• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.4
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• pp.159-164
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• 2023

Solar energy harvesting IoT devices prioritize maximizing the utilization of collected energy due to the periodic recharging nature of solar energy, rather than minimizing energy consumption. Meanwhile, research on edge AI, which performs machine learning near the data source instead of the cloud, is actively conducted for reasons such as data confidentiality and privacy, response time, and cost. One such research area involves performing various audio AI applications using audio data collected from multiple IoT devices in an IoT edge computing environment. However, in most studies, IoT devices only perform sensing data transmission to the edge server, and all processes, including data preprocessing, are performed on the edge server. In this case, it not only leads to overload issues on the edge server but also causes network congestion by transmitting unnecessary data for learning. On the other way, if data preprocessing is delegated to each IoT device to address this issue, it leads to another problem of increased blackout time due to energy shortages in the devices. In this paper, we aim to alleviate the problem of increased blackout time in devices while mitigating issues in server-centric edge AI environments by determining where the data preprocessed based on the energy state of each IoT device. In the proposed method, IoT devices only perform the preprocessing process, which includes sound discrimination and noise removal, and transmit to the server if there is more energy available than the energy threshold required for the basic operation of the device.

• The Korea Journal of Herbology
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• v.38 no.5
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• pp.97-103
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• 2023

Objectives : These days many people tend to prefer spicy taste. The purpose of this study was to find out the relationship between prefer spicy and physical symptoms. Methods : We examined the subjective physical condition of patients who visited L/C clinic during the period between January and June 2023 by conducting a survey. The survey was completed voluntarily, and the anonymity and confidentiality of the research data were strictly protected, and it was stated that patients could withdraw at any time if they did not want to participate. Patients who refused to complete the survey and patients with limited capacity to give consent were excluded. The survey took about 10 minutes to complete. We analyzed 248 cases who answered the survey and found that 66 patients had a high spicy preference. Results : As a result, participants with high spicy taste preference tended to have general body symptoms such as fever, sweat, and thirst; digestive symptoms such as belching, constipation, bloody stools, and abdominal distension; genitourinary symptoms such as yellowish urine, urinary retention, white fluor albus, and premenstrual tension; and neuromuscular symptoms such as edema, blepharospasm, and cold hands. Conclusion : People who have general body symptoms, digestive symptoms, genitourinary symptoms and neuromuscular symptoms described above should try to eat as little spicy food as possible and make sure they get a good balance of the five flavors.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.871-874
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• 2011

The fast emerging of network technology and the high demand of computing resources have prompted many organizations to outsource their storage and computing needs. Cloud based storage services such as Microsoft's Azure and Amazon's S3 allow customers to store and retrieve any amount of data, at anytime from anywhere via internet. The scalable and dynamic of the cloud storage services help their customer to reduce IT administration and maintenance costs. No doubt, cloud based storage services brought a lot of benefits to its customer by significantly reducing cost through optimization increased operating and economic efficiencies. However without appropriate security and privacy solution in place, it could become major issues to the organization. As data get produced, transferred and stored at off premise and multi tenant cloud based storage, it becomes vulnerable to unauthorized disclosure and unauthorized modification. An attacker able to change or modify data while data inflight or when data is stored on disk, so it is very important to secure data during its entire life-cycle. The traditional cryptography primitives for the purpose of data security protection cannot be directly adopted due to user's lose control of data under off premises cloud server. Secondly cloud based storage is not just a third party data warehouse, the data stored in cloud are frequently update by the users and lastly cloud computing is running in a simultaneous, cooperated and distributed manner. In our proposed mechanism we protect the integrity, authentication and confidentiality of cloud based data with the encrypt- then-upload concept. We modified and applied proxy re-encryption protocol in our proposed scheme. The whole process does not reveal the clear data to any third party including the cloud provider at any stage, this helps to make sure only the authorized user who own corresponding token able to access the data as well as preventing data from being shared without any permission from data owner. Besides, preventing the cloud storage providers from unauthorized access and making illegal authorization to access the data, our scheme also protect the data integrity by using hash function.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.469-471
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• 2021

As wireless communication technology advances to ensure high accuracy and safety at high speeds, research and development of Visible Light Communication (VLC) technology has been accelerated as an alternative to traditional radio frequency (RF) technology. As the radio spectrum of RF communication becomes more congested and demand for bandwidth continues to increase, VLCs that can use unlicensed frequency band are proposed as a solution. However, VLC channels have broadcasting characteristics that make them easily exposed to eavesdropping and jamming attacks, and are vulnerable to MITM (Man-In-The-Middle) due to their line of sight (LOS) propagation characteristics. These attacks on VLC channels compromise the confidentiality, integrity, and availability of communications links and data, resulting in higher data retransmission rates, reducing throughput and increasing power consumption, resulting in lower data transmission efficiency. In this work, we model vulnerable VLC channels to analyze the impact of attacks and communications vulnerabilities by malicious jammers.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.647-654
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• 2023

Deep Learning is a useful method for classifying and recognizing complex data such as images and text, and the accuracy of the deep learning method is the basis for making artificial intelligence-based services on the Internet useful. However, the vast amount of user da vita used for training in deep learning has led to privacy violation problems, and it is worried that companies that have collected personal and sensitive data of users, such as photographs and voices, own the data indefinitely. Users cannot delete their data and cannot limit the purpose of use. For example, data owners such as medical institutions that want to apply deep learning technology to patients' medical records cannot share patient data because of privacy and confidentiality issues, making it difficult to benefit from deep learning technology. In this paper, we have designed a privacy preservation technique-applied deep learning technique that allows multiple workers to use a neural network model jointly, without sharing input datasets, in multi-party system. We proposed a method that can selectively share small subsets using an optimization algorithm based on modified stochastic gradient descent, confirming that it could facilitate training with increased learning accuracy while protecting private information.

• Journal of IKEEE
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• v.27 no.4
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• pp.548-555
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• 2023

With the advancement of the internet, the use of personal information in online interactions has increased, underscoring the significance of data protection. Breaches of personal data due to unauthorized access can result in psychological and financial damage to individuals, and may even enable wide-ranging societal attacks aimed at those associated with the victims. In response to such threats, there is active research into security measures using blockchain to safeguard personal information. This study proposes a system that uses middleware and IAM (Identity and Access Management) services to protect personal information in a BaaS (Blockchain as a Service) environment where blockchain is provided via the Internet. The middleware operates on servers where IAM roles and policies are applied, authenticates users, and performs access control to allow only legitimate users to access blockchain data existing in the cloud. Additionally, to understand the impact of the proposed personal information protection method on the system, we measure the response time according to the time taken and the number of users under three assumed scenarios, and compare the proposed method and research related to personal information protection using blockchain in terms of security characteristics such as idea, type of blockchain, authentication, and confidentiality.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.73-80
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• 2023

In this paper, a technology to protect important information from access in order to revitalize the cloud service market. A technology is proposed to solve the risk of leakage of important confidential and personal information stored in cloud systems, which is one of the various obstacles to the cloud service market. To protect important information, access control rights to cloud resources are granted to cloud service providers and general users. The system administrator has superuser authority to maintain and manage the system. Client computing services are managed by an external cloud service provider, and information is also stored in an external system. To protect important in-house information within the company, all users, it was designed to provide access authority with users including cloud service providers, only after they are authenticated. It is expected that the confidentiality of cloud computing resources and service reliability achieved through the proposed access control technology will contribute to revitalizing the cloud service market.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2550-2572
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• 2023

Epidemiological survey is an important means for the prevention and control of infectious diseases. Due to the particularity of the epidemic survey, 1) epidemiological survey in epidemic prevention and control has a wide range of people involved, a large number of data collected, strong requirements for information disclosure and high timeliness of data processing; 2) the epidemiological survey data need to be disclosed at different institutions and the use of data has different permission requirements. As a result, it easily causes personal privacy disclosure. Therefore, traditional access control technologies are unsuitable for the privacy protection of epidemiological survey data. In view of these situations, we propose a black box-assisted fine-grained hierarchical access control scheme for epidemiological survey data. Firstly, a black box-assisted multi-attribute authority management mechanism without a trusted center is established to avoid authority deception. Meanwhile, the establishment of a master key-free system not only reduces the storage load but also prevents the risk of master key disclosure. Secondly, a sensitivity classification method is proposed according to the confidentiality degree of the institution to which the data belong and the importance of the data properties to set fine-grained access permission. Thirdly, a hierarchical authorization algorithm combined with data sensitivity and hierarchical attribute-based encryption (ABE) technology is proposed to achieve hierarchical access control of epidemiological survey data. Efficiency analysis and experiments show that the scheme meets the security requirements of privacy protection and key management in epidemiological survey.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.540-546
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• 2023

The scope of IoT use has expanded due to the development of related technologies, and various sensors have been developed and distributed to meet the demand for implementing various services. Measuring alcohol concentration using a sensor can be used to prevent drunk driving, and to make this possible, accurate alcohol concentration must be measured and safe transmission from the smartphone to the server must be guaranteed. Additionally, a process of converting the measured alcohol concentration value into a standard value for determining the level of drinking is necessary. In this paper, we propose and implement a system. Security with remote servers applies SSL at the network layer to ensure data integrity and confidentiality, and the server encrypts the received information and stores it in the database to provide additional security. As a result of analyzing the accuracy of alcohol concentration measurement and communication efficiency, it was confirmed that the measurement and transmission were within the error tolerance.

• Korean Journal of Radiology
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• v.22 no.12
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• pp.2073-2081
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• 2021

Deep learning-based applications have great potential to enhance the quality of medical services. The power of deep learning depends on open databases and innovation. Radiologists can act as important mediators between deep learning and medicine by simultaneously playing pioneering and gatekeeping roles. The application of deep learning technology in medicine is sometimes restricted by ethical or legal issues, including patient privacy and confidentiality, data ownership, and limitations in patient agreement. In this paper, we present an open platform, MI2RLNet, for sharing source code and various pre-trained weights for models to use in downstream tasks, including education, application, and transfer learning, to encourage deep learning research in radiology. In addition, we describe how to use this open platform in the GitHub environment. Our source code and models may contribute to further deep learning research in radiology, which may facilitate applications in medicine and healthcare, especially in medical imaging, in the near future. All code is available at https://github.com/mi2rl/MI2RLNet.