• Convergence Security Journal
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• v.15 no.5
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• pp.3-8
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• 2015

Most mobile cloud computing system use public key cryptography to provide data security and mutual authentication. A variant of traditional public key technologies called Identity-Based Cryptography(IBC) has recently received considerable attention. The certificate-free approach of IBC may well match the dynamic qualities of cloud environment. But, there is a need for a lightweight secure framework that provides security with minimum processing overhead on mobile devices. In this paper, we propose to use hierarchical ID-Based Encryption in mobile cloud computing. It is suitable for a mobile network since it can reduce the workload of root Public Key Generators by delegating the privilege of user authentication and private key generation. The Identity-Based Encryption and Identity-Based Signature are also proposed and an ID-Based Authentication scheme is presented to secure data processing. The proposed scheme is designed by one-way hash functions and XOR operations, thus has low computation costs for mobile users.

• The Journal of the Korea Contents Association
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• v.3 no.2
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• pp.57-64
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• 2003

A Web Service is an URL addressable set of functionality that is exposed over a network to serve as a building Hock for creating distributed applications. SOAP is a protocol that Web Service consumers often use, when they request and response to a Web Service, and it is a lightweight, XML-based protocol over HTTP for exchange to information in decentralized, distributed environments. A Web Service is very useful forimplementing common functions in especially a large size business area, because it is invoked by a protocol like HTTP or SOAP that we easily use, and by an XML-based data format In this paper, we implement Web Services that process dip data by computers in enterprise accounts in order to enhance the transparency and productivity of enterprises. we analyse the structure of slip data, design dip database, implement stored procedures for manipulating data of slip database, and make thorn controlled by Web Services. The result of this paper will contribute to the standardization and activation of accounting process systems for e-business area.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.4
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• pp.95-105
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• 2021

Road surface damage detection is essential for a comfortable driving environment and the prevention of safety accidents. Road management institutes are using automated technology-based inspection equipment and systems. As one of these automation technologies, a sensor to detect road surface damage plays an important role. For this purpose, several studies on sensors using deep learning have been conducted in recent years. Road images and label images are needed to develop such deep learning algorithms. On the other hand, considerable time and labor will be needed to secure label images. In this paper, the adversarial learning method, one of the semi-supervised learning techniques, was proposed to solve this problem. For its implementation, a lightweight deep neural network model was trained using 5,327 road images and 1,327 label images. After experimenting with 400 road images, a model with a mean intersection over a union of 80.54% and an F1 score of 77.85% was developed. Through this, a technology that can improve recognition performance by adding only road images was developed to learning without label images and is expected to be used as a technology for road surface management in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1272-1278
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• 2022

The government enacted and promulgated the 'Severe Accident Punishment Act' in January 2021 and is implementing this law. However, the number of occupational accidents in 2021 increased by 10.7% compared to the same period of the previous year. Therefore, safety measures are urgently needed in the industrial field. In this study, BLE Mesh networking technology is applied for safety management of high-risk industrial sites with poor communication environment. The complex sensor AIoT device collects gas sensing values, voice and motion values in real time, analyzes the information values through artificial intelligence LSTM algorithm and CNN algorithm, and recognizes dangerous situations and transmits them to the server. The server monitors the transmitted risk information in real time so that immediate relief measures are taken. By applying the AIoT device and safety management system proposed in this study to high-risk industrial sites, it will minimize industrial accidents and contribute to the expansion of the social safety net.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.87-89
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• 2022

Recently, as more consumers spend more time at home due to COVID-19, the time spent on digital consumption such as SNS and OTT, which can be easily used non-face-to-face, naturally increased. Since 2019, when COVID-19 occurred, digital consumption has doubled from 44% to 82%, and it is important to quickly and accurately grasp and apply trends by analyzing consumers' emotions due to the rapidly changing digital characteristics. However, there are limitations in actually implementing services using emotional analysis in small systems rather than large-scale systems, and there are not many cases where they are actually serviced. However, if even a small system can easily analyze consumer trends, it will help the rapidly changing modern society. In this paper, we propose a lightweight trend analysis system that builds a learning network through Transfer Learning (Fine Tuning) of the BERT Model and interlocks Crawler for real-time data collection.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.1-7
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• 2023

The advent of deep learning technologies has led to the development of various medical applications, making healthcare services more convenient and effective. Among these applications, heart rate estimation is considered a vital method for assessing an individual's health. Traditional methods, such as photoplethysmography through smart watches, have been widely used but are invasive and require additional hardware. Recent advancements allow for contactless heart rate estimation through facial image analysis, providing a more hygienic and convenient approach. In this paper, we propose a lightweight methodology capable of accurately estimating heart rate in mobile environments, using a specialized 2-channel network structure based on 2D convolution. Our method considers both subtle facial movements and color changes resulting from blood flow and muscle contractions. The approach comprises two major components: an Encoder for analyzing image features and a regression layer for evaluating Blood Volume Pulse. By incorporating both features simultaneously our methodology delivers more accurate results even in computing environments with limited resources. The proposed approach is expected to offer a more efficient way to monitor heart rate without invasive technology, particularly well-suited for mobile devices.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.3
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• pp.231-242
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• 2004

Remote control and monitoring of information appliances require RTOS and TCP/IP network module to communicate each other. Traditional TCP/IP protocol stacks, however, require relatively large resources to be useful in small 8 or 16-bit systems both in terms of code size and memory usage. It motivates design and implementation of micro TCP/IP that is lightweight for embedded systems. Micro embedded web server is also required to control and monitor information appliances through the Web. In this paper, we design and implement micro TCP/IP and Web server for information appliances. For this goal, we investigate requirements for the interoperability of embedded systems with the Internet and the Web-based control of embedded systems. Next, we compare our micro TCP/IP protocol stack with that of RTIP and QPlus in terms of object code size and performance. The size of micro TCP/IP protocol stack can be reduced by 3/2 and 1/4, respectively, comparing with that of RTIP and QPlus. We also show that the performance of our micro TCP/IP is similar to that of RTIP and QPlus since it handles 2.9Mbps when delayed ACK is not adapted.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.5
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• pp.394-400
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• 2013

WoT (Web of Things) was proposed to realize intelligent thing to thing communications using WEB standard technology. It is difficult to adapt security protocols suited for existing Internet communications into WoT directly because WoT includes LLN(Low-power, Lossy Network) and resource constrained sensor devices. Recently, IETF standard group propose to use DTLS protocol for supporting security services in WoT environments. However, DTLS protocol is not an efficient solution for supporting end to end security in WoT since it introduces complex handshaking procedures and high communication overheads. We, therefore, divide WoT environment into two areas- one is DTLS enabled area and the other is an area using lightweight security scheme in order to improve them. Then we propose a mutual authentication scheme and a session key distribution scheme for the second area. The proposed system utilizes a smart device as a mobile gateway and WoT proxy. In the proposed authentication scheme, we modify the ISO 9798 standard to reduce both communication overhead and computing time of cryptographic primitives. In addition, our scheme is able to defend against replay attacks, spoofing attacks, select plaintext/ciphertext attacks, and DoS attacks, etc.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.9
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• pp.293-300
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• 2014

TDMA(Time Division Multiple Access) is a channel access scheme for shared medium networks. The shared frequency is divided into multiple time slots, some of which are assigned to a user for communication. Techniques for TDMA can be categorized into two classes: synchronous and asynchronous. Synchronization is not suitable for small scale networks because it is complicated and requires additional equipments. In contrast, in DESYNC, a biologically-inspired algorithm, the synchronization can be easily achieved without a global clock or other infrastructure overhead. However, DESYNC spends a great deal of time to complete synchronization and does not guarantee the maximum time to synch completion. In this paper, we propose a lightweight synchronization scheme, C-DESYNC, which counts the number of participating nodes with GP (Global Packet) signal including the information about the starting time of a period. The proposed algorithm is mush simpler than the existing synchronization TDMA techniques in terms of cost-effective method and guarantees the maximum time to synch completion. Our simulation results show that C-DESYNC guarantees the completion of the synchronization process within only 3 periods regardless of the number of nodes.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.17-25
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• 2023

In this paper, we propose a model that can perform human pose estimation through a MobileViT-based model with fewer parameters and faster estimation. The based model demonstrates lightweight performance through a structure that combines features of convolutional neural networks with features of Vision Transformer. Transformer, which is a major mechanism in this study, has become more influential as its based models perform better than convolutional neural network-based models in the field of computer vision. Similarly, in the field of human pose estimation, Vision Transformer-based ViTPose maintains the best performance in all human pose estimation benchmarks such as COCO, OCHuman, and MPII. However, because Vision Transformer has a heavy model structure with a large number of parameters and requires a relatively large amount of computation, it costs users a lot to train the model. Accordingly, the based model overcame the insufficient Inductive Bias calculation problem, which requires a large amount of computation by Vision Transformer, with Local Representation through a convolutional neural network structure. Finally, the proposed model obtained a mean average precision of 0.694 on the MS COCO benchmark with 3.28 GFLOPs and 9.72 million parameters, which are 1/5 and 1/9 the number compared to ViTPose, respectively.