• Journal of Internet Computing and Services
• /
• v.23 no.2
• /
• pp.61-70
• /
• 2022

General users who use smartphone apps often use the Vault app to protect personal information such as photos and videos owned by individuals. However, there are increasing cases of criminals using the Vault app function for anti-forensic purposes to hide illegal videos. These apps are one of the apps registered on Google Play. This paper proposes a methodology for extracting feature points through XML-based keyword frequency analysis to explore Vault apps used by criminals, and text mining techniques are applied to extract feature points. In this paper, XML syntax was compared and analyzed using strings.xml files included in the app for 15 hidden Vault anti-forensics apps and non-hidden Vault apps, respectively. In hidden Vault anti-forensics apps, more hidden-related words are found at a higher frequency in the first and second rounds of terminology processing. Unlike most conventional methods of static analysis of APK files from an engineering point of view, this paper is meaningful in that it approached from a humanities and sociological point of view to find a feature of classifying anti-forensics apps. In conclusion, applying text mining techniques through XML parsing can be used as basic data for exploring hidden Vault anti-forensics apps.

• Journal of Intelligence and Information Systems
• /
• v.29 no.4
• /
• pp.165-184
• /
• 2023

Recently, Deep learning analysis of unstructured text data using language models, such as Google's BERT and OpenAI's GPT has shown remarkable results in various applications. Most language models are used to learn generalized linguistic information from pre-training data and then update their weights for downstream tasks through a fine-tuning process. However, some concerns have been raised that privacy may be violated in the process of using these language models, i.e., data privacy may be violated when data owner provides large amounts of data to the model owner to perform fine-tuning of the language model. Conversely, when the model owner discloses the entire model to the data owner, the structure and weights of the model are disclosed, which may violate the privacy of the model. The concept of offsite tuning has been recently proposed to perform fine-tuning of language models while protecting privacy in such situations. But the study has a limitation that it does not provide a concrete way to apply the proposed methodology to text classification models. In this study, we propose a concrete method to apply offsite tuning with an additional classifier to protect the privacy of the model and data when performing multi-classification fine-tuning on Korean documents. To evaluate the performance of the proposed methodology, we conducted experiments on about 200,000 Korean documents from five major fields, ICT, electrical, electronic, mechanical, and medical, provided by AIHub, and found that the proposed plug-in model outperforms the zero-shot model and the offsite model in terms of classification accuracy.

• Health Policy and Management
• /
• v.34 no.2
• /
• pp.106-119
• /
• 2024

Drug shortage is a persistent phenomenon that poses a public health risk worldwide and occurs due to a range of causes. The purpose of this study is to review key policies to prepare for and respond to drug shortages in selected countries, such as the United States, Canada, and some European countries in order to draw implications. This study reviewed the reports and articles derived from search engines and Google Scholar by using keywords such as drug shortage and stock-out. Over the last decade or so, the United States have strengthened requirements on advance notification for disruption and interruption of drug manufacturing, established the Inter-agency Drug Shortages Task Force to promote the communication and coordination of responses, and expedited drug regulatory processes. Similarly, Canada established the Multi-Stakeholder Steering Committee on drug shortages by involving representatives from central and local governments and private sectors. Canada also adopted a tiered approach to the communication of drug shortages based on the assessment of the severity of the shortage problem and released a detailed information guide on communication. In 2019, the joint task force between the European Medicines Agency and the Heads of Medicines Agencies issued guidelines on drug shortage communication in the European Economic Area. The countries reviewed in this paper focus on communication across different stakeholders for the monitoring of and timely response to drug shortages. The efforts to protect public health from the negative impact of the drug shortage crisis would require multi-sectorial and multi-governmental coordination and development of guidelines.