• Title/Summary/Keyword: network security

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GP Modeling of Nonlinear Electricity Demand Pattern based on Machine Learning (기계학습 기반 비선형 전력수요 패턴 GP 모델링)

  • Kim, Yong-Gil
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.3
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    • pp.7-14
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    • 2021
  • The emergence of the automated smart grid has become an essential device for responding to these problems and is bringing progress toward a smart grid-based society. Smart grid is a new paradigm that enables two-way communication between electricity suppliers and consumers. Smart grids have emerged due to engineers' initiatives to make the power grid more stable, reliable, efficient and safe. Smart grids create opportunities for electricity consumers to play a greater role in electricity use and motivate them to use electricity wisely and efficiently. Therefore, this study focuses on power demand management through machine learning. In relation to demand forecasting using machine learning, various machine learning models are currently introduced and applied, and a systematic approach is required. In particular, the GP learning model has advantages over other learning models in terms of general consumption prediction and data visualization, but is strongly influenced by data independence when it comes to prediction of smart meter data.

Path selection algorithm for multi-path system based on deep Q learning (Deep Q 학습 기반의 다중경로 시스템 경로 선택 알고리즘)

  • Chung, Byung Chang;Park, Heasook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.1
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    • pp.50-55
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    • 2021
  • Multi-path system is a system in which utilizes various networks simultaneously. It is expected that multi-path system can enhance communication speed, reliability, security of network. In this paper, we focus on path selection in multi-path system. To select optimal path, we propose deep reinforcement learning algorithm which is rewarded by the round-trip-time (RTT) of each networks. Unlike multi-armed bandit model, deep Q learning is applied to consider rapidly changing situations. Due to the delay of RTT data, we also suggest compensation algorithm of the delayed reward. Moreover, we implement testbed learning server to evaluate the performance of proposed algorithm. The learning server contains distributed database and tensorflow module to efficiently operate deep learning algorithm. By means of simulation, we showed that the proposed algorithm has better performance than lowest RTT about 20%.

Web Monitoring based Encryption Web Traffic Attack Detection System (웹 모니터링 기반 암호화 웹트래픽 공격 탐지 시스템)

  • Lee, Seokwoo;Park, Soonmo;Jung, Hoekyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.3
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    • pp.449-455
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    • 2021
  • This paper proposes an encryption web transaction attack detection system based on the existing web application monitoring system. Although there was difficulty in detecting attacks on the encrypted web traffic because the existing web traffic security systems detect and defend attacks based on encrypted packets in the network area of the encryption section between the client and server, by utilizing the technology of the web application monitoring system, it is possible to detect various intelligent cyber-attacks based on information that is already decrypted in the memory of the web application server. In addition, since user identification is possible through the application session ID, statistical detection of attacks such as IP tampering attacks, mass web transaction call users, and DDoS attacks are also possible. Thus, it can be considered that it is possible to respond to various intelligent cyber attacks hidden in the encrypted traffic by collecting and detecting information in the non-encrypted section of the encrypted web traffic.

Machine Learning Assisted Information Search in Streaming Video (기계학습을 이용한 동영상 서비스의 검색 편의성 향상)

  • Lim, Yeon-sup
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.3
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    • pp.361-367
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    • 2021
  • Information search in video streaming services such as YouTube is replacing traditional information search services. To find desired detailed information in such a video, users should repeatedly navigate several points in the video, resulting in a waste of time and network traffic. In this paper, we propose a method to assist users in searching for information in a video by using DBSCAN clustering and LSTM. Our LSTM model is trained with a dataset that consists of user search sequences and their final target points categorized by DBSCAN clustering algorithm. Then, our proposed method utilizes the trained model to suggest an expected category for the user's desired target point based on a partial search sequence that can be collected at the beginning of the search. Our experiment results show that the proposed method successfully finds user destination points with 98% accuracy and 7s of the time difference by average.

Transaction Model Suggestion by using Two Enforcements with a Blockchain based on a Service Platform (서비스 플랫폼 기반 이중강화적용 블록체인 응용 거래모델 제안)

  • Lee, Kwan Mok;Kim, Yong Hwan;Bae, Ki Tae
    • Smart Media Journal
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    • v.9 no.4
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    • pp.91-96
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    • 2020
  • A blockchain is a technology in which all nodes participating in a distributed network manage each transaction's contents without a central server managing the transaction, which is a record of the transaction. The block containing the transaction record of a specific period is connected to the blockchain by referring to the hash value for the previous block, and the chain with the new block added is shared with all nodes again. Transactions using existing certificates will pass through FinTech, and in the near future, applications using blockchains are expected to emerge. In this study, we analyze the problems of the existing model, and propose a transaction model that applies the blockchain to come. Among various applications, this study develops a trading model targeting the energy sales market among the topics that will lead the fourth industrial revolution. As a result of analyzing the proposed model, it was possible to be sure of the possibility of a safer energy sales transaction than the existing method.

Development of an intelligent edge computing device equipped with on-device AI vision model (온디바이스 AI 비전 모델이 탑재된 지능형 엣지 컴퓨팅 기기 개발)

  • Kang, Namhi
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.5
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    • pp.17-22
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    • 2022
  • In this paper, we design a lightweight embedded device that can support intelligent edge computing, and show that the device quickly detects an object in an image input from a camera device in real time. The proposed system can be applied to environments without pre-installed infrastructure, such as an intelligent video control system for industrial sites or military areas, or video security systems mounted on autonomous vehicles such as drones. The On-Device AI(Artificial intelligence) technology is increasingly required for the widespread application of intelligent vision recognition systems. Computing offloading from an image data acquisition device to a nearby edge device enables fast service with less network and system resources than AI services performed in the cloud. In addition, it is expected to be safely applied to various industries as it can reduce the attack surface vulnerable to various hacking attacks and minimize the disclosure of sensitive data.

Anonymous Blockchain Voting Model using the Master Node Network (마스터 노드 네트워크를 사용한 블록체인 익명 투표 모델)

  • Cho, Jae-Han;Lee, Lee-Sub;Choi, Chang-Hoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.5
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    • pp.394-402
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    • 2021
  • Electronic voting systems have been widely used in many countries around the world since the mid-1990s. In recent years, studies have applied blockchain to existing electronic voting systems in order to provide reliability, fairness, and transparency for voters. This approach is highly useful as a technology that promotes decentralized citizen participation. However, the existing electronic voting systems using blockchain have not sufficiently considered anonymity. Lack of anonymity acts as an important constraint in cases of small- and medium-sized voting, which is often required in decentralized citizen participation. In this study, we propose a model that provides anonymity to a voting system using blockchain by applying the concept of the master node in Dash cryptocurrency. First, we define the differences in the requirements of the transfer and voting systems in blockchain. We propose a parallel and autonomous model and algorithm to provide anonymity in the blockchain-that is, a decentralized development environment. In addition, a discussion of security and the environment for the proposed model is described.

Two-dimensional OCDMA Encoder/Decoder Composed of Double Ring Add/Drop Filters and All-pass Delay Filters (이중 링 Add/Drop 필터와 All-pass 지연 필터로 구성된 이차원 OCDMA 인코더/디코더)

  • Chung, Youngchul
    • Korean Journal of Optics and Photonics
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    • v.33 no.3
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    • pp.106-112
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    • 2022
  • A two-dimensional optical code division multiple access (OCDMA) encoder/decoder, which is composed of add/drop filters and all-pass filters for delay operation, is proposed. An example design is presented, and its feasibility is illustrated through numerical simulations. The chip area of the proposed OCDMA encoder/decoder could be about one-third that of a previous OCDMA device employing delay waveguides. Its performance is numerically investigated using the transfer-matrix method combined with the fast Fourier transform. The autocorrelation peak level over the maximum cross-correlation level for incorrect wavelength hopping and spectral phase code combinations is greater than 3 at the center of the correctly decoded pulse, which assures a bit error rate lower than 10-3, corresponding to the forward error-correction limit.

A Comparative Analysis of Research Trends in the Information and Communication Technology Field of South and North Korea Using Data Mining

  • Jiwan Kim;Hyunkyoo Choi;Jeonghoon Mo
    • Journal of Information Science Theory and Practice
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    • v.11 no.1
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    • pp.14-30
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    • 2023
  • The purpose of this study is to compare research trends in the information and communication technology (ICT) field between North and South Korea and analyze the differences by using data mining. Frequency analysis, clustering, and network analysis were performed using keywords from seven South Korean and two North Korean ICT academic journals published for five years (2015-2019). In the case of South Korea (S. Korea), the frequency of research on image processing and wireless communication was high at 16.7% and 16.3%, respectively. North Korea (N. Korea) had a high frequency of research, in the order of 18.2% for image processing, 16.9% for computer/Internet applications/security, and 16.4% for industrial technology. N. Korea's natural language processing (NLP) sector was 11.9%, far higher than S. Korea's 0.7 percent. Student education is a unique subject that is not clustered in S. Korea. In order to promote exchanges between the two Koreas in the ICT field, the following specific policies are proposed. Joint research will be easily possible in the image processing sector, with the highest research rate in both Koreas. Technical cooperation of medical images is required. If S. Korea's high-quality image source is provided free of charge to N. Korea, research materials can be enriched. In the field of NLP, it calls for proposing exchanges such as holding a Korean language information conference, developing a Korean computer operating system. The field of student education encourages support for remote education contents and management know-how, as well as joint research on student remote evaluation.

Fusion of Blockchain-IoT network to improve supply chain traceability using Ethermint Smart chain: A Review

  • George, Geethu Mary;Jayashree, LS
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.11
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    • pp.3694-3722
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    • 2022
  • In today's globalized world, there is no transparency in exchanging data and information between producers and consumers. However, these tasks experience many challenges, such as administrative barriers, confidential data leakage, and extensive time delays. To overcome these challenges, we propose a decentralized, secured, and verified smart chain framework using Ethereum Smart Contract which employs Inter Planetary File Systems (IPFS) and MongoDB as storage systems to automate the process and exchange information into blocks using the Tendermint algorithm. The proposed work promotes complete traceability of the product, ensures data integrity and transparency in addition to providing security to their personal information using the Lelantos mode of shipping. The Tendermint algorithm helps to speed up the process of validating and authenticating the transaction quickly. More so in this time of pandemic, it is easier to meet the needs of customers through the Ethermint Smart Chain, which increases customer satisfaction, thus boosting their confidence. Moreover, Smart contracts help to exploit more international transaction services and provide an instant block time finality of around 5 sec using Ethermint. The paper concludes with a description of product storage and distribution adopting the Ethermint technique. The proposed system was executed based on the Ethereum-Tendermint Smart chain. Experiments were conducted on variable block sizes and the number of transactions. The experimental results indicate that the proposed system seems to perform better than existing blockchain-based systems. Two configuration files were used, the first one was to describe the storage part, including its topology. The second one was a modified file to include the test rounds that Caliper should execute, including the running time and the workload content. Our findings indicate this is a promising technology for food supply chain storage and distribution.