• Journal of the Korea Society of Computer and Information
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• v.26 no.2
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• pp.89-97
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• 2021

Blockchain is designed to collect and store the data recorded on the network in one block unit, and is connected and stored back and forth, and its form is similar to how the blocks are connected, so it is called a blockchain. Many companies are trying to popularize blockchain-based services at home and abroad, and blockchains are used in various industries. This study introduces the technical characteristics of the blockchain and deals with application services utilizing the blockchain. Introducing 5 types of blockchain architecture and core technologies and introducing blockchain application services that are used in payment services, blockchain service networks, blockchain real estate platforms, identity verification, cryptocurrency, diamond distribution path tracking, and blog information recording. do. It is expected to increase the understanding of the blockchain and provide usefulness in future blockchain research and service development.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.56-62
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• 2021

High forecast accuracy is required as social issues on particulate matter increase. Therefore, many attempts are being made using machine learning to increase the accuracy of particulate matter prediction. However, due to problems with the distribution of imbalance in the concentration and various characteristics of particulate matter, the learning of prediction models is not well done. In this paper, to solve these problems, a binary classification model was proposed to predict the concentration of particulate matter needed for prediction by dividing it into two classes based on the value of 80㎍/㎥. Four classification algorithms were utilized for the binary classification of PM10. Classification algorithms used logistic regression, decision tree, SVM, and MLP. As a result of performance evaluation through confusion matrix, the MLP model showed the highest binary classification performance with 89.98% accuracy among the four models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2496-2512
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• 2021

The requirements for powerful computing capability, high capacity, low latency and low energy consumption of emerging services, pose severe challenges to the fifth-generation (5G) network. As a promising paradigm, mobile edge networks can provide services in proximity to users by deploying computing components and cache at the edge, which can effectively decrease service delay. However, the coexistence of heterogeneous services and the sharing of limited resources lead to the competition between various services for multiple resources. This paper considers two typical heterogeneous services: computing services and content delivery services, in order to properly configure resources, it is crucial to develop an effective offloading and caching strategies. Considering the high energy consumption of 5G base stations, this paper considers the hybrid energy supply model of traditional power grid and green energy. Therefore, it is necessary to design a reasonable association mechanism which can allocate more service load to base stations rich in green energy to improve the utilization of green energy. This paper formed the joint optimization problem of computing offloading, caching and resource allocation for heterogeneous services with the objective of minimizing the on-grid power consumption under the constraints of limited resources and QoS guarantee. Since the joint optimization problem is a mixed integer nonlinear programming problem that is impossible to solve, this paper uses deep reinforcement learning method to learn the optimal strategy through a lot of training. Extensive simulation experiments show that compared with other schemes, the proposed scheme can allocate resources to heterogeneous service according to the green energy distribution which can effectively reduce the traditional energy consumption.

• New Physics: Sae Mulli
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• v.68 no.11
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• pp.1173-1182
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• 2018

Mesoporous silica allows proper hydration of an ion exchange membrane under low relative humidity due to its strong hydrophilicity and structural characteristic. A mesoporous silica and Nafion composite membrane shows good proton conductivity under low relative humidity. An understanding of ion-channel formation and proton transfer through an ion-channel network in mesoporous silica and Nafion composite membranes is essential for the development and the optimization of ion exchange membranes. In this study, a mesoporous cellular foam $SiO_2/Nafion$ composite membrane is fabricated, and its proton conductivity and performance are measured. Also, the ion-channel distribution is analyzed by using electrostatic force microscopy to measure the surface charge density of the mesoporous cellular foam $SiO_2/Nafion$ composite membrane. The research reveals a few remarkable results. First, the composite membrane shows excellent proton conductivity and performance under low relative humidity. Second, the composite membrane is observed to form ion-channel-rich and ion-channel-poor region locally.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.2
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• pp.97-105
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• 2008

The various mutations of the malicious codes are fast generated on the network. Also the behaviors of them become intelligent and the damage becomes larger step by step. In this paper, we suggest the method to select the useful measures for the detection of the codes. The method has the advantage of shortening the detection time by using header data without payloads and uses connection data that are composed of TCP/IP packets, and much information of each connection makes use of the measures. A naive estimator is applied to the probability distribution that are calculated by the histogram estimator to select the specific measures among 80 measures for the useful detection. The useful measures are then selected by using relative entropy. This method solves the problem that is to misclassify the measure values. We present the usefulness of the proposed method through the result of the detection experiment using the detection patterns based on the selected measures.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.5
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• pp.3-11
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• 2005

This paper presents a performance analysis model based on an M/M/1 queue and Poisson distribution of input data traffic. The simulation on a pipelined AES system with processing rate of 10 rounds per clock shows $4.0\%$ higher performance than a non-pipelined version consuming 10 clocks per transaction. Physical implementation of pipelined AES with FPGA takes 3.5 times bigger gate counts than the non-pipelined version whereas the pipelined version yields only $3.5\%$ performance enhancement. The proposed analysis model can be used to optimize cost-performance of AES hardware designs.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.427-438
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• 2012

The SCADA(Supervisory Control and Data Acquisition) systems are used to control some critical national infrastructures such as electricity, gas, and water distribution systems. Recently, there are many researches on key management scheme for secure communication due to change to the open network environment. We propose a new key management method which is established on ID-based cryptosystem using pairing on MTU(Master Terminal Unit), Sub-MTU, and RTU(Remote Terminal Unit). Furthermore, we present a redistribution protocol of private key of each device and a system recovery protocol as a countermeasure of exposure of KMS(Key Management System) master key which is occurred by some unexpected accidents or malicious attacks.

• Journal of Internet of Things and Convergence
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• v.7 no.2
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• pp.7-12
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• 2021

Wisdom Contents are created with experiences and ideas of multiple authors, and consumed in Internet based Social Network Services that are not subjected to regional restrictions. Existing copyright management systems are designed for the protection of professional authors' rights, and effective in domestic area. On the contrary, the blockchain protocol is subjected to the service and the block is added by the consensus of participating nodes. If the data is stored to the blockchain, it cannot be modified or deleted. In this paper, we propose the blockchain based undeniable multi-signature scheme for the protection of multiple authorship on Wizdom Contents. The proposed scheme is consisted of co-authors' common public key generation, multi-signature generation and verification protocols. In the undeniable signature scheme, the signature cannot be verified without help of the signer. The proposed scheme is best suited to the contents purchase protocol. All co-authors cannot deny the fairness of the automated profit distribution through the verification of multiple authorship on Wizdom Contents.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1053-1065
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• 2020

With the recent development of hardware performance and artificial intelligence technology, sophisticated fake videos that are difficult to distinguish with the human's eye are increasing. Face synthesis technology using artificial intelligence is called Deepfake, and anyone with a little programming skill and deep learning knowledge can produce sophisticated fake videos using Deepfake. A number of indiscriminate fake videos has been increased significantly, which may lead to problems such as privacy violations, fake news and fraud. Therefore, it is necessary to detect fake video clips that cannot be discriminated by a human eyes. Thus, in this paper, we propose a deep-fake detection model applied with Bidirectional Convolution LSTM and Attention Module. Unlike LSTM, which considers only the forward sequential procedure, the model proposed in this paper uses the reverse order procedure. The Attention Module is used with a Convolutional neural network model to use the characteristics of each frame for extraction. Experiments have shown that the model proposed has 93.5% accuracy and AUC is up to 50% higher than the results of pre-existing studies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.1102-1108
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• 2020

Mobile edge computing is a technology that can prepare for a new era of cloud computing and compensate for shortcomings by processing data near the edge of the network where data is generated rather than centralized data processing. It is possible to realize a low-latency/high-speed computing service by locating computing power to the edge and analyzing data, rather than in a data center far from computing and processing data. In this article, we develop a virtual mobile edge computing testbed environment where the cloud and edge nodes divide computing tasks from mobile terminals using the EdgeCloudSim simulator. Performance of offloading techniques for distribution of computing tasks from mobile terminals between the central cloud and mobile edge computing nodes is evaluated and analyzed under the virtual mobile edge computing environment. By providing a virtual mobile edge computing environment and offloading capabilities, we intend to provide prior knowledge to industry engineers for building mobile edge computing nodes that collaborate with the cloud.