• 제목/요약/키워드: industrial internet of things (IIoT)

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스마트서비스를 위한 경량형 IIoT Edge 미들웨어 시스템 개발 (Development of IIoT Edge Middleware System for Smart Services)

  • 이한;황준석;강대현;정석찬
    • 한국빅데이터학회지
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    • 제6권1호
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    • pp.115-125
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    • 2021
  • 각종 ICT 기술 혁신 및 디지털트랜스포메이션(Digital Transformation)에 의해 사물인터넷(Internet of Things : IoT) 환경이 점차 지능화, 분산화, 자동화된 서비스를 요구하고 있으며, 특히 통신네트워크(5G),데이터 분석 및 인공지능(AI), 디지털 트윈(Digital Twin) 기술이 접목되는 산업사물인터넷(Industrial IoT : IIoT)에서의 고도화되고 안정적인 스마트서비스 제공 환경이 요구되고 있다. 본 연구에서는 다양한 산업현장의 설비 장치와 센서 등 이기종 장치와의 유연한 연계와 신속하고 안정적인 데이터 수집 및 처리 등을 위한 IIoT Edge 미들웨어 시스템을 제안하였다.

산업용 사물인터넷을 위한 머신러닝 기반 APT 탐지 기법 (Machine Learning Based APT Detection Techniques for Industrial Internet of Things)

  • 주소영;김소연;김소희;이일구
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2021년도 추계학술대회
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    • pp.449-451
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    • 2021
  • 엔드포인트를 대상으로 하는 사이버 공격이 표적형, 지능형 공격으로 정교하게 진화하면서 산업용 사물인터넷(IIoT, Industrial Internet of Things)을 겨냥하는 지능형 지속 공격(APT, Advanced Persistent Threat)이 증가하고 있다. APT 공격을 효과적으로 방어하기 위하여 룰 기반으로 악성 행위를 탐지하는 기존의 보안 도구를 결합하고 보완하는 머신러닝 기반의 엔드포인트 탐지 및 대응(EDR, Endpoint Detection and Response) 솔루션이 주목을 받고 있다. 하지만 범용 EDR 솔루션은 오탐률이 높고, 높은 수준의 분석가가 방대한 양의 경보를 모니터링 및 분석해야 하는 문제점이 존재한다. 따라서, IIoT 특성과 취약성을 반영한 머신러닝 기반의 EDR 솔루션 최적화 과정이 필수적이다. 본 연구에서는 IIoT 대상의 APT 공격의 흐름과 영향을 분석하고 머신러닝 기반 APT 탐지 EDR 솔루션을 비교 분석한다.

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산업용 사물인터넷에서 포그 컴퓨팅을 위한 인지 IoT 플랫폼 조사연구 (Research study on cognitive IoT platform for fog computing in industrial Internet of Things)

  • 홍성혁
    • 사물인터넷융복합논문지
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    • 제10권1호
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    • pp.69-75
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    • 2024
  • 본 연구에서는 산업용 사물인터넷(IIoT)의 맥락에서 포그 컴퓨팅(Fog Computing, FC)를 위해 특별히 고안된 혁신적인 인지 사물인터넷(Cognitive IoT) 프레임워크를 제안한다. 본 논문에서는 인지 IoT 플랫폼의 복잡한 설계 및 기능적 아키텍처에 초점을 맞추고, 이 아키텍처는 서비스 제공, 인지 의사결정, 분산 모니터링 및 제어와 같은 핵심 구성 요소를 원활하게 통합하는 것을 제안한다. 이 플랫폼의 중요한 측면은 기계 학습(ML) 및 인공 지능(AI)을 통합하는 것으로, 다양한 산업 애플리케이션에서 운영의 유연성과 상호 운용성을 향상시켜 실시간 기계 상태 모니터링에 중점을 둔 예측 유지보수-서비스(Predictive Maintenance-as-a-Service, PdM-as-a-Service) 모델을 통해 제시된다. 이 모델은 실시간 데이터 분석을 활용하여 유지보수 및 관리 작업을 수행함으로써 전통적인 유지보수 접근법을 뛰어넘고, 실증적 결과는 포그 컴퓨팅 환경 내에서 플랫폼의 효과성을 입증하며, 산업용 IoT 애플리케이션 분야에서의 변혁적 잠재력을 보여 IIoT 플랫폼 개발에 기여 하는 연구이다.

IIoTBC: A Lightweight Block Cipher for Industrial IoT Security

  • Juanli, Kuang;Ying, Guo;Lang, Li
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권1호
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    • pp.97-119
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    • 2023
  • The number of industrial Internet of Things (IoT) users is increasing rapidly. Lightweight block ciphers have started to be used to protect the privacy of users. Hardware-oriented security design should fully consider the use of fewer hardware devices when the function is fully realized. Thus, this paper designs a lightweight block cipher IIoTBC for industrial IoT security. IIoTBC system structure is variable and flexibly adapts to nodes with different security requirements. This paper proposes a 4×4 S-box that achieves a good balance between area overhead and cryptographic properties. In addition, this paper proposes a preprocessing method for 4×4 S-box logic gate expressions, which makes it easier to obtain better area, running time, and power data in ASIC implementation. Applying it to 14 classic lightweight block cipher S-boxes, the results show that is feasible. A series of performance tests and security evaluations were performed on the IIoTBC. As shown by experiments and data comparisons, IIoTBC is compact and secure in industrial IoT sensor nodes. Finally, IIoTBC has been implemented on a temperature state acquisition platform to simulate encrypted transmission of temperature in an industrial environment.

A study on BEMS-linked Indoor Air Quality Monitoring Server using Industrial IoT

  • Park, Taejoon;Cha, Jaesang
    • International Journal of Internet, Broadcasting and Communication
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    • 제10권4호
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    • pp.65-69
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    • 2018
  • In this paper, we propose an interworking architecture for building indoor air quality monitoring server (BEMS) using IIoT (Industrial Internet of Things). The proposed monitoring server adopts IIoT-based standard protocol so that interaction with BEMS installed in existing buildings can be performed easily. It can effectively communicate with indoor air quality measurement sensor installed in the building based on IIoT, Indoor air quality monitoring is possible. We implemented a proposed monitoring server, and confirmed the availability and monitoring of data from sensors in the building.

A Novel Smart Contract based Optimized Cloud Selection Framework for Efficient Multi-Party Computation

  • Haotian Chen;Abir EL Azzaoui;Sekione Reward Jeremiah;Jong Hyuk Park
    • Journal of Information Processing Systems
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    • 제19권2호
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    • pp.240-257
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    • 2023
  • The industrial Internet of Things (IIoT) is characterized by intelligent connection, real-time data processing, collaborative monitoring, and automatic information processing. The heterogeneous IIoT devices require a high data rate, high reliability, high coverage, and low delay, thus posing a significant challenge to information security. High-performance edge and cloud servers are a good backup solution for IIoT devices with limited capabilities. However, privacy leakage and network attack cases may occur in heterogeneous IIoT environments. Cloud-based multi-party computing is a reliable privacy-protecting technology that encourages multiparty participation in joint computing without privacy disclosure. However, the default cloud selection method does not meet the heterogeneous IIoT requirements. The server can be dishonest, significantly increasing the probability of multi-party computation failure or inefficiency. This paper proposes a blockchain and smart contract-based optimized cloud node selection framework. Different participants choose the best server that meets their performance demands, considering the communication delay. Smart contracts provide a progressive request mechanism to increase participation. The simulation results show that our framework improves overall multi-party computing efficiency by up to 44.73%.

Empowering Blockchain For Secure Data Storing in Industrial IoT

  • Firdaus, Muhammad;Rhee, Kyung-Hyune
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2020년도 춘계학술발표대회
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    • pp.231-234
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    • 2020
  • In the past few years, the industrial internet of things (IIoT) has received great attention in various industrial sectors which have potentially increased a high level of integrity, availability, and scalability. The increasing of IIoT is expected to create new smart industrial enterprises and build the next generation smart system. However existing IIoT systems rely on centralized servers that are vulnerable to a single point of failure and malicious attack, which exposes the data to security risks and storage. To address the above issues, blockchain is widely considered as a promising solution, which can build a secure and efficient environment for data storing, processing and sharing in IIoT. In this paper, we propose a decentralized, peer-to-peer platform for secure data storing in industrial IoT base on the ethereum blockchain. We exploit ethereum to ensure data security and reliability when smart devices store the data.

IIoT 미들웨어 플랫폼을 활용한 연속 제조공정의 환경센서 빅데이터 정제시스템 (Big Data Refining System for Environmental Sensor of Continuous Manufacturing Process using IIoT Middleware Platform)

  • 윤여진;김태형;이준희;김영곤
    • 한국인터넷방송통신학회논문지
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    • 제18권4호
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    • pp.219-226
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    • 2018
  • 산업용 사물인터넷(IIoT:Industrial Internet of Thing)은 기존의 공정의 자동화란 범주를 넘어 모든 제조공정을 정보화 하는 것을 의미한다. 또한 각 공정에 설치된 센서로 부터 수집되는 데이터를 토대로 정보화 시스템을 구축하여 각 공정을 실시간으로 관리하고 자동화하여 최적의 생산성을 유지하는데 그 목적을 두고 있다. 각 공정의 센서로 부터 수집되는 데이터는 비정형성을 띄고 있으며 이러한 비정형데이터를 효과적으로 수집하고 처리하기 위해 많은 연구가 이루어지고 있다. 본 논문에서는 효과적인 빅데이터 수집 및 처리를 위하여 미들웨어로 Node-RED를 사용한 시스템을 제안하였다.

Cybersecurity Framework for IIoT-Based Power System Connected to Microgrid

  • Jang, Ji Woong;Kwon, Sungmoon;Kim, SungJin;Seo, Jungtaek;Oh, Junhyoung;Lee, Kyung-ho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권5호
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    • pp.2221-2235
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    • 2020
  • Compared to the past infrastructure networks, the current smart grid network can improve productivity and management efficiency. However, as the Industrial Internet of Things (IIoT) and Internet-based standard communication protocol is used, external network contacts are created, which is accompanied by security vulnerabilities from various perspectives. Accordingly, it is necessary to develop an appropriate cybersecurity guideline that enables effective reactions to cybersecurity threats caused by the abuse of such defects. Unfortunately, it is not easy for each organization to develop an adequate cybersecurity guideline. Thus, the cybersecurity checklist proposed by a government organization is used. The checklist does not fully reflect the characteristics of each infrastructure network. In this study, we proposed a cybersecurity framework that reflects the characteristics of a microgrid network in the IIoT environment, and performed an analysis to validate the proposed framework.

FCBAFL: An Energy-Conserving Federated Learning Approach in Industrial Internet of Things

  • Bin Qiu;Duan Li;Xian Li;Hailin Xiao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제18권9호
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    • pp.2764-2781
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    • 2024
  • Federated learning (FL) has been proposed as an emerging distributed machine learning framework, which lowers the risk of privacy leakage by training models without uploading original data. Therefore, it has been widely utilized in the Industrial Internet of Things (IIoT). Despite this, FL still faces challenges including the non-independent identically distributed (Non-IID) data and heterogeneity of devices, which may cause difficulties in model convergence. To address these issues, a local surrogate function is initially constructed for each device to ensure a smooth decline in global loss. Subsequently, aiming to minimize the system energy consumption, an FL approach for joint CPU frequency control and bandwidth allocation, called FCBAFL is proposed. Specifically, the maximum delay of a single round is first treated as a uniform delay constraint, and a limited-memory Broyden-Fletcher-Goldfarb-Shanno bounded (L-BFGS-B) algorithm is employed to find the optimal bandwidth allocation with a fixed CPU frequency. Following that, the result is utilized to derive the optimal CPU frequency. Numerical simulation results show that the proposed FCBAFL algorithm exhibits more excellent convergence compared with baseline algorithm, and outperforms other schemes in declining the energy consumption.