• Title/Summary/Keyword: IoT 결함

Search Result 645, Processing Time 0.025 seconds

A Trust Evaluation Model on QoS based Services Composition for IoT Environments (IoT 환경에서 QoS 기반 서비스 조합을 위한 신뢰 평가모델)

  • Kim, Yukyong
    • Journal of Software Assessment and Valuation
    • /
    • v.15 no.2
    • /
    • pp.85-93
    • /
    • 2019
  • In an open, heterogeneous environment based on machine-to-machine (M2M) interactions, service selection is a critical issue and the concept of social trust can be applied to service selection so that IoT devices can make the best choice for interaction. In this paper, we propose a method for evaluating the trust level of the service and for estimating the QoS of the composite service using a profile created based on social trust relationship in IoT environment. As the service selection is made through quantitative evaluation, it is expected that the result of a more reliable service combination can be obtained.

Trend Analysis of IoT Technology Using Open Source (오픈소스를 이용한 IoT 기술의 동향 분석)

  • Kwon, Yong-Kwang;Kim, Sun-Young
    • The Journal of the Institute of Internet, Broadcasting and Communication
    • /
    • v.20 no.3
    • /
    • pp.65-72
    • /
    • 2020
  • The Internet of Things(IoT) is to build a hyper-connected society through interconnection, and on this basis, to improve the quality of life and productivity, including solving social problems, and to become the next growth engine for the nation. The open common eco-system pursued by the IoT can start with the under- standing of the word 'open'. The IoT can achieve the expected effect of lowering the barriers to entry of technology development, and in these changes, OSSW and OSHW play a very important role in accelerating IoT eco-system maturity and breaking the boundaries between industries to promote convergence. Recently, it has developed into an intelligent IoT that combines artificial intelligence (AI) with the connectivity of the IoT. Here, I will analyze the direction of development of the IoT through understanding and analysis of open source.

A Survey Analysis of Internet of Things Security Issues and Combined Service

  • Kim, HyunHo;Lee, HoonJae;Lee, YoungSil
    • Journal of the Korea Society of Computer and Information
    • /
    • v.25 no.8
    • /
    • pp.73-79
    • /
    • 2020
  • Since the start of the 4th industrial revolution, technologies have been developed in the Internet of Things (IoT), artificial intelligence (AI), virtual reality (VR), and 5G. Compared to other technologies IoT is currently being commercialized more than other technologies where the numbers of connected things are increases every year. The IoT has a huge advantage to provide convenience and lots of information to users, but security cannot keep up with the speed of development. IoT services continue to provide services for related devices, but at present, more and more types of new services are being combined with other technologies by utilizing the services of devices. This paper reviews and analyzes research on security issues and services related to the Internet of Things to explore how security trends and service delivery will develop in the future.

A comparative study of the performance of machine learning algorithms to detect malicious traffic in IoT networks (IoT 네트워크에서 악성 트래픽을 탐지하기 위한 머신러닝 알고리즘의 성능 비교연구)

  • Hyun, Mi-Jin
    • Journal of Digital Convergence
    • /
    • v.19 no.9
    • /
    • pp.463-468
    • /
    • 2021
  • Although the IoT is showing explosive growth due to the development of technology and the spread of IoT devices and activation of services, serious security risks and financial damage are occurring due to the activities of various botnets. Therefore, it is important to accurately and quickly detect the activities of these botnets. As security in the IoT environment has characteristics that require operation with minimum processing performance and memory, in this paper, the minimum characteristics for detection are selected, and KNN (K-Nearest Neighbor), Naïve Bayes, Decision Tree, Random A comparative study was conducted on the performance of machine learning algorithms such as Forest to detect botnet activity. Experimental results using the Bot-IoT dataset showed that KNN can detect DDoS, DoS, and Reconnaissance attacks most effectively and efficiently among the applied machine learning algorithms.

The prevent method of data loss due to differences in bit rate between heterogeneous IoT devices (이기종 IoT 장치간의 데이터 전송 속도 차이로 인한 데이터 손실 방지 기법)

  • Seo, Hyungyoon;Park, Jung Kyu
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.23 no.7
    • /
    • pp.829-836
    • /
    • 2019
  • IoT devices are widely used in network construction and are increasing. If necessary, heterogeneous IoT devices are used for data transmission. This paper proposes to prevent the method of data loss due to differences in throughput when the local network is constructed by Bluetooth 5 and long range network does by LoRa(Long Range). Data loss occur when the data transmits through LoRa, due to the throughputs of Bluetooth 5 faster than that of LoRa. The prevent method proposed by this paper can apply not only Bluetooth 5 and LoRa but heterogeneous IoT devices and expect to prevent data loss due to differences in throughput between heterogeneous IoT devices. Also, this paper shows the simulation result by applying the proposed avoid method. In this paper, two way to the preventive method shows the data transmission ratio and amount of memory that of necessity.

Design of Efficient Big Data Collection Method based on Mass IoT devices (방대한 IoT 장치 기반 환경에서 효율적인 빅데이터 수집 기법 설계)

  • Choi, Jongseok;Shin, Yongtae
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
    • /
    • v.14 no.4
    • /
    • pp.300-306
    • /
    • 2021
  • Due to the development of IT technology, hardware technologies applied to IoT equipment have recently been developed, so smart systems using low-cost, high-performance RF and computing devices are being developed. However, in the infrastructure environment where a large amount of IoT devices are installed, big data collection causes a load on the collection server due to a bottleneck between the transmitted data. As a result, data transmitted to the data collection server causes packet loss and reduced data throughput. Therefore, there is a need for an efficient big data collection technique in an infrastructure environment where a large amount of IoT devices are installed. Therefore, in this paper, we propose an efficient big data collection technique in an infrastructure environment where a vast amount of IoT devices are installed. As a result of the performance evaluation, the packet loss and data throughput of the proposed technique are completed without loss of the transmitted file. In the future, the system needs to be implemented based on this design.

Blockchain-based lightweight consensus algorithm (L-PBFT) for building trust networks in IoT environment (IoT 환경에서 신뢰 네트워크 구축을 위한 블록체인 기반의 경량 합의 알고리즘(L-PBFT))

  • Park, Jung-Oh
    • Journal of Industrial Convergence
    • /
    • v.20 no.6
    • /
    • pp.37-45
    • /
    • 2022
  • With the development of the Internet of Things (IoT), related network infrastructures require new technologies to protect against threats such as external hacking. This study proposes an L-PBFT consensus algorithm that can protect IoT networks based on a blockchain consensus algorithm. We designed a blockchain (private) model suitable for small networks, tested processing performance for ultra-small/low-power IoT devices, and verified stability. As a result of performance analysis, L-PBFT proved that at least the number of nodes complies with the operation of the consensus algorithm(minimum 14%, maximum 29%) and establishes a trust network(separation of secure channels) different from existing security protocols. This study is a 4th industry convergence research and will be a foundation technology that will help develop IoT device security products in the future.

Attack Detection and Classification Method Using PCA and LightGBM in MQTT-based IoT Environment (MQTT 기반 IoT 환경에서의 PCA와 LightGBM을 이용한 공격 탐지 및 분류 방안)

  • Lee Ji Gu;Lee Soo Jin;Kim Young Won
    • Convergence Security Journal
    • /
    • v.22 no.4
    • /
    • pp.17-24
    • /
    • 2022
  • Recently, machine learning-based cyber attack detection and classification research has been actively conducted, achieving a high level of detection accuracy. However, low-spec IoT devices and large-scale network traffic make it difficult to apply machine learning-based detection models in IoT environment. Therefore, In this paper, we propose an efficient IoT attack detection and classification method through PCA(Principal Component Analysis) and LightGBM(Light Gradient Boosting Model) using datasets collected in a MQTT(Message Queuing Telementry Transport) IoT protocol environment that is also used in the defense field. As a result of the experiment, even though the original dataset was reduced to about 15%, the performance was almost similar to that of the original. It also showed the best performance in comparative evaluation with the four dimensional reduction techniques selected in this paper.

A Study on Blockchain Networking for Internet of Things (사물인터넷을 위한 블록체인 네트워킹에 대한 연구)

  • Lee, Il-Gu
    • Journal of Digital Convergence
    • /
    • v.16 no.8
    • /
    • pp.201-210
    • /
    • 2018
  • High expectations are posed on the blockchain-based internet of things (IoT), in which IoT and blockchain technology is combined to obtain trust in the Internet, where trust appears impossible to obtain. However, applications of current blockchain-based IoT technology to real-world scenarios appears to be significantly more difficult owing to limitations regarding scalability and security. In this paper, the difficulties to implement blockchain networking technologies for IoT and digital businesses are investigated and practical solutions such as sharding, off-chain, de-idetification and P2P crypto-currency exchange are explored. In further work, a blockchain platform for IoTs which provides scalability and security will be implemented according to this research results, and compared with conventional blockchain platforms.

A study on the development of quality control algorithm for internet of things (IoT) urban weather observed data based on machine learning (머신러닝기반의 사물인터넷 도시기상 관측자료 품질검사 알고리즘 개발에 관한 연구)

  • Lee, Seung Woon;Jung, Seung Kwon
    • Journal of Korea Water Resources Association
    • /
    • v.54 no.spc1
    • /
    • pp.1071-1081
    • /
    • 2021
  • In addition to the current quality control procedures for the weather observation performed by the Korea Meteorological Administration (KMA), this study proposes quality inspection standards for Internet of Things (IoT) urban weather observed data based on machine learning that can be used in smart cities of the future. To this end, in order to confirm whether the standards currently set based on ASOS (Automated Synoptic Observing System) and AWS (Automatic Weather System) are suitable for urban weather, usability was verified based on SKT AWS data installed in Seoul, and a machine learning-based quality control algorithm was finally proposed in consideration of the IoT's own data's features. As for the quality control algorithm, missing value test, value pattern test, sufficient data test, statistical range abnormality test, time value abnormality test, spatial value abnormality test were performed first. After that, physical limit test, stage test, climate range test, and internal consistency test, which are QC for suggested by the KMA, were performed. To verify the proposed algorithm, it was applied to the actual IoT urban weather observed data to the weather station located in Songdo, Incheon. Through this, it is possible to identify defects that IoT devices can have that could not be identified by the existing KMA's QC and a quality control algorithm for IoT weather observation devices to be installed in smart cities of future is proposed.