• Title/Summary/Keyword: 의료 정보 보안

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A new type of lightweight stream encryption algorithm motif for applying low capacity messaging data encryption for IoT / QR / electronic tags (IoT/QR/전자태그용 저용량 메시지 데이터 암호화 적용을 위한 새로운 방식의 스트림 경량 암호화 알고리즘 모티브 제안)

  • Kim, Jung-Hoon
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.10 no.1
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    • pp.46-56
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    • 2017
  • Recently, the spread of IoT technology has been spreading, and it has been applied to all industrial fields such as home / home appliance / medical care. Due to the low specification, low power consumption characteristic and communication data characteristic of IoT, implementation of existing algorithm is difficult thing. From this reason, we have proposed for the first time that encryption and decryption can be proceeded by introducing a kind of variable length bit XOR operation method which changes a variable the bit length value by using carry up and carry down method. We confirmed the practicality of encrypting short message data frequently processed by IoT device / QR code / RFID / NFC without changing the size of data before and after encryption.

X-ray Image Denoising Agorithm Using Bilateral Weight (양방향 가중치를 이용한 x선 영상 잡음 제거 알고리즘)

  • Shin, Soo-Yeon;Suh, Jae-Won
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.1
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    • pp.137-143
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    • 2017
  • X-ray image is a widely used to medical examination, airport security and cargo inspection. However, X-ray images contain many visual noise, which interrupt image analysis. Consequently, it is primary importance to reduce noises of X-ray image. In this paper, we present a improved denoise technique for x-ray image using pixel value and range weights. First, we denoise a x-ray image using bilateral filter. Next, we detect a edge region of the original x-ray image. If a denoised pixel belongs to the edge region, we calculate weighting values of original x-ray image and denoised x-ray image in $3{\times}3$ neighboring pixels and compute the cost value to determine the boundary pixel value. Finally, the pixel value having minimum cost is determined as the pixel value of the denoised x-ray image. Simulation results show that the proposed algorithm achieves good performance in terns of PSNR comparison and subjective visual quality.

New Sequential Clustering Combination for Rule Generation System (규칙 생성 시스템을 위한 새로운 연속 클러스터링 조합)

  • Kim, Sung Suk;Choi, Ho Jin
    • Journal of Internet Computing and Services
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    • v.13 no.5
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    • pp.1-8
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    • 2012
  • In this paper, we propose a new clustering combination based on numerical data driven for rule generation mechanism. In large and complicated space, a clustering method can obtain limited performance results. To overcome the single clustering method problem, hybrid combined methods can solve problem to divided simple cluster estimation. Fundamental structure of the proposed method is combined by mountain clustering and modified Chen clustering to extract detail cluster information in complicated data distribution of non-parametric space. It has automatic rule generation ability with advanced density based operation when intelligent systems including neural networks and fuzzy inference systems can be generated by clustering results. Also, results of the mechanism will be served to information of decision support system to infer the useful knowledge. It can extend to healthcare and medical decision support system to help experts or specialists. We show and explain the usefulness of the proposed method using simulation and results.

Biometrics System Technology Trends Based on Biosignal (생체신호 기반 바이오인식 시스템 기술 동향)

  • Choi, Gyu-Ho;Moon, Hae-Min;Pan, Sung-Bum
    • Journal of Digital Convergence
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    • v.15 no.1
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    • pp.381-391
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    • 2017
  • Biometric technology is a technology for authenticating a user using the physical or behavioral features of the inherent characteristics of the individual. With the necessity and efficiency of the technology in the fields of finance, security, access control, medical welfare, inspection, and entertainment, the service range has been expanding. Biometrics using biometric information such as fingerprints and faces have been exposed to counterfeit and disguised threats and become a social problem. Recent studies using a bio-signal from the inside of the body other than the bio-information of the external body are being developed. This paper analyzes the recent research and technology of biometric systems using bio-signals, ECG, heart sounds, EEG, and EMG to present the skills needed for the development direction. In the future, utilizing the deep learning to build and analyze database to manage bio-signal based big data for the complex condition of individuals, biometrics technologies suitable for real time environment are expected to be researched.

Distributed Time Division Piconet Coexistence Using Local Time Offset Exchange (로컬 오프셋을 이용한 분산 시간 분리 피코넷 충돌회피 방법론)

  • Park, Yongsuk
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.6
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    • pp.1447-1453
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    • 2014
  • Wireless Body Area Networks (WBAN), standardized as IEEE 802.15.6, enable digital devices on/around the human body to communicate with one another. WBAN is essentially a person's piconet consisting of a master (mobile) device and several slave devices, which follows his/her mobility pattern, and hence, occasionally collides with another piconet as people meet or pass by. As such, a mechanism to detect collision and avoid interference is needed for intra-piconet communications. In this paper, we focus on this notorious problem of piconet collision and propose Distributed Time Division Piconet Coexistence (DTDPC) using local time offset exchange as a simple, attractive solution. The proposed DTDPC provides different level of services for various applications. Besides our simulation results have shown that the proposed solution outperforms the conventional CSMA protocols.

Finding Industries for Big Data Usage on the Basis of AHP (AHP 기반의 빅데이터 활용을 위한 산업 탐색)

  • Lee, Sang-Won;Kim, Sung-Hyun
    • Journal of Digital Convergence
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    • v.14 no.7
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    • pp.21-27
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    • 2016
  • Big Data is gathering all the attention from every business community. Pervasive use of machine-to-machine (M2M) applications and mobile devices bring an explosion of data. By analyzing this data, the private and public sectors can benefit in the areas of cost reduction and productivity. The Korean government is actively pursuing Big Data initiatives to promote its usage. This paper aims to select industries which fit for the development of Big Data with a verification of the experts. The analytic hierarchy process (AHP) is applied to systematically derive the opinion of more than 50 professionals. Medical / welfare, transportation / warehousing, information and communications / information security, energy, the financial sector have been identified as promising industries. The results can be utilized in developing Big Data best practices thus contributing industrial development.

Case Analysis for Introduction of Machine Learning Technology to the Mining Industry (머신러닝 기술의 광업 분야 도입을 위한 활용사례 분석)

  • Lee, Chaeyoung;Kim, Sung-Min;Choi, Yosoon
    • Tunnel and Underground Space
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    • v.29 no.1
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    • pp.1-11
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    • 2019
  • This study investigated use cases of machine learning technology in domestic medical, manufacturing, finance, automobile, urban sectors and those in overseas mining industry. Through a literature survey, it was found that the machine learning technology has been widely utilized for developing medical image information system, real-time monitoring and fault diagnosis system, security level of information system, autonomous vehicle and integrated city management system. Until now, the use cases have not found in the domestic mining industry, however, several overseas projects have found that introduce the machine learning technology to the mining industry for improving the productivity and safety of mineral exploration or mine development. In the future, the introduction of the machine learning technology to the mining industry is expected to spread gradually.

Efficient Deep Neural Network Architecture based on Semantic Segmentation for Paved Road Detection (효율적인 비정형 도로영역 인식을 위한 Semantic segmentation 기반 심층 신경망 구조)

  • Park, Sejin;Han, Jeong Hoon;Moon, Young Shik
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.11
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    • pp.1437-1444
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    • 2020
  • With the development of computer vision systems, many advances have been made in the fields of surveillance, biometrics, medical imaging, and autonomous driving. In the field of autonomous driving, in particular, the object detection technique using deep learning are widely used, and the paved road detection is a particularly crucial problem. Unlike the ROI detection algorithm used in general object detection, the structure of paved road in the image is heterogeneous, so the ROI-based object recognition architecture is not available. In this paper, we propose a deep neural network architecture for atypical paved road detection using Semantic segmentation network. In addition, we introduce the multi-scale semantic segmentation network, which is a network architecture specialized to the paved road detection. We demonstrate that the performance is significantly improved by the proposed method.

Study on the Positioning Method using BLE for Location based AIoT Service (위치 기반 지능형 사물인터넷 서비스를 위한 BLE 측위 방법에 관한 연구)

  • Ho-Deok Jang
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.17 no.1
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    • pp.25-30
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    • 2024
  • Smart City, a key application area of the AIoT (Artificial Intelligence of Things), provides various services in safety, security, and healthcare sectors through location tracking and location-based services. an IPS (Indoor Positioning System) is required to implement location-based services, and wireless communication technologies such as WiFi, UWB (Ultra-wideband), and BLE (Bluetooth Low Energy) are being applied. BLE, which enables data transmission and reception with low power consumption, can be applied to various IoT devices such as sensors and beacons at a low cost, making it one of the most suitable wireless communication technologies for indoor positioning. BLE utilizes the RSSI (Received Signal Strength Indicator) to estimate the distance, but due to the influence of multipath fading, which causes variations in signal strength, it results in an error of several meters. In this paper, we conducted research on a path loss model that can be applied to BLE IPS for proximity services, and confirmed that optimizing the free space propagation loss coefficient can reduce the distance error between the Tx and Rx devices.

A Study on Key Protection Method based on WhiteBox Cipher in Block Chain Environment (블록체인 환경에서 화이트박스 암호기반 키 보호 기법에 관한 연구)

  • Choi, Do-Hyeon;Hong, Chan-Ki
    • Journal of Convergence for Information Technology
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    • v.9 no.10
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    • pp.9-15
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    • 2019
  • Recently, in the field of next-generation e-commerce and finance, interest in blockchain-based technologies such as Bitcoin and Ethereum is great. Although the security of blockchain technology is known to be secure, hacking incidents / accidents related to cryptocurrencies are being issued. The main causes were vulnerabilities in the external environment, such as taking over login sessions on cryptocurrency wallets, exposing private keys due to malware infection, and using simple passwords. However, private key management recommends general methods such as utilizing a dedicated application or local backup and physical archiving through document printing. In this paper, we propose a white box password-based private key protection scheme. As a result of safety and performance analysis, we strengthened the security against vulnerability of private key exposure and proved the processing efficiency of existing protocol.