• Journal of Convergence for Information Technology
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• v.10 no.12
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• pp.15-21
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• 2020

Although IoT systems are used in a variety of heterogeneous environments as cloud environments develop, all IoT devices are not provided with reliable protocols and services. This paper proposes an IoT data management technique that can extend the IoT cloud environment to an n-layer multi-level structure so that information collected from different heterogeneous IoT devices can be efficiently sorted and processed. The proposed technique aims to classify and process IoT information by transmitting routing information and weight information through wireless data link data collected from heterogeneous IoT devices. The proposed technique not only delivers information classified from IoT devices to the corresponding routing path but also improves the efficiency of IoT data processing by assigning priority according to weight information. The IoT devices used in the proposed technique use each other's reliable protocols, and queries for other IoT devices locally through a local cloud composed of hierarchical structures have features that ensure scalability because they maintain a certain cost.y channels of IoT information in order to make the most of the multiple antenna technology.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.349-350
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• 2022

As research on IT convergence continues, the scope of IoT (Internet of Things) services continues to expand. The IoT service uses a device suitable for the purpose. These IoT devices require an authentication function. In addition, in IoT services that handle important information such as personal information, security of transmission data is required. In this study, we implement a crypto key-based IoT network security system that can authenticate devices for IoT services and securely transmit data between devices. Through this study, IoT service can authenticate the device itself and maintain the confidentiality of transmitted data. However, since it is an IoT service, additional research on the application efficiency of the encryption algorithm is required.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.291-306
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• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.

• Journal of Convergence for Information Technology
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• v.9 no.11
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• pp.8-14
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• 2019

Due to the development of computer technology, IoT technology is being used in various fields of industry, economy, medical service and education. However, multimedia information processed through IoT equipment is still one of the major issues in the application sector. In this paper, a big data protection model for users of IoT based IoT is proposed to ensure integrity of users' multimedia information processed through IoT equipment. The proposed model aims to prevent users' illegal exploitation of big data information collected through IoT equipment without users' consent. The proposed model uses signatures and authentication information for IoT users in a hybrid cryptographic method. The proposed model feature ensuring integrity and confidentiality of users' big data collected through IoT equipment. In addition, the user's big data is not abused without the user's consent because the user's signature information is encrypted using a steganography-based cryptography-based encryption technique.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.37-47
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• 2018

The number of capabilities of Internet of Things (IoT) devices will exponentially grow over the next years. These devices may generate a vast amount of time-constrained data. In the context of IoT, data management should act as a layer between the objects and devices generating the data and the applications accessing the data for analysis purposes and services. In addition, most of IoT services will be content-centric rather than host centric to increase the data availability and the efficiency of data delivery. IoT will enable all the communication devices to be interconnected and make the data generated by or associated with devices or objects globally accessible. Also, fog computing keeps data and computation close to end users at the edge of network, and thus provides a new breed of applications and services to end users with low latency, high bandwidth, and geographically distributed. In this paper, we propose Edge-Fog cloud-based Hierarchical Data Delivery ($EFcHD^2$) method that effectively and reliably delivers IoT data to associated with IoT applications with ensuring time sensitivity. The proposed $EFcHD^2$ method stands on basis of fully decentralized hybrid of Edge and Fog compute cloud model, Edge-Fog cloud, and uses information-centric networking and bloom filters. In addition, it stores the replica of IoT data or the pre-processed feature data by edge node in the appropriate locations of Edge-Fog cloud considering the characteristic of IoT data: locality, size, time sensitivity and popularity. Then, the performance of $EFcHD^2$ method is evaluated through an analytical model, and is compared to fog server-based and Content-Centric Networking (CCN)-based data delivery methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1598-1607
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• 2016

Safe transmitting monitoring data is essential for supporting IoT-Cloud services efficiently. In this paper, we find ways to configure data path flexibly in SDN based for IoT-Cloud services utilizing SmartX-mini Playground. To do this, we use ONOS(Open Network Operating System) SDN Controller, ONOS NBI Applications made from us to check flexible and safe data path configuration for IoT-Cloud monitoring data transmitting in real IoT-SDN-Cloud environments.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.3
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• pp.139-150
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• 2015

The major components of IoT(Internet of Things) environment are IoT devices rather than the conventional desktop computers. One of the intrinsic characteristics of IoT devices is diversity in view of data type and data access method. In addition, IoT devices usually deal with real-time data. In order to use such IoT data for internal business or cloud services, an IoT platform capable of easy domain management and consistent data access interface is required. This paper proposes a Linux FUSE-based virtual file system connecting IoT devices on POSIX file system view. It is possible to manage IoT domain with the native Linux utilities such as mkdir, mknod, ls and find in the file system. Also, the file system makes it possible to access or control IoT devices through POSIX interface such as open(), read(), write() or close() without any separate APIs or utilities. A test result shows that the management performance of the file system is lower than that of linux file system negligibly.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.4
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• pp.995-1012
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• 2016

In Internet of Things (IoT) environments, devices or sensors everywhere can automatically collect data without the individual awareness, further combine and share data using ubiquitous network, and thus the development of IoT raises new challenges in respect of personal data protection and privacy. This study aims to identify main issues related to data protection in the IoT and propose adequate measures. We analyzed the types of personal data controllers and processors in IoT and figured out the issues regarding the processing of personal data and the rights to privacy of data subject. Accordingly, we suggested the institutional ways (e.g., establishment of user-friendly notice and flexible consent system, re-identification risk monitoring system, data protection in cross-border transfer, and user education) to improve the situation of personal data protection in IoT and finally proposed the improvement tasks to carry out first based on the degree of urgency and importance.

• Journal of Advanced Navigation Technology
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• v.20 no.4
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• pp.374-379
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• 2016

Recently, IoT(Internet of Things) to connect the objects and people has attracted attention. And it is rapidly developing. IoT is to develop, experts are predicting that the device is connected to the Internet to break through around 100 billion within 10 years. However, the current IoT companies are having a difficult state to the other each other IoT platform for interaction between data silos effects. These silos effects will limit the IoT grow to a larger market. Thus, the IoT service supplier shall develop an open platform for interaction IoT data between each IoT platform. These web technologies for current open IoT platform has emerged. If developers are using familiar, easy-to-learn Web technologies, developers can take advantage of a variety of services for the collected data, and found the IoT devices can be bypassed if there is a problem on the network. In this paper, we investigate the data communications technology that can be used in WoT environment to overcome these silos effects. As a result, the polling method that can simply send the IoT information the fastest.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.2-5
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• 2021

With the recent development of the Internet of Things (IoT) technology, various terminals are being connected to the Internet. As a result, the amount of IoT data is also increasing, and an index key that can efficient analyze the large-scale IoT data is proposed. Existing index keys have only time and space information, so if data stored in index tables and instance tables were queried using repetition or join operation, IoT data was embedded in the index key of the proposal to create OLAP-based big tables to minimize the number of repetitions or join times.