• Journal of the Korea Society of Computer and Information
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• v.26 no.9
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• pp.81-88
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• 2021

In this paper, we analyze the possibility of deregistration attack in 5G SNPN (Standalone Non-Public Network) based on 3GPP standard document. In the deregistraion attack, the attacker pretends to be a UE that is normally registered with AMF (Access and Mobility Management Function) and attempts to establish a spoofed RRC (Radio Resource Control) connection, causing AMF to deregister the existing UE. The existing deregistration attack attempts a spoofed RRC connection to the AMF in which the UE is registered. In addition, this paper analyzes whether deregistration attack is possible even when an attacker attempts to establish a spoofed RRC connection to a new AMF that is different from the registered AMF. When the 5G mobile communication network system is implemented by faithfully complying with the 3GPP standard, it is determined that a deregistration attack of a UE is impossible.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.119-126
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• 2020

In this paper, we design and implement a product information guidance system Based on BLE beacons. This system is designed to provide various functions such as contactless entrance service through mobile ticket, seat guidance service, event push service, content push service, and public service. This system consists of three modules: a beacon recognition module, a server linkage module, and a content transmission module. The beacon recognition module implements a function of transmitting a specific ID of a nearby beacon when a customer with a smartphone approaches the available service area. The server linkage module recognizes the beacon ID value, transfers it to the server, and implements the function to check the location of the server having the ID. The content transmission module implements a function of transmitting event or service information set at a corresponding location to a smartphone. The beacon-based product information guidance system implemented in this paper has the advantage of being able to quickly and easily implement various product information guidance systems.

• Asia-Pacific Journal of Business
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• v.13 no.3
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• pp.293-309
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• 2022

Purpose - The purpose of this study is to explore the possibility of predicting the degree of smartphone overdependence based on mobile phone usage patterns. Design/methodology/approach - In this study, a survey conducted by Korea Internet and Security Agency(KISA) called "problematic smartphone use survey" was analyzed. The survey consists of 180 questions, and data were collected from 29,712 participants. Based on the data on the smartphone usage pattern obtained through the questionnaire, the smartphone addiction level was predicted using machine learning techniques. k-NN, gradient boosting, XGBoost, CatBoost, AdaBoost and random forest algorithms were employed. Findings - First, while various factors together influence the smartphone overdependence level, the results show that all machine learning techniques perform well to predict the smartphone overdependence level. Especially, we focus on the features which can be obtained from the smartphone log data (without psychological factors). It means that our results can be a basis for diagnostic programs to detect problematic smartphone use. Second, the results show that information on users' age, marriage and smartphone usage patterns can be used as predictors to determine whether users are addicted to smartphones. Other demographic characteristics such as sex or region did not appear to significantly affect smartphone overdependence levels. Research implications or Originality - While there are some studies that predict smartphone overdependence level using machine learning techniques, but the studies only present algorithm performance based on survey data. In this study, based on the information gain measure, questions that have more influence on the smartphone overdependence level are presented, and the performance of algorithms according to the questions is compared. Through the results of this study, it is shown that smartphone overdependence level can be predicted with less information if questions about smartphone use are given appropriately.

• Journal of Industrial Convergence
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• v.21 no.2
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• pp.117-123
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• 2023

In the fintech environment, Smart phones are mainly used for various service. User authentication technology is required to use safe services. Authentication is performed by transmitting authentication information to the server when the PIN or password is entered and touch the button completing authentication. But A post-attack is possible because the smudge which is the trace of using screen remains instead of recording attack with a camera or SSA(Shoulder Surfing Attack). To prevent smudge attacks, users must erase their fingerprints after authentication. In this study, we proposed a technique to determine whether to erase fingerprints. The proposed method performed erasing fingerprint which is the trace of touching after entering PIN and designed the security keypads that processes instead of entering completion button automatically when determined whether the fingerprint has been erased or not. This method suggests action that must erase the fingerprint when entering password. By this method, A user must erase the fingerprint to complete service request and can block smudge attack.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.184-186
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• 2022

Recently, as interest in personal information protection has increased, various apps for personal information protection have emerged. These apps protect data in various formats, such as photos, videos, and documents containing personal information, using encryption and hide functions. These apps can have a positive effect on personal information protection, but in digital forensics, they act as anti-forensic because they can be difficult to analyze data during the investigation process. In this paper, finds out PIN, an access control function, through reverse engineering on Calculator - photo vault, one of the personal information protection apps, and files such as photos and documents to which encryption and hide were applied. In addition, the vulnerability to this app was analyzed by research decryption for database files where logs for encrypted and hide files are stored.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.478-480
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• 2022

Smart Railway as a next generation railway technology is expected to have rapid evolution with developments of information and communications tehchology. Especially, smart railway will be progressed more evolved transportation means for railway operation and costomer service based with spread of commercial 5G communication. So, it is very important to investigate and analyze trends of smart railway related tehcnology of 5G mobile communication for samrt railway infra structure, server technolgy for AI, big data, deep learning, information security technology, sensor and IoT. In this paper, 5G based communicaion technology and application techology related smart railway is described and trends of new techlogy on this communication tehnology is investigated. The results of this study can be used for smart railway study and implementation, research and development for smart railway communicaion technology, etc.

• KNOM Review
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• v.22 no.1
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• pp.42-51
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• 2019

Recently, the amount of internet traffic is increasing due to the increase in speed and capacity of the network environment, and protocol data is increasing due to mobile, IoT, application, and malicious behavior. Most of these private protocols are unknown in structure. For efficient network management and security, analysis of the structure of private protocols must be performed. Many protocol reverse engineering methodologies have been proposed for this purpose, but there are disadvantages to applying them. In this paper, we propose a methodology for inferring a detailed protocol structure based on network trace analysis by hierarchically combining CSP (Contiguous Sequential Pattern) and SP (Sequential Pattern) Algorithm. The proposed methodology is designed and implemented in a way that improves the preceeding study, A²PRE, We describe performance index for comparing methodologies and demonstrate the superiority of the proposed methodology through the example of HTTP, DNS protocol.

• Health Policy and Management
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• v.33 no.1
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• pp.29-39
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• 2023

Background: Breaking the chain of disease transmission from overseas is necessary to control new infectious diseases such as coronavirus disease 2019 effectively. In this study, we developed a mobile app called Self-Symptom Checker (SSC) to monitor the health of inbound travelers. Methods: SSC was developed for general users and administrators. The functions of SSC include non-repudiation using QR (quick response) codes, monitoring fever and respiratory symptoms, and requiring persons showing symptoms to undergo polymerase chain reaction tests at nearby screening stations following a review of reported symptoms by the Korea Disease Control and Prevention Agency, as well as making phone calls, via artificial intelligence or public health personnel, to individuals who have not entered symptoms to provide the necessary information. Results: From February 12 to March 27, 2020, 165,000 people who were subjected to the special entry procedure installed SSC. The expected number of public health officers and related resources needed per day would be 800 if only the phone was used to perform symptom monitoring during the above period. Conclusion: By applying SSC, more effective symptom monitoring was possible. The daily average number of health officers decreased to 100, or 13% of the initial estimate. SSC reduces the work burden on public healthcare personnel. SSC is an electronic solution conceived in response to health questionnaires completed by inbound travelers specified in the World Health Organization International Health Regulations as a requirement in the event of a pandemic.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.169-171
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• 2021

Image processing through cameras such as self-driving, CCTV, mobile phone security, and parking facilities is being used to solve many real-life problems. Simple classification is solved through image processing, but it is difficult to find images or in-image features of complexly mixed objects. To solve this feature point, we utilize deep learning techniques in classification, detection, and segmentation of image data so that we can think and judge closely. Of course, the results are better than just image processing, but we confirm that the results judged by the method of image segmentation using deep learning have deviations from the real object. In this paper, we study how to perform accuracy improvement through simple image processing just before outputting the output of deep learning image segmentation to increase the precision of image segmentation.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.77-89
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• 2024

This paper presents an unmanned store management system that can provide inventory management and theft prevention for displayed products using a small camera that can monitor the shelves of sold products in small and medium-sized stores. This system is a service solution that integrates object recognition, real-time communication, security management, access management, and mobile authentication. The proposed system uses a custom YOLOv5-x model to recognize objects on the display, measure quantities in real time, and support real-time data communication with servers through Raspberry Pie. In addition, the number of objects in the database and the object recognition results are compared to detect suspected theft situations and provide burial images at the time of theft. The proposed unmanned store solution is expected to improve the efficiency of small and medium-sized unmanned store operations and contribute to responding to theft.