• Journal of the Korea Society of Computer and Information
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• v.25 no.11
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• pp.1-8
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• 2020

In this paper, we proposed a smart greenhouse system that can easily grow plants indoors without professional knowledge by using the criteria of factors affected by common plants (temperature, humidity, soil humidity), and implemented a system that can check the greenhouse state in real time and control the device remotely through mobile applications. Based on Raspberry pie and Arduino, the system measures the state of greenhouse in real time through sensors and automatically controls the device. After growing and experimenting with plants in a greenhouse for a certain period of time, it was confirmed that the environment suitable for each plant was maintained. Therefore, the smart greenhouse system in this paper is expected to improve plant cultivation efficiency and user convenience and also increase beginners' access to plants.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1196-1213
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• 2020

There is a growing interest in the development of smart environments through predicting the behaviors of inhabitants of smart spaces in the recent past. Various smart services are deployed in modern smart cities to facilitate residents and city administration. Prediction algorithms are broadly used in the smart fields in order to well equip the smart services for the future demands. Hence, an accurate prediction technology plays a vital role in the smart services. In this paper, we take out an extensive survey of smart spaces such as smart homes, smart farms and smart cars and smart applications such as smart health and smart energy. Our extensive survey is based on more than 400 articles and the final list of research studies included in this survey consist of 134 research papers selected using Google Scholar database for period of 2008 to 2018. In this survey, we highlight the role of prediction algorithms in each sub-domain of smart Internet of Things (IoT) environments. We also discuss the main algorithms which play pivotal role in a particular IoT subfield and effectiveness of these algorithms. The conducted survey provides an efficient way to analyze and have a quick understanding of state of the art work in the targeted domain. To the best of our knowledge, this is the very first survey paper on main categories of prediction algorithms covering statistical, heuristic and hybrid approaches for smart environments.

• Convergence Security Journal
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• v.17 no.2
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• pp.15-22
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• 2017

This paper presents new 8-bit implementation of AES. Most typical 8-bit AES designs are to reduce the circuit area by sacrificing its throughput. The presented AES architecture employs two separated S-box to perform round operation and key generation in parallel. From the simulation results of the proposed AES-128, the maximum critical path delay is 13.0ns. It can be operated in 77MHz and the throughput is 15.2 Mbps. Consequently, the throughput of the proposed AES has 1.54 times higher throughput than the other counterpart although the area increasement is limited in 1.17 times. The proposed AES design enables very low-area design without sacrificing its performance. Thereby, it can be suitable for the various IoT applications that need high speed communication.

• Journal of KIISE
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• v.42 no.8
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• pp.979-989
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• 2015

Machine to Machine (M2M) technology has gained attention due to the fast diffusion of Internet of Things (IoT) technologies and smart devices. Most wireless network experts believe that Bluetooth Low Energy (BLE) Communications technology in an iBeacon network has amazing advantages in terms of providing communication services at a low cost in smartphone applications. Specifically, BLE does not require any pairing process during its communication phases, so it is possible to send a message to any node without incurring additional transmissions costs if they are within the BLE communication range. However, BLE does not require any security verification during communication, so it has weak security. Therefore, a security authorization process would be necessary to obtain customer confidence. To provide security functions for iBeacon, we think that the iBeacon Message Encryption process and a Decryption (Authorization) process should be designed and implemented. We therefore propose the BLE message Authorization Mechanism based on a One Time Password Algorithm (BLE-OTP). The effectiveness of our mechanism is evaluated by conducting a performance test on an attendance system based on BLE-OTP.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.1
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• pp.17-28
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• 2019

6LoWPAN based on IEEE 802.15.4 is a realistic standard platform for various Internet of Things (IoT) applications. To bootstrap the LoWPAN (Low-power Wireless Personal Area Network), each device must perform 6LoWPAN-ND address registration to assign a unique IPv6 address. Without adequate security mechanisms, 6LoWPAN-ND is vulnerable to a variety of security attacks including corrupted node attacks. Several security mechanisms have been proposed as a supplement to the vulnerability, but the vulnerability exists because it relies solely on IEEE 802.15.4 hop-by-hop security. In this paper, we propose and analyze a vulnerability of 6LoWPAN-ND address registration and a new security mechanism suitable for preventing the attack of damaged node. It also shows that the proposed security mechanism is compatible with the Internet Engineering Task Force (IETF) standard and is more efficient than the mechanism proposed in the IETF 6 lo WG.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.7
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• pp.875-880
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• 2019

A RC4 stream cipher is widely used for security applications such as IEEE 802.11 WEP, IEEE 802.11i TKIP and so on, because it can be simply implemented to dedicated circuits and achieve a high-speed encryption. RC4 is also used for systems with limited resources like IoT, but there are performance limitations. RC4 consists of two stages, KSA and PRGA. KSA performs initialization and randomization of S-box and K-box and PRGA produces cipher texts using the randomized S-box. In this paper, we initialize the S-box and K-box in the randomization of the KSA stage to reduce the initialization delay. In the randomization, we use clusters to process swap operation between elements of S-box in parallel and can generate two cipher texts per clock. The proposed RC4 cipher hardware can initialize S-box and K-box without any delay and achieves about 2 times to 6 times improvement in KSA randomization and key stream generation.

• Smart Media Journal
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• v.8 no.2
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• pp.66-73
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• 2019

Recently, object recognition technology using computer vision has attracted attention as a technology to replace sensor-based object recognition technology. It is often difficult to commercialize sensor-based object recognition technology because such approach requires an expensive sensor. On the other hand, object recognition technology using computer vision may replace sensors with inexpensive cameras. Moreover, Real-time recognition is viable due to the growth of CNN, which is actively introduced into other fields such as IoT and autonomous vehicles. Because object recognition model applications demand expert knowledge on deep learning to select and learn the model, such method, however, is challenging for non-experts to use it. Therefore, in this paper, we analyze the structure of deep - learning - based object recognition models, and propose a platform that can automatically select a deep - running object recognition model based on a user 's desired condition. We also present the reason we need to select statistics-based object recognition model through conducted experiments on different models.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.5
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• pp.277-286
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• 2019

In this paper, we propose an efficient hyperplane generation technique to classify human activity from combination of events and sequence information obtained from multiple-event sensors. By generating hyperplane efficiently, our machine learning algorithm classify with less memory and run time than the LSVM (Linear Support Vector Machine) for embedded system. Because the fact that light weight and high speed algorithm is one of the most critical issue in the IoT, the study can be applied to smart home to predict human activity and provide related services. Our approach is based on reducing numbers of hyperplanes and utilizing robust string comparing algorithm. The proposed method results in reduction of memory consumption compared to the conventional ML (Machine Learning) algorithms; 252 times to LSVM and 34,033 times to LSTM (Long Short-Term Memory), although accuracy is decreased slightly. Thus our method showed outstanding performance on accuracy per hyperplane; 240 times to LSVM and 30,520 times to LSTM. The binarized image is then divided into groups, where each groups are converted to binary number, in order to reduce the number of comparison done in runtime process. The binary numbers are then converted to string. The test data is evaluated by converting to string and measuring similarity between hyperplanes using Levenshtein algorithm, which is a robust dynamic string comparing algorithm. This technique reduces runtime and enables the proposed algorithm to become 27% faster than LSVM, and 90% faster than LSTM.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.1
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• pp.37-42
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• 2019

In this paper, we propose a syndrome decoding scheme that can correct two errors for single error correcting Hamming codes within a code length. The decoding scheme proposed in this paper has the advantage of significantly improving the error rate performance compared to the decoder complexity by correcting multiple errors without substantially increasing the decoding complexity. It is suitable for applications in which the energy use of encoder/decoder is extremely limited and the low error rate performance is required, such as IoT communications and molecular communications. In order to verify the improvement of the error rate performance of the Hamming code with the proposed decoding scheme, we performed simulation on Hamming codes with short code length in the AWGN and BPSK modulation environments. As a result, compared with the conventional decoding method, the proposed decoding scheme showed performance improvement of about 1.1 ~ 1.2[dB] regardless of the code length of the Hamming code.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.290-292
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• 2019

Since the advent of blockchain and bitcoin, decentralization has been accelerating around the world as a public blockchain ethereum with smartcontract has begun. Developers can use Ethereum's blockchain development platform to develop "distributed applications" (DApp) running on a decentralized P2P network, and various types of devices from IoT to mobile can participate in a block-chain distributed environment have. Using Ethereum's blockchain development platform, developers can develop "Decentralized Application (DApp)" that run on a decentralized P2P network and various types of devices from IOT to mobile can participate in distributed blockchain environments. There are many ways to interact with the blockchain and the smart contract, but users tend to prefer the mobile methods due to their convenience and accessibility advantages. Therefore, the author developed an Android based voting DApp and researched related issues. Since the current development methods of DApp are not adequately researched and standardized, efficient methods for developing user-friendly DApp were studied. Because DApp has to spend a certain amount of fees to interact with blockchain, it has intensively investigated the gas problem of Smart Contract code and the security problem of code, and author would like to introduce it in this paper.