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5G wireless network technology is widely used, and data protection is becoming more important as data transmitted and received over the network increases. As the number of Internet of Things devices rapidly increases, data leakage attacks targeting lightweight devices are increasing. Machine learning models have limitations in being applied to lightweight devices because of their large computational complexity and latency in the learning process. Improving utility while protecting data using existing data privacy protection techniques is difficult. Guaranteeing privacy and data utility is difficult because processing large amounts of data with low-capacity memory is complicated. Therefore, a memory-efficient mechanism is needed while ensuring privacy and data utility in data transmission conditions. We propose an optimal feature selection mechanism that maximizes privacy and utility by optimizing the privacy-utility trade-off for resource-constrained lightweight device environments. The proposed mechanism extracts privacy-sensitive features by selecting features requiring privacy protection, removing privacy-sensitive features, making it difficult for attackers to identify data even if they intercept them during data transmission. It demonstrated improved accuracy and memory usage compared to conventional models and improved the accuracy of legitimate nodes by 17.6% compared to models with differential privacy, reduced the accuracy of attackers by 15.45% compared to models without privacy protection techniques, and memory usage by 18.26% under 100% data sampling ratio conditions. Thus, it has been proven to be a secure and efficient model for data transmission environments by effectively improving data utility, privacy, and memory usage.

In this work, the suppression of tyrosinase-related genes, including an improvement in UV absorption effects of bioconverted CS extracts (BCS), was investigated to improve the skin-whitening effect. Total polyphenols and total flavonoids, which are bioactive components, increased 2.6- and 5.4-times in bioconversion using Lactiplantibacillus plantarum SM4, respectively, as compared to ultrasound-assisted extracts (UCS). The effect of BCS on radical scavenging activity, UV-A absorption, and tyrosinase activity inhibition, contributing to skin-whitening, were 1.3-, 1.2-, and 1.2-times higher than those of UCS, respectively. The main component identified in high-performance liquid chromatography (HPLC) was gallic acid in both UCS and BCS, which increased by 2.9-times following bioconversion. The gene expression of tyrosinase-related proteins, including TRP-1 and TRP-2 genes, was studied to confirm the suppression of melanin synthesis by BCS in order to identify the skin-whitening mechanism, and BCS decreased both genes’ expression by 1.7- and 1.6-times, demonstrating that BCS effectively suppressed melanin synthesis. These findings imply that the chestnut inner shell can be employed as a cosmetic material by simultaneously inhibiting melanogenesis and enhancing UV-A absorption through bioconversion using L. plantarum SM4.

Considering the increasing scale and severity of damage from recent cybersecurity incidents, the need for fundamental solutions to external security threats has increased. Hence, network separation technology has been designed to stop the leakage of information by separating business computing networks from the Internet. However, security accidents have been continuously occurring, owing to the degradation of data transmission latency performance between the networks, decreasing the convenience and usability of the work environment. In a conventional centralized network connection concept, a problem occurs because if either usability or security is strengthened, the other is weakened. In this study, we proposed a distributed authentication mechanism for secure network connectivity (DAM4SNC) technology in a distributed network environment that requires security and latency performance simultaneously to overcome the trade-off limitations of existing technology. By communicating with separated networks based on the authentication between distributed nodes, the inefficiency of conventional centralized network connection solutions is overcome. Moreover, the security is enhanced through periodic authentication of the distributed nodes and differentiation of the certification levels. As a result of the experiment, the relative efficiency of the proposed scheme (REP) was about 420% or more in all cases.