• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.738-741
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• 2012

한국정보통신기술협회(TTA)에서 표준 제안한 WBAN(Wireless Body Area Network)은 인체 내부 통신(in-body or implant)과, 인체 외부 통신(on-body)통신으로 구분하고 있다. 생체측정 정보 중 체온, 호흡, 맥박, 운동량, 심박의 부분적인 데이터 수집을 바탕으로 환자의 생체정보 데이터를 수합 후 데이터 프레임구조로 변환하여 스마트모바일 애플리케이션 환경에서 사용자가 모바일기기 화면에 정보를 표시 할 수 있다. 이렇게 표시된 정보들은 환자의 상태를 실시간으로 자신의 스마트모바일을 이용하여 확인할 수 있으며, 이러한 정보를 보호하고 의료기관에 전송하기 위한 방법으로 국제표준암호알고리즘인 HIGHT 알고리즘을 적용하여 생체정보 데이터의 부분 암호화 적용을 설계 하였다. 이를 통해 의료기관의 인증서버에 대한 부하 감소 및 환자의 생체정보의 보안 강화를 제시한다.

• ETRI Journal
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• v.40 no.6
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• pp.745-758
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• 2018

A wide range of studies in various disciplines has focused on the Internet of Things (IoT) and cyber-physical systems (CPS). However, it is necessary to summarize the current status and to establish future directions because each study has its own individual goals independent of the completion of all IoT applications. The absence of a comprehensive understanding of IoT and CPS has disrupted an efficient resource allocation. To assess changes in the knowledge structure and emerging technologies, this study explores the dynamic research trends in IoT by analyzing bibliographic data. We retrieved 54,237 keywords in 12,600 IoT studies from the Scopus database, and conducted keyword frequency, co-occurrence, and growth-rate analyses. The analysis results reveal how IoT technologies have been developed and how they are connected to each other. We also show that such technologies have diverged and converged simultaneously, and that the emerging keywords of trust, smart home, cloud, authentication, context-aware, and big data have been extracted. We also unveil that the CPS is directly involved in network, security, management, cloud, big data, system, industry, architecture, and the Internet.

• Current Optics and Photonics
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• v.6 no.6
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• pp.565-575
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• 2022

In this paper, we propose a non-fungible token (NFT) transaction method that can commercialize the real 3D property and make property sharing possible using the 3D reconstruction technique. In addition, our proposed method enhances the security of NFT copyright and metadata by using optical encryption. In general, a conventional NFT is used for 2D image proprietorial rights. To expand the scope of the use of tokens, many cryptocurrency industries are currently trying to apply tokens to real three-dimensional (3D) property. However, many token markets have an art copyright problem. Many tokens have been minted without considering copyrights. Therefore, tokenizing real property can cause significant social issues. In addition, there are not enough methods to mint 3D real property for NFT commercialization and sharing property tokens. Therefore, we propose a new token management technique to solve these problems using integral imaging and double random phase encryption. To show our system, we conduct a private NFT market using a test blockchain network that can demonstrate the whole NFT transaction process.

• The Journal of Industrial Distribution & Business
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• v.13 no.10
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• pp.15-22
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• 2022

Purpose: In the manufacturing sector, VDI (Virtual Desktop Infrastructure) offers advantages to the organizations, such as allowing manufacturers access to the system from any location. The most important things are understanding what the user needs, avoiding under-provisioning, network preparation. This research is to provide useful practical l implementations of VDI in manufacturing industry based on numerous prior studies. Research design, data and methodology: This research has conducted the qualitative content analysis (QCA). When conducting this research, the present author assumed that it is crucial to create the procedures and processes that will be used to acquire the text data needed to structure or solve problems. Results: According to the prior literature analysis, there are five suggestions to implement successful VDI for manufacturing sector. The five solutions are (1) Creation of the machines, (2) Direct users to an available 'Virtual Machine', (3) 'Virtual Machine Power Management', (4) Performance monitoring, and (5) Review security. Conclusions: The research clearly details how VDI can be implemented on a manufacturer platform and how it can be connected to hundreds of users. The author can conclude that connecting hundreds of users can be done using the remote connection of devices and encourage manufacturers to work from different areas.

• Review of KIISC
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• v.32 no.4
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• pp.7-17
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• 2022

운전자 보조 시스템을 통한 차량의 전자적인 제어를 위하여, 최근 차량에 탑재된 전자 제어 장치 (ECU; Electronic Control Unit)의 개수가 급증하고 있다. ECU는 효율적인 통신을 위해서 차량용 내부 네트워크인 CAN(Controller Area Network)을 이용한다. 하지만 CAN은 기밀성, 무결성, 접근 제어, 인증과 같은 보안 메커니즘이 고려되지 않은 상태로 설계되었기 때문에, 공격자가 네트워크에 쉽게 접근하여 메시지를 도청하거나 주입할 수 있다. 악의적인 메시지 주입은 차량 운전자 및 동승자의 안전에 심각한 피해를 안길 수 있기에, 최근에는 주입된 메시지를 식별하기 위한 침입 탐지 시스템(IDS; Intrusion Detection System)에 대한 연구가 발전해왔다. 특히 최근에는 AI(Artificial Intelligence) 기술을 이용한 IDS가 다수 제안되었다. 그러나 제안되는 기법들은 특정 공격 데이터셋에 한하여 평가되며, 각 기법에 대한 탐지 성능이 공정하게 평가되었는지를 확인하기 위한 평가 프레임워크가 부족한 상황이다. 따라서 본 논문에서는 machine learning/deep learning에 기반하여 제안된 차랑용 IDS 5가지를 선정하고, 기존에 공개된 데이터셋을 이용하여 제안된 기법들에 대한 비교 및 평가를 진행한다. 공격 데이터셋에는 CAN의 대표적인 4가지 공격 유형이 포함되어 있으며, 추가적으로 본 논문에서는 메시지 주기 유형을 활용한 공격 유형을 제안하고 해당 공격에 대한 탐지 성능을 평가한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1671-1686
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• 2022

Face manipulation tools represented by Deepfake have threatened the security of people's biological identity information. Particularly, manipulation tools with deep learning technology have brought great challenges to Deepfake detection. There are many solutions for Deepfake detection based on traditional machine learning and advanced deep learning. However, those solutions of detectors almost have problems of poor performance when evaluated on different quality datasets. In this paper, for the sake of making high-quality Deepfake datasets, we provide a preprocessing method based on the image pixel matrix feature to eliminate similar images and the residual channel attention network (RCAN) to resize the scale of images. Significantly, we also describe a Deepfake detector named Cascaded-Hop which is based on the PixelHop++ system and the successive subspace learning (SSL) model. By feeding the preprocessed datasets, Cascaded-Hop achieves a good classification result on different manipulation types and multiple quality datasets. According to the experiment on FaceForensics++ and Celeb-DF, the AUC (area under curve) results of our proposed methods are comparable to the state-of-the-art models.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.126-134
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• 2023

Drones are emerging as a new security threat, and the world is working to reduce them. Detection and identification are the most difficult and important parts of the anti-drone systems. Existing detection and identification methods each have their strengths and weaknesses, so complementary operations are required. Detection and identification performance in anti-drone systems can be improved through the use of artificial intelligence. This is because artificial intelligence can quickly analyze differences smaller than humans. There are three ways to utilize artificial intelligence. Through reinforcement learning-based physical control, noise and blur generated when the optical camera tracks the drone may be reduced, and tracking stability may be improved. The latest NeRF algorithm can be used to solve the problem of lack of enemy drone data. It is necessary to build a data network to utilize artificial intelligence. Through this, data can be efficiently collected and managed. In addition, model performance can be improved by regularly generating artificial intelligence learning data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.494-510
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• 2024

Internet users are exposed to sophisticated cyberattacks that intrusion detection systems have difficulty detecting. Therefore, research is increasing on intrusion detection methods that use artificial intelligence technology for detecting novel cyberattacks. Unsupervised learning-based methods are being researched that learn only from normal data and detect abnormal behaviors by finding patterns. This study developed an anomaly-detection method based on unsupervised machines and deep learning for a network intrusion detection system (NIDS). We present a hybrid anomaly detection approach based on unsupervised learning techniques using the autoencoder (AE), Isolation Forest (IF), and Local Outlier Factor (LOF) algorithms. An oversampling approach that increased the detection rate was also examined. A hybrid approach that combined deep learning algorithms and traditional machine learning algorithms was highly effective in setting the thresholds for anomalies without subjective human judgment. It achieved precision and recall rates respectively of 88.2% and 92.8% when combining two AEs, IF, and LOF while using an oversampling approach to learn more unknown normal data improved the detection accuracy. This approach achieved precision and recall rates respectively of 88.2% and 94.6%, further improving the detection accuracy compared with the hybrid method. Therefore, in NIDS the proposed approach provides high reliability for detecting cyberattacks.

• The Transactions of the Korea Information Processing Society
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• v.5 no.6
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• pp.1593-1602
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• 1998

In this paper, a hybrid firewall system using the screening router, dual-homed gateway, screened host galeway and the application level gateway is proposed, The screened host gateway is comjXlsed of screening router, DMZ and bastion host. All external input traffics are filtered by screening router with network protrcol filtering, and transmitted to the bastion host performing application level filtering, The dual homed gateway is an internlediate equipment prohibiting direct access from external users, The application level gateway is an equipment enabling transmission using only the proxy server. External users can access only through the public servers in the DMZ, but internal users can aeee through any servers, The rule base which allows Telnet only lo the adrnilllslratol is applied to manage hosts in the DMZ According to the equipmental results, denial of access was in orderof Web. Mail FTP, and Telnet. Access to another servers except for server in DMZ were denied, Prolocol c1mials of UDP was more than that of TCP, because the many hosts broadcasted to networds using BOOTP and NETBIOS, Also, the illegal Telnet and FTP that transfer to inside network were very few.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.1
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• pp.49-57
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• 2016

Recently, marine accidents such as the sinking accident Mongol freighter ship and the sinking accident of Sewol ferry in Jindo continuously happen. In order to decrease the number of these marine accidents, Korean ships are obliged to follow the AIS(Automatic Identification System) system. The AIS protocol includes all information for sailing ships. However, the standard AIS protocol does not provide any security function, In addition, it is possible to hijack the standard AIS protocol in case of using a satellite communication device called FUNcuve Dongle Pro+. Therefore, this paper analyzes weak points of the security in the standard AIS protocol. Furthermore, this paper ensures reliability by marking the MAC Address of sender and receiver for secure communication and suggests the protocol that can securely send data, using the VPN Tunnelling method. Therefore, the suggested AIS protocol provides the secure communication to the AIS protocol and protect the messages in the AIS protocol, which can serve safe voyages by decreasing the marine accidents.