• Annual Conference of KIPS
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• 2016.04a
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• pp.297-299
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• 2016

기술의 발달과 융합으로 사물인터넷(Internet of Things; IoT)의 시대가 열렸다. 빅 데이터와 센서의 발달로 인해 정보는 전과 달리 더욱 사용자와 밀접해졌고 다양해졌으며 양 또한 많아졌다. 이와 더불어 IoT 환경은 다양한 기술들이 융합된 구조로 기존 기술들이 가지고 있는 보안 취약점뿐만 아니라 보다 복잡한 보안 문제점들이 발생할 수 있다. 본 논문에서는 IoT 환경에서 서비스나 IoT 기기들이 갖춰야할 보안 요구사항들을 확장성(scalability), 상호운용성(interoperability), 최소 자원 필요성(minimum resource necessity)으로 분류 하고 정의하였으며, IoT 서비스를 제공하기 위해 사용하는 대표적 프로토콜인 MQTT(Message Queue Telemetry Transfer)와 CoAP(Constrained Application Protocol)에 초점을 맞춰 각각의 표준 문서에서 권고하고 있는 보안 기술에 대해 살펴본다. 또한 그런 기술들에 있어서 발생 가능한 보안 취약점들을 분석하고 이를 해결하기 위한 방법을 제시한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.305-306
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• 2021

본 논문에서는 인천공항 Airside와 Landside에 위치한 자산의 효율적인 관리를 위한 사물인터넷(IoT) 기반 스마트 자산관리 시스템의 구성과 실증을 제시한다. IoT기반 스마트 자산관리시스템은 위치정보를 생성하는 IoT 태그와 게이트웨이, 수집된 위치정보를 수신하고 표출하는 서버로 구성되어 있으며, IoT 태그를 자산에 부착하여 자산의 실내외 위치정보를 자산관리 시스템에서 실시간으로 확인할 수 있다. 실내 위치정보는 BLE(Bluetooth Low Energy)를 통해 취득하며, 실외 위치정보는 GPS와 LoRa(Long Range)를 통해 취득 가능하다. 개발한 시스템의 성능 검증을 위해 인천공항 제1여객터미널 내 기설치된 AP를 활용하였으며, 공항 전역을 커버할 수 있는 LoRa Gateway를 설치하였다. 개발한 자산관리 시스템은 공항이 보유한 자산의 도난 방지 등 효율적인 관리 와 공항운영에 기여할 것으로 예상된다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.235-238
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• 2016

With the vision of Internet of Things (IoT), physical world itself is becoming a connected information system on the Internet and cyber world is computing as a physical act to sense and respond to real-world events collaboratively. The systems that tightly interlink the cyber and physical worlds are often referred to as Smart Systems or Cyber-Physical Systems. Smart IoT Clouds aim to provide a cyber-physical infrastructure for utility (pay-as-you-go) computing to easily and rapidly build, modify and provision auto-scale smart systems that continuously monitor and collect data about real-world events and automatically control their environment. Developing specifications for service interoperability is critical to enable to achieve this vision. In this paper, we bring an issue to extend Open Cloud Computing Interface for uniform, interoperable interfaces for Smart IoT Cloud Services to access services and build a smart system through orchestrating the cloud services.

• Smart Media Journal
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• v.5 no.2
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• pp.24-32
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• 2016

Recently, the development of electronic teaching materials and the demand of digital learners have led the needs on the education contents that replace learning from character information and the change of an information design method for this. Chinese character education in the traditional schooling mainly focuses on writing and memorization (semantic memory). This way that the stories do not exist has brought the learners' recognition that Chinese character is difficult to learn. Meanwhile, for a language study such as English, cross-media development between printed materials and audio-visual materials has been actively introduced. The method that extends episode memories along with memorization through a story is widely used. Therefore, this content suggests a prototype, which is broken away from an existing way of learning Chinese character that mainly focuses on writing, one sided instruction and information cramming. This makes learners learn through a story from printed materials and animation. Furthermore, it suggests a method that extends episode memories through Chinese education contents based on IoT explaining the principle of Chinese character by combining IT technology (information and communications, IoT) and education contents on block toys.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.4
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• pp.151-157
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• 2023

RPL (IPv6 Routing Protocol for Low-power Lossy Network) is a standardized routing protocol for LLNs (Low power and Lossy Networks) by the IETF (Internet Engineering Task Force). RPL creates routes and builds a DODAG (Destination Oriented Directed Acyclic Graph) through OF (Objective Function) defining routing metrics and optimization objectives. RPL supports a leaf mode which does not allow any child nodes. In this paper, we propose INFRA-RPL which provides a dynamic leaf mode functionality to a leaf node with the mobility. The proposed protocol is implemented in the open-source IoT operating system, Contiki-NG and Cooja simulator, and its performance is evaluated. The evaluation results show that INFRA-RPL outperforms the existing protocols in the terms of PDR, latency, and control message overhead.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.575-576
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• 2017

Recently, research have smart gateways can provide additional services through the IoT and Big Data. However, the existing System is number of devices connected increases to the Server, the stability of the network is degraded and data security is poor. In this paper, we design a smart gateway VPN tunneling control system based on IoT to solve these problems. we propose an effective VPN tunneling technology for low-end targets such as routers, and a method for efficiently controlling traffic in real-time in an environment where the quality of the Internet line changes dramatically. It is possible to control the sensor in the home safely through the VPN at the remote place.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.49-56
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• 2023

Machine learning methods diversely applied to the Internet of Things (IoT) field have been successful due to the enhancement of computer processing power. They offer an effective way of detecting malicious intrusions in IoT because of their high-level feature extraction capabilities. In this paper, we proposed a novel feature selection method for malicious intrusion detection in IoT by using an evolutionary technique - Genetic Algorithm (GA) and Machine Learning (ML) algorithms. The proposed model is performing the classification of BoT-IoT dataset to evaluate its quality through the training and testing with classifiers. The data is reduced and several preprocessing steps are applied such as: unnecessary information removal, null value checking, label encoding, standard scaling and data balancing. GA has applied over the preprocessed data, to select the most relevant features and maintain model optimization. The selected features from GA are given to ML classifiers such as Logistic Regression (LR) and Support Vector Machine (SVM) and the results are evaluated using performance evaluation measures including recall, precision and f1-score. Two sets of experiments are conducted, and it is concluded that hyperparameter tuning has a significant consequence on the performance of both ML classifiers. Overall, SVM still remained the best model in both cases and overall results increased.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1026-1037
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• 2016

3rd Generation Partnership Project (3GPP) is the progressing standardization of the narrowband IoT (NB-IoT) system to support massive devices for the Internet of Things (IoT) services. The NB-IoT system uses a coverage class technique to increase the performance of the NB-IoT system while serving massive devices in very wide coverage area. A moving device can change the coverage class according to the distance or the channel state between the base station and the moving device. However, in the conventional NB-IoT standard, the performance of the NB-IoT system degrades because the coverage class is changed based on the fixed criterion. This paper proposes the coverage class adaptation schemes to increase the performance of the NB-IoT system by dynamically change the coverage class according to the location or the channel state of the device. Simulation results show that the proposed coverage class adaptation scheme decreases both the signaling overhead and the PDCCH decoding error rate in comparison with the conventional coverage class adaptation scheme in the 3GPP standard.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.95-102
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• 2023

The emergence of Internet of Things (IoT) into our daily lives has grown rapidly. It's been integrated to our homes, cars, and cities, increasing the intelligence of devices involved in communications. Enormous amount of data is exchanged over smart devices through the internet, which raises security concerns in regards of privacy evasion. This paper is focused on the forensics and intrusion detection on one of the most common protocols in IoT environments, especially smart home environments, which is the Message Queuing Telemetry Transport (MQTT) protocol. The paper covers general IoT infrastructure, MQTT protocol and attacks conducted on it, and multiple network forensics frameworks in smart homes. Furthermore, a machine learning model is developed and tested to detect several types of attacks in an IoT network. A forensics tool (MQTTracker) is proposed to contribute to the investigation of MQTT protocol in order to provide a safer technological future in the warmth of people's homes. The MQTT-IOT-IDS2020 dataset is used to train the machine learning model. In addition, different attack detection algorithms are compared to ensure the suitable algorithm is chosen to perform accurate classification of attacks within MQTT traffic.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.5
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• pp.109-116
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• 2016

Today various IoT platforms exist, but most of them only consider IPv6, without other types of network including private network. They support, therefore, the private network to use virtual private network or through the hardware gateway. To solve this limitation, we propose a IoT platform that provides IoT Services on private networks. Also we verify this platform though constructing a testbed.