• Title/Summary/Keyword: IoT environments

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A SECURITY ARCHITECTURE FOR THE INTERNET OF THINGS

  • Behrens, Reinhard;Ahmed, Ali
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.12
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    • pp.6092-6115
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    • 2017
  • This paper demonstrates a case for an end-to-end pure Application Security Layer for reliable and confidential communications within an Internet of Things (IoT) constrained environment. To provide a secure key exchange and to setup a secure data connection, Transport Layer Security (TLS) is used, which provides native protection against replay attacks. TLS along with digital signature can be used to achieve non-repudiation within app-to-app communications. This paper studies the use of TLS over the JavaScript Object Notation (JSON) via a The Constrained Application Protocol (CoAP) RESTful service to verify the hypothesis that in this way one can provide end-to-end communication flexibility and potentially retain identity information for repudiation. As a proof of concept, a prototype has been developed to simulate an IoT software client with the capability of hosting a CoAP RESTful service. The prototype studies data requests via a network client establishing a TLS over JSON session using a hosted CoAP RESTful service. To prove reputability and integrity of TLS JSON messages, JSON messages was intercepted and verified against simulated MITM attacks. The experimental results confirm that TLS over JSON works as hypothesised.

An Hybrid Probe Detection Model using FCM and Self-Adaptive Module (자가적응모듈과 퍼지인식도가 적용된 하이브리드 침입시도탐지모델)

  • Lee, Seyul
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.13 no.3
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    • pp.19-25
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    • 2017
  • Nowadays, networked computer systems play an increasingly important role in our society and its economy. They have become the targets of a wide array of malicious attacks that invariably turn into actual intrusions. This is the reason computer security has become an essential concern for network administrators. Recently, a number of Detection/Prevention System schemes have been proposed based on various technologies. However, the techniques, which have been applied in many systems, are useful only for the existing patterns of intrusion. Therefore, probe detection has become a major security protection technology to detection potential attacks. Probe detection needs to take into account a variety of factors ant the relationship between the various factors to reduce false negative & positive error. It is necessary to develop new technology of probe detection that can find new pattern of probe. In this paper, we propose an hybrid probe detection using Fuzzy Cognitive Map(FCM) and Self Adaptive Module(SAM) in dynamic environment such as Cloud and IoT. Also, in order to verify the proposed method, experiments about measuring detection rate in dynamic environments and possibility of countermeasure against intrusion were performed. From experimental results, decrease of false detection and the possibilities of countermeasures against intrusions were confirmed.

Restful Web Services Composition Using Semantic Ontology for Elderly Living Assistance Services

  • Fattah, Sheik Mohammad Mostakim;Chong, Ilyoung
    • Journal of Information Processing Systems
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    • v.14 no.4
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    • pp.1010-1032
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    • 2018
  • Recent advances in medical science have made people live longer, which has affected many aspects of life, such as caregiver burden, increasing cost of healthcare, increasing number of disabled and depressive disorder persons, and so on. Researchers are now focused on elderly living assistance services in smart home environments. In recent years, assisted living technologies have rapidly grown due to a faster growing aging society. Many smart devices are now interconnected within the home network environment and such a home setup supports collaborations between those devices based on the Internet of Things (IoT). One of the major challenges in providing elderly living assistance services is to consider each individual's requirements of different needs. In order to solve this, the virtualization of physical things, as well as the collaboration and composition of services provided by these physical things should be considered. In order to meet these challenges, Web of Objects (WoO) focuses on the implementation aspects of IoT to bring the assorted real world objects with the web applications. We proposed a semantic modelling technique for manual and semi-automated service composition. The aim of this work is to propose a framework to enable RESTful web services composition using semantic ontology for elderly living assistance services creation in WoO based smart home environment.

Development of NCS-Based Technical Education Program for Analog Signal Processing (아날로그 신호처리를 위한 NCS 기반 기술교육 프로그램 개발)

  • Cho, Choon-Nam
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.33 no.6
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    • pp.510-514
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    • 2020
  • Vocational education needs to be transformed to cultivate talents with diverse fusion competencies, which is in line with the recent changes that have become a part of the complex technological developments in the 4th Industrial Revolution. Therefore, it is very important for college graduates to obtain employment skills as they are required to prepare for careers within the complex environments of future societies. With the transition to the Internet of Things (IoT)-based control in the manufacturing industry, the development of technological education and related training programs is required to cultivate practical talents for students who have acquired not only the information on existing programmable logic controller (PLC)-based technology, but also that on embedded programming technology. Therefore, to develop an NCS-based education program for analog signal processing to ensure that programming can easily be learned for cultivating practical talent, this study summarizes the opinions of field experts, selects the appropriate NCS competency unit, and designs an adequate technology education training program.

Development of Smart Device Module for Perimeter Intrusion Detection (외곽 침입 감지를 위한 스마트 디바이스의 개발)

  • Ryu, Dae-Hyun;Choi, Tae-Wan
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.2
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    • pp.363-370
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    • 2021
  • The perimeter intrusion detection system is very important in physical security. In this study, a micro smart device (module) using MEMS sensor was developed in IoT environment for external intrusion detection. The outer intrusion detection system applying the smart device developed in this study is installed in various installation environments, such as barbed wire of various materials and shapes, the city center, the beach, and the mountain, so that it can detect external intrusion and its location as well as false alarms. As a smart sensor that can minimize the false alarm rate and economical construction cost, it is expected that it can be used for the safe operation of major facilities and prevention of disasters and crimes.

Optimal Implementation of Lightweight Block Cipher PIPO on CUDA GPGPU (CUDA GPGPU 상에서 경량 블록 암호 PIPO의 최적 구현)

  • Kim, Hyun-Jun;Eum, Si-Woo;Seo, Hwa-Jeong
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.32 no.6
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    • pp.1035-1043
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    • 2022
  • With the spread of the Internet of Things (IoT), cloud computing, and big data, the need for high-speed encryption for applications is emerging. GPU optimization can be used to validate cryptographic analysis results or reduced versions theoretically obtained by the GPU in a reasonable time. In this paper, PIPO lightweight encryption implemented in various environments was implemented on GPU. Optimally implemented considering the brute force attack on PIPO. In particular, the optimization implementation applying the bit slicing technique and the GPU elements were used as much as possible. As a result, the implementation of the proposed method showed a throughput of about 19.5 billion per second in the RTX 3060 environment, achieving a throughput of about 122 times higher than that of the previous study.

Edge Detection based on Contrast Analysis in Low Light Level Environment (저조도 환경에서 명암도 분석 기반의 에지 검출)

  • Park, Hwa-Jung;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.437-440
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    • 2022
  • In modern society, the use of the image processing field is increasing rapidly due to the 4th industrial revolution and the development of IoT technology. In particular, edge detection is widely used in various fields as an essential preprocessing process in image processing applications such as image classification and object detection. Conventional methods for detecting an edge include a Sobel edge detection filter, a Roberts edge detection filter, a Prewitt edge detection filter, Laplacian of Gaussian (LoG), and the like. However, existing methods have the disadvantage of showing somewhat insufficient performance of edge detection characteristics in a low-light level environment with low contrast. Therefore, this paper proposes an edge detection algorithm based on contrast analysis to increase edge detection characteristics even in low-light level environments.

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Hyperparameter optimization for Lightweight and Resource-Efficient Deep Learning Model in Human Activity Recognition using Short-range mmWave Radar (mmWave 레이더 기반 사람 행동 인식 딥러닝 모델의 경량화와 자원 효율성을 위한 하이퍼파라미터 최적화 기법)

  • Jiheon Kang
    • IEMEK Journal of Embedded Systems and Applications
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    • v.18 no.6
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    • pp.319-325
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    • 2023
  • In this study, we proposed a method for hyperparameter optimization in the building and training of a deep learning model designed to process point cloud data collected by a millimeter-wave radar system. The primary aim of this study is to facilitate the deployment of a baseline model in resource-constrained IoT devices. We evaluated a RadHAR baseline deep learning model trained on a public dataset composed of point clouds representing five distinct human activities. Additionally, we introduced a coarse-to-fine hyperparameter optimization procedure, showing substantial potential to enhance model efficiency without compromising predictive performance. Experimental results show the feasibility of significantly reducing model size without adversely impacting performance. Specifically, the optimized model demonstrated a 3.3% improvement in classification accuracy despite a 16.8% reduction in number of parameters compared th the baseline model. In conclusion, this research offers valuable insights for the development of deep learning models for resource-constrained IoT devices, underscoring the potential of hyperparameter optimization and model size reduction strategies. This work contributes to enhancing the practicality and usability of deep learning models in real-world environments, where high levels of accuracy and efficiency in data processing and classification tasks are required.

Secure SLA Management Using Smart Contracts for SDN-Enabled WSN

  • Emre Karakoc;Celal Ceken
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.11
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    • pp.3003-3029
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    • 2023
  • The rapid evolution of the IoT has paved the way for new opportunities in smart city domains, including e-health, smart homes, and precision agriculture. However, this proliferation of services demands effective SLAs between customers and service providers, especially for critical services. Difficulties arise in maintaining the integrity of such agreements, especially in vulnerable wireless environments. This study proposes a novel SLA management model that uses an SDN-Enabled WSN consisting of wireless nodes to interact with smart contracts in a straightforward manner. The proposed model ensures the persistence of network metrics and SLA provisions through smart contracts, eliminating the need for intermediaries to audit payment and compensation procedures. The reliability and verifiability of the data prevents doubts from the contracting parties. To meet the high-performance requirements of the blockchain in the proposed model, low-cost algorithms have been developed for implementing blockchain technology in wireless sensor networks with low-energy and low-capacity nodes. Furthermore, a cryptographic signature control code is generated by wireless nodes using the in-memory private key and the dynamic random key from the smart contract at runtime to prevent tampering with data transmitted over the network. This control code enables the verification of end-to-end data signatures. The efficient generation of dynamic keys at runtime is ensured by the flexible and high-performance infrastructure of the SDN architecture.

Transmission Performance of Lattice Structure Ad-Hoc Network under Intrusions (침해가 있는 격자구조 애드-혹 네트워크의 전송성능)

  • Kim, Young-Dong
    • The Journal of the Korea institute of electronic communication sciences
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    • v.9 no.7
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    • pp.767-772
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    • 2014
  • As temporary network, ad-hoc network has been effected by structures and implemented environments of networks. In this paper, transmission performance of lattice structure ad-hoc network, which is expected to use in sensor network and IoT(Internet of Things), is analyzed in point of intrusions and countermeasure for intrusion is suggested. In this paper, computer simulation based on NS-2 is used for performance analysis, VoIP(Voice over Internet Protocol) as a widely used service is chosen for performance measure. MOS(Mean Opinion Score) and call connection rate is used as performance parameter. As results of performance analysis, it is shown that for MOS, random network is better then lattice network at intrusion environments, but for call connection rate, lattice network is better then random network.