lowers the risk of later life depression. Several variables were found significant in moderating contact frequency-depression symptoms.Disclosure of Interest: None Declared