• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4B
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• pp.165-173
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• 2008

In this paper, we propose a new reliable broadcast protocol referred to as timer-based reliable broadcast (TRB) for wireless sensor networks (WSNs). The proposed TRB scheme exploits (1) bitmap based explicit ACK to effectively reduce the unnecessary error control messages and (2) randomized timer for ACK transmission to substantially reduce the possibility of contentions. Although it has been argued that 100% reliability is not necessary in WSNs, there should be messages (such as mission-critical message, task assignment, software updates, etc.) that need to be reliably delivered to the entire sensor field. We propose to use the TRB algorithm for such cases. Performance evaluation shows that the TRB scheme achieves 100 % reliability significantly better than other schemes with expense of slightly increased energy consumption.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.949-958
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• 2004

race detection using a boosting based algorithm requires a very large size of face and nonface data. In addition, the fact that there always occurs a need for adding additional training data for better detection rates demands an efficient incremental teaming algorithm. In the design of incremental teaming based classifiers, the final classifier should represent the characteristics of the entire training dataset. Conventional methods have a critical problem in combining intermediate classifiers that weight updates depend solely on the performance of individual dataset. In this paper, for the purpose of application to face detection, we present a new method to combine an intermediate classifier with previously acquired ones in an optimal manner. Our algorithm creates a validation set by incrementally adding sampled instances from each dataset to represent the entire training data. The weight of each classifier is determined based on its performance on the validation set. This approach guarantees that the resulting final classifier is teamed by the entire training dataset. Experimental results show that the classifier trained by the proposed algorithm performs better than by AdaBoost which operates in batch mode, as well as by ${Learn}^{++}$.

• Smart Structures and Systems
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• v.15 no.1
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• pp.135-150
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• 2015

Large concrete structures are prone to cracks and damages over time from human usage, weathers, and other environmental attacks such as flood, earthquakes, and hurricanes. The health of the concrete structures should be monitored regularly to ensure safety. A reliable method of real time communications can facilitate more frequent structural health monitoring (SHM) updates from hard to reach positions, enabling crack detections of embedded concrete structures as they occur to avoid catastrophic failures. By implementing an unconventional mode of communication that utilizes guided stress waves traveling along the concrete structure itself, we may be able to free structural health monitoring from costly (re-)installation of communication wires. In stress-wave communications, piezoelectric transducers can act as actuators and sensors to send and receive modulated signals carrying concrete status information. The new generation of lead zirconate titanate (PZT) based smart aggregates cause multipath propagation in the homogeneous concrete channel, which presents both an opportunity and a challenge for multiple sensors communication. We propose a time reversal based pulse position modulation (TR-PPM) communication for stress wave communication within the concrete structure to combat multipath channel dispersion. Experimental results demonstrate successful transmission and recovery of TR-PPM using stress waves. Compared with PPM, we can achieve higher data rate and longer link distance via TR-PPM. Furthermore, TR-PPM remains effective under low signal-to-noise (SNR) ratio. This work also lays the foundation for implementing multiple-input multiple-output (MIMO) stress wave communication networks in concrete channels.

• Journal of Navigation and Port Research
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• v.45 no.2
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• pp.61-68
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• 2021

Logistics movement using ships has been used for many centuries, but maritime accidents are still difficult to predict and they occur on a large scale. The International Maritime Organization (IMO) made it mandatory to install Electronic Chart Display and Information System (ECDIS) for safe seas, but S-57 standards applied to equipment were not updated over 30 years. In addition, it is difficult to keep the equipment up-to-date and revise standards as ships move around the world. In consideration of the limitations of S-57, the IHO developed the new standard as S-100 rather than an update of the S-57. In this study, the previously developed S-100 tool and S/W were configured as one platform and applied to the S-100 ECDIS. The platform conducts as the S-100 cycle and ecosystem from the creation of standards to release and practical use in ships. The hydrographic information standard is machine-readable as defined in S-100, and it has been validated that the latest standard can be applied using the Plug and Play (PnP) function without software system updates. It is expected that international organization such as the International Hydrographic Office (IHO) and the International Association of Marine Aids to Navigation and Lighthouse Authorities (IALA) shall develop and release standards and mariners can easily apply the latest standards to equipment through the machine-readable platform.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2964-2985
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• 2019

Global data center IP traffic is expected to reach 20.6 zettabytes (ZB) by the end of 2021. Intra-data center networks (Intra-DCN) will account for 71.5% of the data center traffic flow and will be the largest portion of the traffic. The understanding of traffic distribution in IntraDCN is still sketchy. It causes significant amount of bandwidth to go unutilized, and creates avoidable choke points. Conventional transport protocols such as Optical Packet Switching (OPS) and Optical Burst Switching (OBS) allow a one-sided view of the traffic flow in the network. This therefore causes disjointed and uncoordinated decision-making at each node. For effective resource planning, there is the need to consider joining the distributed with centralized management which anticipates the system's needs and regulates the entire network. Methods derived from Kalman filters have proved effective in planning road networks. Considering the network available bandwidth as data transport highways, we propose an intelligent enhanced SDN concept applied to OBS architecture. A management plane (MP) is added to conventional control (CP) and data planes (DP). The MP assembles the traffic spatio-temporal parameters from ingress nodes, uses Kalman filtering prediction-based algorithm to estimate traffic demand. Prior to packets arrival at edges nodes, it regularly forwards updates of resources allocation to CPs. Simulations were done on a hybrid scheme (1+1) and on the centralized OBS. The results demonstrated that the proposition decreases the packet loss ratio. It also improves network latency and throughput-up to 84 and 51%, respectively, versus the traditional scheme.

• Journal of Industrial Convergence
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• v.16 no.2
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• pp.25-31
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• 2018

An APT attack is a new hacking technique that continuously attacks specific targets and is called an APT attack in which a hacker exploits various security threats to continually attack a company or organization's network. Protect employees in a specific organization and access their internal servers or databases until they acquire significant assets of the company or organization, such as personal information leaks or critical data breaches. Also, APT attacks are not attacked at once, and it is difficult to detect hacking over the years. This white paper examines ongoing APT attacks and identifies, educates, and proposes measures to build a security management system, from the executives of each organization to the general staff. It also provides security updates and up-to-date antivirus software to prevent malicious code from infiltrating your company or organization, which can exploit vulnerabilities in your organization that could infect malicious code. And provides an environment to respond to APT attacks.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.1
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• pp.41-55
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• 2005

A group key agreement protocol allows a group of user to share a key which may later be used to achieve certain cryptographic goals. In this paper, we propose a new scalable two-round ID-based group key agreement protocol which would be well fit to a Pay-TV system, additionally. to the fields of internet stock quotes, audio and music deliveries, software updates and the like. Our protocol improves the three round poop key agreement protocol of Nam et al., resulting in upgrading the computational efficiency by using the batch verification technique in pairing-based cryptography. Also our protocol simplifies the key agreement procedures by utilizing ID-based system. We prove the security of our protocol under the Computational Diffie-Hellman assumption and the Bilinear Decisional Diffie-Hellman assumption. Also we analyze its efficiency.

• Journal of Industrial Convergence
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• v.20 no.7
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• pp.57-64
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• 2022

There are various structures in the underground space, and the structures is managed as 3D data in Integrated Underground Geospatial Map Management System(IUGMMS). The worker transmits and updates the integrated map including the changed underground geospatial data to IUGMMS with the completed book submission program. However, there is a problem in that the transmission time and the update time is delayed because the size of the integrated map file is large. In this paper, we try to extract and transmit only the changed integrated map by obtaining and comparing each spatial characteristic information of the integrated map. As a result of the experiment, the transmission time of the suggestion method is short and the update time is also short than the transitional method because the suggestion method transmits only the integrated map including the changed underground geospatial data. As a result, it was possible to reduce the delay time in transmitting and updating the changed integrated map.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.197-202
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• 2022

IoT (Internet of Things) devices are being attacked by malware due to many security vulnerabilities, such as the use of weak IDs/passwords and unauthenticated firmware updates. However, due to the diversity of CPU architectures, it is difficult to set up a malware analysis environment and design features. In this paper, we design time series features using the byte sequence of executable files to represent independent features of CPU architectures, and analyze them using recurrent neural networks. The proposed feature is a fixed-length time series pattern extracted from the byte sequence by calculating partial entropy and applying linear interpolation. Temporary changes in the extracted feature are analyzed by RNN and LSTM. In the experiment, the IoT malware detection showed high performance, while low performance was analyzed in the malware family classification. When the entropy patterns for each malware family were compared visually, the Tsunami and Gafgyt families showed similar patterns, resulting in low performance. LSTM is more suitable than RNN for learning temporal changes in the proposed malware features.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.13-18
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• 2022

In this paper, we proposed VW-FedAVG(Validation based Weighted FedAVG) which updates the global model by weighting according to performance verification from the models of each device participating in the training. The first method is designed to validate each local client model through validation dataset before updating the global model with a server side validation structure. The second is a client-side validation structure, which is designed in such a way that the validation data set is evenly distributed to each client and the global model is after validation. MNIST, CIFAR-10 is used, and the IID, Non-IID distribution for image classification obtained higher accuracy than previous studies.