• Journal of Digital Contents Society
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• v.18 no.5
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• pp.803-810
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• 2017

Currently, every person possesses a smart phone due to the development of the IT industry. There is an improper situation in which a smart phone is not set in silent mode, such as a lecture room, a library, and a theatre hall. The proposed system automatically automates the function of smart phones where they are designated as a public place or etiquette area and automatically return the function of the smartphone if they deviate from the location of the site. It is also equipped with a combination of autonomous devices and services, based on Bluetooth communications, which are applied to ultra-light low-power IoT(Internet of Things) devices, and has features that allow diverse types of features and services to be added without requiring deformation of the hardware.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.77-87
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• 2023

Applying various association rule mining algorithms to the network intrusion detection task involves two critical issues: too large size of generated rule set which is hard to be utilized for IoT systems and hardness of control of false negative/positive rates. In this research, we propose an association rule mining algorithm based on the newly defined measures called coverage and exclusion. Coverage shows how frequently a pattern is discovered among the transactions of a class and exclusion does how frequently a pattern is not discovered in the transactions of the other classes. We compare our algorithm experimentally with the Apriori algorithm which is the most famous algorithm using the public dataset called KDDcup99. Compared to Apriori, the proposed algorithm reduces the resulting rule set size by up to 93.2 percent while keeping accuracy completely. The proposed algorithm also controls perfectly the false negative/positive rates of the generated rules by parameters. Therefore, network analysts can effectively apply the proposed association rule mining to the network intrusion detection task by solving two issues.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.43-50
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• 2024

This manuscript proposes an artificial intelligence-based(AI) energy platform system that efficiently use existing energy than creating new energy than creating new energy sources. To this end, it collects public information data portal and statistics data portal and data emissions, including energy usage and greenhouse gas emissions, including energy consumption and greenhouse gas emissions.In addition, it provides strong security and personal information protection functions to overcome the limit of existing energy platform. Through the built energy platform, improving power supply and user convenience of users and users to contribute to global warming issues.In this paper, the contents to implement the contents of the system, and improvement direction from the future completion and improvement direction.

• Journal of Wellbeing Management and Applied Psychology
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• v.5 no.4
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• pp.19-31
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• 2022

Purpose: This study was conducted to identify indoor air quality in various living spaces using sensors that can measure noise, vibration, fine dust, and odor in real time and to propose optimal indoor air quality maintenance management using Internet of Things(IoT). Research design, data and methodology: Using real-time sensors to monitor physical factors and environmental air pollutants that affect the comfort of the residential environment, Noise, Vibration, Atmospheric Pressure, Blue Light, Formaldehyde, Hydrogen Sulfide, Illumination, Temperature, Ozone, PM10, Aldehyde, Amine, LVOCs and TVOCs were measured. It were measured every 1 seconds from 4 offices and 4 stores on a small scale from November 2018 to January 2019. Results: The difference between illuminance and blue light for each measuring point was found to depend on lighting time, and the ratio of blue light in total illumination was 0.358 ~ 0.393. Formaldehyde and hydrogen sulphide were found to be higher than those that temporarily attract people in an indoor office space that is constantly active, requiring office air ventilation. The noise was found to be 50dB higher than the office WHO recommendation noise level of 35 ~ 40dB. The most important factors for indoor environmental quality were temperature> humidity> illumination> blue light in turn. Conclusions: Various factors that determine the comfort of indoor living space can be measured with real-time sensors. Further, it is judged that the use of IoT can help maintain indoor air quality comfortably.

• Journal of Internet of Things and Convergence
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• v.6 no.1
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• pp.23-30
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• 2020

This paper proposes energy management directions to discover the factors of energy loss in homes and buildings and to find ways to improve them. We designed a diagnostic content app for everyday life so that not only housing experts but also the general public can use the detachable thermal imaging camera, which is a strong point of popularity and convenience. The diagnostic results using the app were analyzed using Energy Finder, an energy efficiency diagnostic solution. The survey was conducted on the senior center which is in the blind spots and facilities of the energy welfare area. The target of diagnosis was energy efficiency diagnosis by selecting 30 senior centers for over 15 years from 600 locations located in Naju City, Jeollanam-do. The overall diagnosis was good, but it is considered that the place classified as 7th grade needs to be supplemented to improve energy efficiency.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.1-7
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• 2023

Cases in which personal terminals or servers are infected by ransomware are rapidly increasing. Ransomware uses a self-developed encryption module or combines existing symmetric key/public key encryption modules to illegally encrypt files stored in the victim system using a key known only to the attacker. Therefore, in order to decrypt it, it is necessary to know the value of the key used, and since the process of finding the decryption key takes a lot of time, financial costs are eventually paid. At this time, most of the ransomware malware is included in a hidden form in binary files, so when the program is executed, the user is infected with the malicious code without even knowing it. Therefore, in order to respond to ransomware attacks in the form of binary files, it is necessary to identify the encryption module used. Therefore, in this study, we developed a mechanism that can detect and identify by reverse analyzing the encryption module applied to the malicious code hidden in the binary file.

• Journal of Internet of Things and Convergence
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• v.6 no.4
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• pp.81-87
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• 2020

This paper creates a standard node for acquiring sensor data from various industrial sensors (IoT/non-IoT) for the establishment of Smart Factory Digital Twin, and provides inter-compatible data by linking zones by group/process to secure data stability and to ensure the digital twin (Digital Twin) of Smart Factory. The process of the Zone Master platform contains interface specifications to define sensor objects and how sensor interactions between independent systems are performed and carries out individual policies for unique data exchange rules. The interface for execution control of the Zone Master Platform processor provides system management, declaration management for public-subscribe, object management for registering and communicating status information of sensor objects, ownership management for property ownership sharing, time management for data synchronization, and data distribution management for Route information on data exchange.

• Journal of Internet of Things and Convergence
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• v.9 no.4
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• pp.71-75
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• 2023

Changes in modern society are resulting in the emergence of various service models that apply software and artificial intelligence, and all fields are rapidly changing based on software and artificial intelligence. Education on software and artificial intelligence is emerging as a major influencing factor that determines national competitiveness. Following these social changes, interest in the use of software and artificial intelligence is quite high. Starting in 2025, software and artificial intelligence-related curricula are scheduled to be introduced into public education in elementary, middle, and high schools, so many educational activities are becoming active. In this study, based on the content of operating the software and artificial intelligence experience activity program, we would like to propose the efficiency of future learning programs and operating methods for software and artificial intelligence.

• Journal of Internet of Things and Convergence
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• v.6 no.2
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• pp.25-29
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• 2020

The elliptic curve crypto-algorithm is widely used in authentication for IoT environment, since it has small key size and low communication overhead compare to the RSA public key algorithm. If the scalar multiplication, a core operation of the elliptic curve crypto-algorithm, is not implemented securely, attackers can find the secret key to use simple power analysis or differential power analysis. In this paper, an elliptic curve scalar multiplication algorithm using a randomized scalar and an elliptic curve point blinding is suggested. It is resistant to power analysis but does not significantly reduce efficiency. Given a random r and an elliptic curve random point R, the elliptic scalar multiplication kP = u(P+R)-vR is calculated by using the regular variant Shamir's double ladder algorithm, where l+20-bit u≡rn+k(modn) and v≡rn-k(modn) using 2^lP=∓cP for the case of the order n=2^l±c.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.4
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• pp.67-78
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• 2016

Recently many countries around the world are actively promoting smart city projects to address various urban problems such as traffic congestion, housing shortage, and energy scarcity. Due to development of the Internet of Things (IoT), the development of a smart city with sustainability, convenience, and environment-friendliness was enabled through the effective control and reuse of urban resources. The purpose of this study is to analyze the technical trends of IoT and present a development plan for smart city which is one of the applications of the IoT. To this end, the news articles of the Electronic Times between 2013 and 2015were analyzed using the text mining technique and smart city development cases of other countries were investigated. The analysis results revealed the close relationships of big data, cloud, platforms, and sensors with smart city. For the successful development of a smart city, first, all the interested parties in the city must work together to create new values throughout the entire process of value chain. Second, they must utilize big data and disclose public data more actively than they are doing now. This study has made academic contribution in that it has presented a big data analysis method and stimulated follow-up studies. For the practical contribution, the results of this study provided useful data for the policy making of local governments and administrative agencies for smart city development. This study may have limitations in the incorporation of the total trends because only the news articles of the Electronic Times were selected to analyze the technical trends of the IoT.