• Title/Summary/Keyword: 네트워크 계산

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An Approach of Hiding Hangul Secret Message in Image using XNOR-XOR and Fibonacci Technique (XNOR-XOR과 피보나치 기법을 이용하여 이미지에서 한글 비밀 메시 지를 은닉하는 방법)

  • Ji, Seon-su
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.14 no.2
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    • pp.109-114
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    • 2021
  • As various users increase in a network environment, it is difficult to protect sensitive and confidential information transmitted and received from attackers. Concealing bitwise secret data in an image using the LSB technique can be very vulnerable to attack. To solve this problem, a hybrid method that combines encryption and information hiding is used. Therefore, an effective method for users to securely protect secret messages and implement secret communication is required. A new approach is needed to improve security and imperceptibility to ensure image quality. In this paper, I propose an LSB steganography technique that hides Hangul messages in a cover image based on MSB and LSB. At this time, after separating Hangul into chosung, jungsung and jongsung, the secret message is applied with Exclusive-OR or Exclusive-NOR operation depending on the selected MSB. In addition, the calculated secret data is hidden in the LSB n bits of the cover image converted by Fibonacci technique. PSNR was used to confirm the effectiveness of the applied results. It was confirmed 41.517(dB) which is suitable as an acceptable result.

Stateless Randomized Token Authentication for Performance Improvement of OAuth 2.0 MAC Token Authentication (OAuth 2.0 MAC 토큰인증의 효율성 개선을 위한 무상태 난수화토큰인증)

  • Lee, Byoungcheon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.28 no.6
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    • pp.1343-1354
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    • 2018
  • OAuth 2.0 bearer token and JWT(JSON web token), current standard technologies for authentication and authorization, use the approach of sending fixed token repeatedly to server for authentication that they are subject to eavesdropping attack, thus they should be used in secure communication environment such as HTTPS. In OAuth 2.0 MAC token which was devised as an authentication scheme that can be used in non-secure communication environment, server issues shared secret key to authenticated client and the client uses it to compute MAC to prove the authenticity of request, but in this case server has to store and use the shared secret key to verify user's request. Therefore, it's hard to provide stateless authentication service. In this paper we present a randomized token authentication scheme which can provide stateless MAC token authentication without storing shared secret key in server side. To remove the use of HTTPS, we utilize secure communication using server certificate and simple signature-based login using client certificate together with the proposed randomized token authentication to achieve the fully stateless authentication service and we provide an implementation example.

A Study on Consensus Algorithm based on Blockchain (블록체인 기반 합의 알고리즘 연구)

  • Yoo, Soonduck
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.3
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    • pp.25-32
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    • 2019
  • The core of the block chain technology is solving the problem of agreement on double payment, and the PoW, PoS and DPoS algorithms used for this have been studied. PoW in-process proofs are consensus systems that require feasible efforts to prevent minor or malicious use of computing capabilities, such as sending spam e-mail or initiating denial of service (DoS) attacks. The proof of the PoS is made to solve the Nothing at stake problem as well as the energy waste of the proof of work (PoW) algorithm, and the decision of the sum of each node is decided according to the amount of money, not the calculation ability. DPoS is that a small number of authorized users maintain a trade consensus through a distributed network, whereas DPS provides consent authority to a small number of representatives, whereas PoS has consent authority to all users. If PoS is direct democracy, DPoS is indirect democracy. This study aims to contribute to the continuous development of the related field through the study of the algorithm of the block chain agreement.

Personalized Recommendation Considering Item Confidence in E-Commerce (온라인 쇼핑몰에서 상품 신뢰도를 고려한 개인화 추천)

  • Choi, Do-Jin;Park, Jae-Yeol;Park, Soo-Bin;Lim, Jong-Tae;Song, Je-O;Bok, Kyoung-Soo;Yoo, Jae-Soo
    • The Journal of the Korea Contents Association
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    • v.19 no.3
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    • pp.171-182
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    • 2019
  • As online shopping malls continue to grow in popularity, various chances of consumption are provided to customers. Customers decide the purchase by exploiting information provided by shopping malls such as the reviews of actual purchasing users, the detailed information of items, and so on. It is required to provide objective and reliable information because customers have to decide on their own whether the massive information is credible. In this paper, we propose a personalized recommendation method considering an item confidence to recommend reliable items. The proposed method determines user preferences based on various behaviors for personalized recommendation. We also propose an user preference measurement that considers time weights to apply the latest propensity to consume. Finally, we predict the preference score of items that have not been used or purchased before, and we recommend items that have highest scores in terms of both the predicted preference score and the item confidence score.

Analysis of Blood pressure influence factor Correction for Photoplethysmography Fusion Algorithm Calibration (광전용적맥파 융합 알고리즘 보정을 위한 혈압 영향인자 상관관계 분석)

  • Kim, Seon-Chil
    • Journal of the Korea Convergence Society
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    • v.10 no.2
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    • pp.67-73
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    • 2019
  • The blood pressure measurement is calculated as a value corresponding to the pressure of the blood vessel using the pressure from the outside for a long time. Due to the recent miniaturization of measurement equipment and the ICT combination of personal healthcare systems, a system that enables continuous and real-time measurement of blood pressure with a sensor is required. In this study, blood pressure was measured using pulse transit time using Photoplethysmography. In this study, blood pressure was estimated by using systolic blood pressure. And it is possible to make measurement only with PPG itself, which can contribute to making a micro blood pressure measuring device. As a result, systolic blood pressure and PPG's S1-P and P-S2 were used to analyze the possibility of blood pressure estimation.

An Attribute-Based Authentication Scheme Using Smart Cards (스마트카드를 이용한 속성기반 사용자 인증 스킴)

  • Yoo, Hye-Joung;Rhee, Hyun-Sook
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.18 no.5
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    • pp.41-47
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    • 2008
  • In a network environment, when a user requests a server's service, he/she must pass an examination of user authentication. Through this process, the server can determine if the user can use the provided services and the exact access rights of this user in these services. In these authentication schemes, the security of private information became an important issue. For this reason, many suggestions have been made in order to protect the privacy of users and smart cards have been widely used for authentication systems providing anonymity of users recently. An remote user authentication system using smart cards is a very practical solution to validate the eligibility of a user and provide secure communication. However, there are no studies in attribute-based authentication schemes using smart cards so far. In this paper, we propose a novel user authentication scheme using smart cards based on attributes. The major merits include : (1) the proposed scheme achieves the low-computation requirement for smart cards; (2) user only needs to register once and can use permitted various services according to attributes; (3) the proposed scheme guarantees perfect anonymity to remote server.

Development of medical bed system equipped with body pressure sensors (체압센서를 장착한 의료용 침대 시스템의 개발)

  • Seon, Minju;Lee, Youngdae
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.1
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    • pp.646-653
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    • 2021
  • The medical bed developed in this study consists of N keys and each is driven vertically by an actuator. Since M sensors are mounted on each keyboard to measure body pressure, the resolution of the body pressure map is determined by the MN. A sensor controller is mounted on each keyboard, and the body pressure values measured from M sensors are transmitted to the main controller through a serial communication network such as CAN (Car Area Network). Each keyboard is equipped with a servo driver that drives a motor, and it is connected to the main controller via CAN to control the height of the keyboard according to the displacement value indicated by the main controller. In addition, the maximum body pressure value and body pressure ratio applied to each part of the keyboard are calculated and used as the basic data for controlling bed comfort by artificial intelligence. As a result, the proposed system can be a foundation that can be used for the control of body comfort and pressure sore prevention by artificial intelligence to be developed in the future.

Partial Offloading System of Multi-branch Structures in Fog/Edge Computing Environment (FEC 환경에서 다중 분기구조의 부분 오프로딩 시스템)

  • Lee, YonSik;Ding, Wei;Nam, KwangWoo;Jang, MinSeok
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.10
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    • pp.1551-1558
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    • 2022
  • We propose a two-tier cooperative computing system comprised of a mobile device and an edge server for partial offloading of multi-branch structures in Fog/Edge Computing environments in this paper. The proposed system includes an algorithm for splitting up application service processing by using reconstructive linearization techniques for multi-branch structures, as well as an optimal collaboration algorithm based on partial offloading between mobile device and edge server. Furthermore, we formulate computation offloading and CNN layer scheduling as latency minimization problems and simulate the effectiveness of the proposed system. As a result of the experiment, the proposed algorithm is suitable for both DAG and chain topology, adapts well to different network conditions, and provides efficient task processing strategies and processing time when compared to local or edge-only executions. Furthermore, the proposed system can be used to conduct research on the optimization of the model for the optimal execution of application services on mobile devices and the efficient distribution of edge resource workloads.

Dynamic Adjustment of the Pruning Threshold in Deep Compression (Deep Compression의 프루닝 문턱값 동적 조정)

  • Lee, Yeojin;Park, Hanhoon
    • Journal of the Institute of Convergence Signal Processing
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    • v.22 no.3
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    • pp.99-103
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    • 2021
  • Recently, convolutional neural networks (CNNs) have been widely utilized due to their outstanding performance in various computer vision fields. However, due to their computational-intensive and high memory requirements, it is difficult to deploy CNNs on hardware platforms that have limited resources, such as mobile devices and IoT devices. To address these limitations, a neural network compression research is underway to reduce the size of neural networks while maintaining their performance. This paper proposes a CNN compression technique that dynamically adjusts the thresholds of pruning, one of the neural network compression techniques. Unlike the conventional pruning that experimentally or heuristically sets the thresholds that determine the weights to be pruned, the proposed technique can dynamically find the optimal thresholds that prevent accuracy degradation and output the light-weight neural network in less time. To validate the performance of the proposed technique, the LeNet was trained using the MNIST dataset and the light-weight LeNet could be automatically obtained 1.3 to 3 times faster without loss of accuracy.

Multiple Binarization Quadtree Framework for Optimizing Deep Learning-Based Smoke Synthesis Method

  • Kim, Jong-Hyun
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.4
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    • pp.47-53
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    • 2021
  • In this paper, we propose a quadtree-based optimization technique that enables fast Super-resolution(SR) computation by efficiently classifying and dividing physics-based simulation data required to calculate SR. The proposed method reduces the time required for quadtree computation by downscaling the smoke simulation data used as input data. By binarizing the density of the smoke in this process, a quadtree is constructed while mitigating the problem of numerical loss of density in the downscaling process. The data used for training is the COCO 2017 Dataset, and the artificial neural network uses a VGG19-based network. In order to prevent data loss when passing through the convolutional layer, similar to the residual method, the output value of the previous layer is added and learned. In the case of smoke, the proposed method achieved a speed improvement of about 15 to 18 times compared to the previous approach.