• Convergence Security Journal
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• v.19 no.3
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• pp.51-59
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• 2019

In this paper, we propose a device identification system for network visibility that can maintain the secure internal network environment in the IoT era. Recently, the area of enterprise network is getting huge and more complicated. Not only desktops and smartphones but also business pads, barcode scanners, APs, Video Surveillance, digital doors, security devices, and lots of Internet of Things (IoT) devices are rapidly pouring into the business network, and there are highly risk of security threats. Therefore, in this paper, we propose the device identification system that includes the process and module-specific functions to identify the exploding device in the IoT era. The proposed system provides in-depth visibility of the devices and their own vulnerabilities to the IT manager in company. These information help to mitigate the risk of the potential cyber security threats in the internal network and offer the unified security management against the business risks.

• Journal of Internet of Things and Convergence
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• v.8 no.1
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• pp.65-72
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• 2022

The Internet of Things (IoT) provides data convergence and sharing functions, and IoT technology is the most fundamental core technology in creating new services by convergence of various cutting-edge technologies. However, there are different classification systems for the Internet of Things, and when it is limited to the domestic public sector, it is difficult to properly grasp the current status of which devices are installed and operated with what share, and systematic data or research The results are very difficult to find. Therefore, in this study, the relevance of the classification system for IoT devices was analyzed according to reality based on sales, shipments, and growth rate, and based on this, the actual share of IoT devices among domestic public institutions was analyzed in detail. The derived detailed analysis results are expected to be efficiently utilized in the process of selecting IoT devices for research and analysis to advance information protection technology such as responding to malicious code attacks on IoT devices, analyzing incidents, and strengthening security vulnerabilities.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.1279-1282
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• 2017

현재 사물인터넷(Internet of Things; IoT) 기술을 이용한 스마트홈 환경을 구축하기 위해서는 같은 식별체계를 사용하는 플랫폼 디바이스를 사용해야 한다. 그러나 주요 IoT 플랫폼들은 각각 다른 식별체계를 사용하고 있기 때문에 이종 플랫폼 간 디바이스 식별이 어려운 상황이다. 이종 플랫폼 간 디바이스 식별체계 상호연동에 대한 연구는 진행 중이며 아직까지 해결책은 제시되지 않았다. 따라서 본 논문에서는 주요 IoT 플랫폼인 oneM2M, GS1 Oliot, IBM Watson IoT, OCF IoTivity의 디바이스 식별체계를 분석하고 비교하여 서로 다른 플랫폼 간 디바이스 식별체계에 대한 번역기 또는 해석기의 필요성과 개념모델을 제시한다.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.159-169
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• 2024

This paper proposes a new real-time fire monitoring and evacuation navigation system by integrating Augmented Reality (AR) technology with Internet of Things (IoT) technology. The proposed system collects temperature data through IoT temperature measurement devices installed in buildings and automatically transmits it to a MySQL cloud database via an IoT platform, enabling real-time and accurate data monitoring. Subsequently, the real-time IoT data is visualized on a 3D building model generated through Building Information Modeling (BIM), and the model is represented in the real world using AR technology, allowing intuitive identification of the fire origin. Furthermore, by utilizing Vuforia engine's Device Tracking and Area Targets features, the system tracks the user's real-time location and employs an enhanced A^* algorithm to find the optimal evacuation route among multiple exits. The paper evaluates the proposed system's practicality and demonstrates its effectiveness in rapid and safe evacuation through user experiments based on various virtual fire scenarios.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.441-447
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• 2020

In a situation in which around 50 million metric tons of electrical and electronic products is generated globally per year, the total installed base of Internet of Things (IoT) devices is projected to amount to around 75 billion worldwide by 2025. However, there is very little research on identification schemes for end-of-life treatment (EoLT) of IoT devices. To address this issue, this paper proposes new identifiers including EoLT information such as recyclability rate (Rcyc) and recoverability rate (Rcov) of an IoT device, recycling rate (RCR) and recovery rate (RVR) of each part in the IoT device, etc. and implements them by using object identifier (OID), mobile radio frequency identification (RFID) and quick response (QR) code. The implemented OID and mobile RFID can be used with cooperation of a remote server via communication networks and the implemented QR code can be used simply with a smartphone app.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.6
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• pp.1561-1569
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• 2016

As the use of the sensor device increases in IoT environment, the need for device security is becoming more and more important When a sensor device is deployed in IEEE 802.15.4-based LoWPAN, it has to perform the join operation with PAN Coordinator and the binding operation with another device. In the join and binding process, authentication and key distribution of the device are performed using the pre-distributed network key or certificate. However, the network key used in the conventional method has problems that it's role is limited to the group authentication and individual identification is not applied in certificate issuing. In this paper, we propose a secure join and binding protocol in LoWPAN environment that solves the problems of pre-distributed network key.

• Journal of the Microelectronics and Packaging Society
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• v.23 no.2
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• pp.29-35
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• 2016

With the pace of rapid innovation in technology of IoT (Internet of Things) and smart devices, biometric technology becomes one of the most progressive industries. Recent trends in biometrics show most are focused on embedding biometric sensors in mobile devices for user authentication. Multifactor biometrics such as fingerprint, retina, voice, etc. are considering as identification system to provide users with services more secured and convenient. Here we, therefore, demonstrate some major technologies and market trends of mobile biometric technology with its concerns and issues.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.20-34
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• 2021

Today, IoT devices are flooding, and traffic is increasing rapidly. The Internet of Things creates a variety of added value through connections between devices, while many devices are easily targeted by attackers due to security vulnerabilities. In the IoT environment, security diagnosis has problems such as having to provide different solutions for different types of devices in network situations where various types of devices are interlocked, personal leakage of security solutions themselves, and high cost, etc. To avoid such problems, a TCP-based active scan was presented. However, the TCP-based active scan has limitations that it is difficult to be applied to real-time systems due to long detection times. To complement this, this study uses UDP-based approaches. Specifically, a lightweight active scan algorithm that effectively identifies devices using UPnP protocols (SSDP, MDNS, and MBNS) that are most commonly used by manufacturers is proposed. The experimental results of this study have shown that devices can be distinguished by more than twice the true positive and recall at an average time of 1524 times faster than Nmap, which has a firm position in the field.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.4
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• pp.107-114
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• 2014

Things in the IoT(Internet of Things) make various services by exchanging information over networks. The IoT includes many types of WSNs(Wireless Sensor Networks) that consists of spatially distributed wireless sensor nodes and operates with the various purposes with useful technologies such as identification, sensing and communication. Typically, Zigbee network composed of low-cost and lowpower devices is mainly used for wide-area monitoring and remote device control systems. The IoT composed of various WSNs cannot interoperate among networks because of heterogeneous communication protocol and different data representation of each network, but can facilitate interconnection and information exchange among networks via the DDS, which is communication middleware standard that aims to enable real-time, high performance and interoperable data exchanges. In this paper, we proposed design of Zigbee Adaptor for two-way interoperation and data exchange between Zigbee network and other networks in the IoT. Zigbee Adaptor communicates with Zigbee network according to the Zigbee protocol and communicates with external networks via DDS. DDS-based Zigbee Adaptor can facilitate interoperation between a Zigbee network and external networks by systematic cooperation among its components.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.1-6
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• 2019

As mobile technologies such as Internet of Things (IoT)-based smart homes and financial technologies (FinTech) are developed, authentication by smart devices is used everywhere. As a result, presence-based biometric authentication using smart devices has become a new mainstream in knowledge-based authentication methods like the existing passwords. The electrocardiogram (ECG) is less prone to forgery, and high-level personal identification is its unique feature from among various biometric authentication methods, such as the pulse, fingerprints, the face, and the iris. Biometric authentication using an ECG is receiving a great deal of attention due to its uses in healthcare and FinTech. In this study, we implemented an ECG authentication system that allows users to easily measure and authenticate their ECG waveforms using a miniaturized wearable device, rather than a large and expensive measurement device. The implemented ECG authentication system identifies ECG features through P-Q-R-S-T feature point identification, and was user-certified under the proposed authentication protocols. Finally, assessment of measurements in a majority of adult males showed a relatively low false acceptance rate of 1.73%, and a low false rejection rate of 4.14%, in a stable normal state. In a high-activity state, the false acceptance rate was 13.72%, and the false rejection rate was 21.68%. In a high-heart rate state, the false acceptance rate was 10.48%, and the false rejection rate was 11.21%.