• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.9
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• pp.707-714
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• 2013

IoT, which can be regarded as an enhanced version of M2M communication technology, was proposed to realize intelligent thing to thing communications by utilizing Internet connectivity. Things in IoT are generally heterogeneous and resource constrained. Also such things are connected with each other over LLN(low power and lossy Network). Confidentiality, mutual authentication and message origin authentication are required to make a secure service in IoT. Security protocols used in traditional IP Networks cannot be directly adopted to resource constrained devices in IoT. Under the respect, a IETF standard group proposes to use lightweight version of DTLS protocol for supporting security services in IoT environments. However, the protocol can not cover up all of very constrained devices. To solve the problem, we propose a scheme which tends to support mutual authentication and session key agreement between devices that contain only a single crypto primitive module such as hash function or cipher function because of resource constrained property. The proposed scheme enhances performance by pre-computing a session key and is able to defend various attacks.

• Journal of KIISE:Software and Applications
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• v.31 no.9
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• pp.1233-1245
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• 2004

Though biometrics to authenticate a person is a good tool in terms of security and convenience, typical authentication algorithms using biometrics may not be executed on resource-constrained devices such as smart cards. Thus, to execute biometric processing on resource-constrained devices, it is desirable to develop lightweight authentication algorithm that requires only small amount of memory and computation. Also, among biological features, face is one of the most acceptable biometrics, because humans use it in their visual interactions and acquiring face images is non-intrusive. We present a new face authentication algorithm in this paper. Our achievement is two-fold. One is to present a face authentication algorithm with low memory requirement, which uses support vector machines (SVM) with the feature set extracted by genetic algorithms (GA). The other contribution is to suggest a method to reduce further, if needed, the amount of memory required in the authentication at the expense of verification rate by changing a controllable system parameter for a feature set size. Given a pre-defined amount of memory, this capability is quite effective to mount our algorithm on memory-constrained devices. The experimental results on various databases show that our face authentication algorithm with SVM whose input vectors consist of discriminating features extracted by GA has much better performance than the algorithm without feature selection process by GA has, in terms of accuracy and memory requirement. Experiment also shows that the number of the feature ttl be selected is controllable by a system parameter.

• The KIPS Transactions:PartA
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• v.9A no.4
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• pp.467-478
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• 2002

With the rapid development of wired or wireless Internet, various kinds of resource constrained mobile devices, such as cellular phone, PDA, homepad, smart phone, handhold PC, and so on, have been emerging into personal or commercial usages. Most software to be embedded into those devices has been forced to have the characteristic of flexibility rather than the fixedness which was an inherent property of embedded system. It means that recent technologies require the flexible embedding into the variety of resource constrained mobile devices. A document processor for XML which has been positioned as a standard mark-up language for information representation on the Web, is one of the essential software to be embedded into those devices for browsing the information. In this paper, a framework for configurable XML processor called EmXJ is designed and implemented for flexible embedding into various types of resource constrained mobile devices, and its advantages are compared to conventional XML processors.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.147-153
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• 2016

Recently, IETF (Internet Engineering Task) working group has adopted CoAP (Constrained Application Protocol) as a standard IoT proctocol. CoAP is a specialized web transfer protocol for use with constrained nodes and constrained environment such as small memory and low power networks. In this paper, we design and implement a registration service with CoAP protocol based on RD(Resource Directory) to connect IoT nodes in mobile Internet environments. The resource directory between the mobile terminal and IoT nodes provides to discover the IoT nodes and get the context data. The mobile terminal has as the CoAP client and embedded IoT nodes includes as the CoAP server so that it can conveniently manage the constrained IoT nodes to get the context data and control devices in a mobile environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1396-1414
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• 2018

With the proliferation of the Internet of Things (IoT) healthcare devices, significant interoperability issue arises where devices use proprietary data transfer protocols. The IHE PCD-01 standard has been suggested for the exchange of healthcare data in ISO/IEEE 11073 PHD data model. However, the PCD-01 is not efficient to be used in the IoT environment. This is because the use of SOAP for PCD-01 may be too complex to be implemented in the resource-constrained IoT healthcare devices. In this paper, we have designed a communication system to implement ISO/IEEE 11073 and IHE PCD-01 integration using the IETF CoAP. More specifically, we have designed the architecture and procedures, using CoAP, to seamlessly transmit the bio-signal from the tiny resource-constrained IoT healthcare devices to the server in a standardized way. We have also built the agent, gateway, and PCD-01 interface at the server, all of which are using the CoAP as a communication protocol. In order to evaluate the performance of the proposed system, we have used the PCD data to be transmitted over CoAP, MQTT, and HTTP. The evaluation of the system performance shows that the use of CoAP results in faster transaction and lesser cost than other protocols, with less battery power consumption.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.1-6
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• 2015

The IoT(Internet of things) technology enable objects around user to be connected with each other for sharing information. To support security is the mandatory requirement in IoT because it is related to the disclosure of private information but also directly related to the human safety. However, it is difficult to apply traditional security mechanism into lightweight devices. This is owing to the fact that many IoT devices are generally resource constrained and powered by battery. PSK(Pre-Shared Key) based approach, which share secret key in advance between communication entities thereafter operate security functions, is suitable for light-weight device. That is because PSK is costly efficient than a session key establishment approach based on public key algorithm. However, how to safely set a PSK of the lightweight device in advance is a difficult issue because input/output interfaces such as keyboard or display are constrained in general lightweight devices. To solve the problem, we propose and develop a secure PSK configuration scheme for resource constrained devices in IoT.

• 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.

• Journal of information and communication convergence engineering
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• v.9 no.6
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• pp.683-688
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• 2011

The wireless sensor network (WSN) is well known for an enabling technology for the ubiquitous environment such as real-time surveillance system, habitat monitoring, home automation and healthcare applications. However, the WSN featuring wireless communication through air, a resource constraints device and irregular network topology, is threatened by malicious nodes such as eavesdropping, forgery, illegal modification or denial of services. For this reason, security in the WSN is key factor for utilizing the sensor network into the commercial way. There is a series of symmetric cryptography proposed by laboratory or industry for a long time. Among of them, recently proposed HUMMINGBIRD algorithm, motivated by the design of the well-known Enigma machine, is much more suitable to resource constrained devices, including smart card, sensor node and RFID tags in terms of computational complexity and block size. It also provides resistance to the most common attacks such as linear and differential cryptanalysis. In this paper, we implements ultra-lightweight cryptography, HUMMINGBIRD algorithm into the resource constrained device, sensor node as a perfectly customized design of sensor node.

• Journal of information and communication convergence engineering
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• v.21 no.3
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• pp.185-191
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• 2023

The Internet of Things (IoT) can be defined as the connection of devices, sensors, and actors via the Internet to a single network to provide services to end-users. Owing to the flexibility and simplicity of IoT devices, which impart convenience to end-users, the demand for these devices has increased significantly in the last decade. To make these systems more scalable, achieve a larger number of connected devices, and achieve greater economic success, it is vital to develop them by considering parameters such as security, cost, bandwidth, data rate, and power consumption. This study aims to improve energy efficiency and prolong the lifetime of IoT networks by proposing a new approach called the constrained application protocol CoAP45. This approach reduces the number of updates to the CoAP server using a centralized resource. The simulation results show that the proposed approach outperforms all existing protocols.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.12
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• pp.363-370
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• 2023

Object detection technology that accurately recognizes the road and surrounding conditions is a key technology in the field of autonomous driving. In the field of autonomous driving, object detection technology requires real-time performance as well as accuracy of inference services. Task offloading technology should be utilized to apply object detection technology for accuracy and real-time on resource-constrained devices rather than high-performance machines. In this paper, experiments such as performance comparison of task offloading, performance comparison according to input image resolution, and performance comparison according to camera object resolution were conducted and the results were analyzed in relation to the application of task offloading for real-time object detection of autonomous driving in resource-constrained devices. In this experiment, the low-resolution image could derive performance improvement through the application of the task offloading structure, which met the real-time requirements of autonomous driving. The high-resolution image did not meet the real-time requirements for autonomous driving due to the increase in communication time, although there was an improvement in performance. Through these experiments, it was confirmed that object recognition in autonomous driving affects various conditions such as input images and communication environments along with the object recognition model used.