• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.9
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• pp.1313-1318
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• 2013

In order to actively respond to cyber attacks, not only the security systems such as IDS, IPS, and Firewalls, but also ESM, a system that detects cyber attacks by analyzing various log data, are preferably deployed. However, as the attacks be come more elaborate and advanced, existing signature-based detection methods start to face their limitations. In response to that, researches upon symptom detection technology based on attack modeling by employing big-data analysis technology are actively on-going. This symptom detection technology is effective when it can accurately extract features of attacks and manipulate them to successfully execute the attack modeling. We propose the ways to extract attack features which can play a role as the basis of the modeling and detect intelligent threats by carrying out scenario-based modeling.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.762-770
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• 2014

Tangible Space Initiative (TSI) is a new framework that can provide a more natural and intuitive Human Computer Interface for users. This is composed of three cooperative components: a Tangible Interface, Responsive Cyber Space, and Tangible Agent. In this paper we present a Tangible Tele-Meeting system in TSI, which allows people to communicate with each other without any spatial limitation. In addition, we introduce a method for registering a Tangible Avatar with a Tangible Agent. The suggested method is based on relative pose estimation between the user and the Tangible Agent. Experimental results show that the user can experience an interaction environment that is more natural and intelligent than that provided by conventional tele-meeting systems.

• Journal of Intelligence and Information Systems
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• v.10 no.3
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• pp.105-114
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• 2004

In the past year, the increasing concern about the biometric recognition makes the great activities on the security fields, such as the entrance control or user authentication. In particular, although the features of face recognition, such as user friendly and non-contact made it to be used widely, unhappily it has some disadvantages of low accuracy or low Re-attempts Rates. For this reason, I suggest the new approach to re-classify the classified data of recognition result data to solve the problems. For this study, I will use the typical appearance-based, PCA(Principal Component Analysis) algorithm and verify the performance improvement by adopting the re-classification approach using 200 peoples (10 pictures per one person).

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.632-644
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• 2019

The remote monitoring and warning system for dangerous chemicals is designed with the concept of the Cyber-Physical System (CPS) in this paper. The real-time perception, dynamic control, and information service of major hazards chemicals are realized in this CPS system. The CPS system architecture, the physical layer and the applacation layer, are designed in this paper. The terminal node is mainly composed of the field collectors which complete the data acquisition of sensors and video in the physical layers, and the use of application layer makes CPS system safer and more reliable to monitor the hazardous chemicals. The cloud application layer completes the risk identification and the prediction of the major hazard sources. The early intelligent warning of the major dangerous chemicals is realized and the security risk images are given in the cloud application layer. With the CPS technology, the remote network of hazardous chemicals has been completed, and a major hazard monitoring and accident warning online system is formed. Through the experiment of the terminal node, it can be proved that the terminal node can complete the mass data collection and classify. With this experiment it can be obtained the CPS system is safe and effective. In order to verify feasible, the multi-risk warning based on CPS is simulated, and results show that the system solves the problem of hazardous chemicals enterprises safety management.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.17-26
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• 2018

Connected car plays an important role on Intelligent Transport System (ITS). ITS is able to secure drivers' convenience and safety, however, the overall system can be threatened by hacking attempt. Blockchain is one strong candidate of the remedy to promote the security of the ITS network. However, there will be many challenges to adopt previously proposed blockchain technologies to ITS. This work presents a new ITS structure based on blockchain technology. Proposed scheme includes three major layers. The first layer is central manager which is initiated once to register a certain connected car. The third layer is RSU (Road Side Unit) layer which exploits PoS (Proof of Stake) for consortium blockchains and retains real-time information. In addition, this layer performs block expiration based on timers to maintain manageable block length. In the second layer, the generated blocks of the third layer without expiration are housed as private blockchains. We finally demonstrate possible merits of newly proposed scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2399-2413
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• 2021

A recommendation system is an information filter tool, which uses the ratings and reviews of users to generate a personalized recommendation service for users. However, the cold-start problem of users and items is still a major research hotspot on service recommendations. To address this challenge, this paper proposes a high-efficient hybrid recommendation system based on Fuzzy C-Means (FCM) clustering and supervised learning models. The proposed recommendation method includes two aspects: on the one hand, FCM clustering technique has been applied to the item-based collaborative filtering framework to solve the cold start problem; on the other hand, the content information is integrated into the collaborative filtering. The algorithm constructs the user and item membership degree feature vector, and adopts the data representation form of the scoring matrix to the supervised learning algorithm, as well as by combining the subjective membership degree feature vector and the objective membership degree feature vector in a linear combination, the prediction accuracy is significantly improved on the public datasets with different sparsity. The efficiency of the proposed system is illustrated by conducting several experiments on MovieLens dataset.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.208-214
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• 2021

Recently, much of the intelligent security scenario and criminal investigation demands for matching photo and non-photo. Existing face recognition system can not sufficiently guarantee these needs. In this paper, we propose an algorithm to improve the performance of heterogeneous face recognition systems by reducing the different modality between sketches and photos of the same person. The proposed algorithm extracts each image's texture features through texture descriptors (gray level co-occurrence matrix, multiscale local binary pattern), and based on this, generates a transformation matrix through eigenfeature regularization and extraction techniques. The score value calculated between the vectors generated in this way finally recognizes the identity of the sketch image through the score normalization methods.

• Geomechanics and Engineering
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• v.30 no.4
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• pp.383-392
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• 2022

Although pipelines are composed of segmental tubes commonly connected by rubber gasket or push-in joints, current studies mainly simplified pipelines as continuous structures. Effects of joints on three-dimensional deformation mechanisms of existing pipelines due to tunnel excavation are not fully understood. By conducting three-dimensional numerical analyses, effects of pipeline burial depth, tunnel burial depth, volume loss, pipeline stiffness and joint stiffness on bending strain and joint rotation of existing pipelines are explored. By increasing pipeline burial depth or decreasing tunnel cover depth, tunneling-induced pipeline deformations are substantially increased. As tunnel volume loss varies from 0.5% to 3%, the maximum bending strains and joint rotation angles of discontinuous pipelines increase by 1.08 and 9.20 times, respectively. By increasing flexural stiffness of pipe segment, a dramatic increase in the maximum joint rotation angles is observed in discontinuous pipelines. Thus, the safety of existing discontinuous pipelines due to tunnel excavation is controlled by joint rotation rather than bending strain. By increasing joint stiffness ratio from 0.0 (i.e., completely flexible joints) to 1.0 (i.e., continuous pipelines), tunneling-induced maximum pipeline settlements decrease by 22.8%-34.7%. If a jointed pipeline is simplified as a continuous structure, tunneling-induced settlement is thus underestimated, but bending strain is grossly overestimated. Thus, joints should be directly simulated in the analysis of tunnel-soil-pipeline interaction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2882-2903
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• 2022

Image super-resolution (SR) processing is of great value in the fields of digital image processing, intelligent security, film and television production and so on. This paper proposed a densely connected deep learning network based on cascade architecture, which can be used to solve the problem of super-resolution in the field of image quality enhancement. We proposed a more efficient residual scaling dense block (RSDB) and the multi-channel cascade architecture to realize more efficient feature reuse. Also we proposed a hybrid loss function based on L₁ error and L_∞ error to achieve better L_∞ error performance. The experimental results show that the overall performance of the network is effectively improved on cascade architecture and residual scaling. Compared with the residual dense net (RDN), the PSNR / SSIM of the new method is improved by 2.24% / 1.44% respectively, and the L_∞ performance is improved by 3.64%. It shows that the cascade connection and residual scaling method can effectively realize feature reuse, improving the residual convergence speed and learning efficiency of our network. The L_∞ performance is improved by 11.09% with only a minimal loses of 1.14% / 0.60% on PSNR / SSIM performance after adopting the new loss function. That is to say, the L_∞ performance can be improved greatly on the new loss function with a minor loss of PSNR / SSIM performance, which is of great value in L_∞ error sensitive tasks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4224-4243
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• 2021

Cognitive radio (CR) is a feasible intelligent technology and can be used as an effective solution to spectrum scarcity and underutilization. As the key function of CR, cooperative spectrum sensing (CSS) is able to effectively prevent the harmful interference with primary users (PUs) and identify the available spectrum resources by exploiting the spatial diversity of multiple secondary users (SUs). However, the open nature of the cognitive radio networks (CRNs) framework makes CSS face many security threats, such as, the malicious user (MU) launches Byzantine attack to undermine CRNs. For this aim, we make an in-depth analysis of the motive and purpose from the MU's perspective in the interweave CR system, aiming to provide the future guideline for defense strategies. First, we formulate a dynamic Byzantine attack model by analyzing Byzantine behaviors in the process of CSS. On the basis of this, we further make an investigation on the condition of making the fusion center (FC) blind when the fusion rule is unknown for the MU. Moreover, the throughput and interference to the primary network are taken into consideration to evaluate the impact of Byzantine attack on the interweave CR system, and then analyze the optimal strategy of Byzantine attack when the fusion rule is known. Finally, theoretical proofs and simulation results verify the correctness and effectiveness of analyses about the impact of Byzantine attack strategy on the throughput and interference.