• KIPS Transactions on Software and Data Engineering
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• v.4 no.3
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• pp.129-134
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• 2015

Since automatic social engineering based spam attacks induce for users to click or receive the short message service (SMS), e-mail, site address and make a relationship with an unknown friend, it is very easy for them to active in online social networks. The previous spam detection schemes only apply manual filtering of the system managers or labeling classifications regardless of the features of social networks. In this paper, we propose the spam detection metric after reflecting on a couple of features of social networks followed by analysis of real social network data set, Twitter spam. In addition, we provide the online social networks based unsupervised scheme for automated social engineering spam with self organizing map (SOM). Through the performance evaluation, we show the detection accuracy up to 90% and the possibility of real time training for the spam detection without the manager.

• Journal of Korea Multimedia Society
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• v.11 no.10
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• pp.1338-1346
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• 2008

In this paper, we propose a new P2P-based music recommendation system. In comparison with previous system in client-server environment, the proposed system shows higher quality of music recommendation through real-time sharing of music preference information between peers. A collaborative filtering is implemented as a recommendation algorithm. As a user preference profile, we use the inherit KID music genre index contained in all legitimate music file instead of music feature vectors as in previous research so that the proposed system can mitigate the performance degradation and high computational load caused by feature inaccuracy and feature extraction. The performance of the proposed system is evaluated in various ways with real 16-weeks transaction data provided by Korean music portal, 5 company and it shows comparative quality of recommendation with only small amount of computational load.

• Journal of Advanced Navigation Technology
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• v.13 no.6
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• pp.901-906
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• 2009

This paper proposes a call admission control(CAC) method for wireless networks, which is based on the upper bound of a possibility distribution of handoff calls dropping rates. The possibility distribution is estimated in a fuzzy inference and a learning algorithm in neural network. The learning algorithm is considered for tuning the membership functions(then parts)of fuzzy rules for the inference. The fuzzy inference method is based on a weighted average of fuzzy sets. The proposed method can avoid estimating excessively large handoff calls dropping rates, and makes possibile self-compensation in real time for the case where the estimated values are smaller than real values. So this method makes secure CAC, thereby guaranteeing the allowed CDR. From simulation studies we show that the estimation performance for the upper bound of call dropping rate is good, and then handoff call dropping rates in CAC are able to be sustained below user's desired value.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.49-56
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• 2020

Detecting shadows in images and restoring or removing them was a very challenging task in computer vision. Traditional researches used color information, edges, and thresholds to detect shadows, but there were errors such as not considering the penumbra area of shadow or even detecting a black area that is not a shadow. Deep learning has been successful in various fields of computer vision, and research on applying deep learning has started in the field of shadow detection and removal. However, it was very difficult and time-consuming to collect data for network learning, and there were many limited conditions for shooting. In particular, it was more difficult to obtain shadow data from buildings and satellite images, which hindered the progress of the research. In this paper, we propose a method for generating shadow data from buildings and satellites using Unity3D. In the virtual Unity space, 3D objects existing in the real world were placed, and shadows were generated using lights effects to shoot. Through this, it is possible to get all three types of images (shadow-free, shadow image, shadow mask) necessary for shadow detection and removal when training deep learning networks. The method proposed in this paper contributes to helping the progress of the research by providing big data in the field of building or satellite shadow detection and removal research, which is difficult for learning deep learning networks due to the absence of data. And this can be a suboptimal method. We believe that we have contributed in that we can apply virtual data to test deep learning networks before applying real data.

• KIEE International Transactions on Power Engineering
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• v.4A no.4
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• pp.171-177
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• 2004

In the current age of the information oriented society in which we live, many people use PCs and are dependant on the databases provided by the network server. However, online data can be missed during the occurrence of a blackout and furthermore, power failure can greatly effect Power Quality. This has resulted in the trend of using interruption-free live-line work when trouble occurs in a power system. However, 83% of the population receives an electric shock experience when a laborer is performing interruption-free live-line work. In the interruption-free method, education and training problems have been pinpointed. However, there are few instructors to implement the necessary training. Furthermore, the trainees undergo only a short training period of just 4 weeks. In this paper, to develop a method with no restrictions on time and place and to ensure a reduction in the misuse of materials, immersion type virtual reality (or environment) technology is used. The users of a 3D immersion type VR training system can interact with the system by performing the equivalent action in a safe environment. Thus, it can be valuable to apply this training system to such dangerous work as 'Interruption-free live-line work exchanging COS (Cut-Out-Switch)'. In this program, the user carries out work according to instructions displayed through the window and speaker and cannot perform other tasks until each part of the task is completed in the proper sequence. The workers using this system can utilize their hands and viewpoint movement since they are in a real environment but the trainee cannot use all parts and senses of a real body with the current VR technology. Despite these weak points, when we consider the trends of improvement in electrical devices and communication technology, we can say that 3D graphic VR application has high potentiality.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.1003-1010
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• 2018

The geomagnetic sensor nodes are usually designed with wireless communication and battery for easy installation on the road without cable connection and wiring. To minimize operation cost of a system, it is important to prolong the battery lifetime of the geomagnetic sensors installed on the road. In this paper, we propose a low-power TDMA MAC protocol that reduces energy consumption while guaranteeing the real-time vehicle detection information in the vehicle detection system. The performance evaluations are conducted through a real testbed of a vehicle detection system, and it proves that the proposed low-power protocols provides 5 year lifetime by improving energy efficiency up to about 62%.

• Journal of Korea Water Resources Association
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• v.54 no.8
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• pp.589-597
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• 2021

In this study, corrosion depth equation was suggested according to real measured corrosion data, and then management indexes of pipe network which can determine the deterioration rate and safety rate has been established and applied to real pipe networks. Furthermore, reliability analysis and management index analysis have been conducted to estimate and compare the deterioration rate. From the results of reliability analysis, it was found that probability of failure of 200 mm steel pipe can be increased from 4.36% at present time to 8.23% after 20years at Gaduk and from 7.35% to 12.99% at Nami. From the results of management index analysis, it was found that deterioration rates of Gaduk and Nami are 1.009 and 1.174, respectively. Priority of improvement and replacement of water pipe can be determined by results of reliability analysis and management index analysis.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.11
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• pp.319-328
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• 2023

Unlike cloud computing, edge computing technology analyzes and judges data close to devices and users, providing advantages such as real-time service, sensitive data protection, and reduced network traffic. EdgeX Foundry, a representative open source of edge computing platforms, is an open source-based edge middleware platform that provides services between various devices and IT systems in the real world. EdgeX Foundry provides a service for handling camera devices, along with a service for handling existing sensed data, which only supports simple streaming and camera device management and does not store or process image data obtained from the device inside EdgeX. This paper presents a technique that can store and process image data inside EdgeX by applying some of the services provided by EdgeX Foundry. Based on the proposed technique, a service pipeline for object detection services used core in the field of autonomous driving was created for experiments and performance evaluation, and then compared and analyzed with existing methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.5
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• pp.1059-1071
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• 2024

The 5G mobile network provides various services to numerous devices and applications, unlike LTE which focuses on smartphones. Features of 5G, such as low latency and massive connectivity, increase the overhead of the control plane(CP, signaling part) and make it difficult to detect abnormal devices due to random traffic patterns. In this paper, we propose a DBSCAN clustering-based detection method to counter signaling attacks, which are a type of 'Denial of Service(DoS)' attack targeting mobile networks. DBSCAN helps to create clusters of various shapes and can address dynamic traffic because the algorithm needs not to depend on past traffic statistics. We also use a real-time traced dataset for experiments to assess usability in real-world scenarios. According to the experiments, our method achieves 99.32% of accuracy and 0.03% of false-positive rates, demonstrating superior performance compared to previous works.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2347-2352
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• 2011

driver for safety always check the status of their vehicle, and it is essential to understand. But if you want to know the status of the driver of the vehicle in specialist referral time and money because it costs the operator shall be paid.IT technoligy with the development of the various features of your phone to check the status of the vehicle was able to do. However, the car' existing phone system, car diagnostic expertise must be learned because it will reveal the status of the vehicle do not have the expertise to not highlight the need for diagnostic. To reflect these points in smartphone users to easily use their own vehicles at a time to determine the status of a system that is required. In this paper, OBD-II protocol conversion WiFi OBD-II connector, retrieving information from the driver of the vehicle replacement cycle of consumables required vehicle inspection, vehicle problems in real-time diagnostic information to the user ease of use shows the iPhone implementation in the automotive supply was implemented based on the smartphone.