• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.44 no.6
• /
• pp.16-23
• /
• 2007

Changeable biometrics has been developed as a solution to problem of enhancing security and privacy. The idea is to transform a biometric signal or feature into a new one for the purposes of enrollment and matching. In this paper, we propose a changeable biometric system that can be applied to appearance based face recognition system. In the first step when using feature extraction, ICA(Independent Component Analysis) coefficient vectors extracted from an input face image are replaced randomly using their mean and variation. The transformed vectors by replacement are scrambled randomly and a new transformed face coefficient vector (transformed template) is generated by combination of the two transformed vectors. When this transformed template is compromised, it is replaced with new random numbers and a new scrambling rule. Because e transformed template is generated by e addition of two vectors, e original ICA coefficients could not be easily recovered from the transformed coefficients.

• IE interfaces
• /
• v.23 no.4
• /
• pp.311-318
• /
• 2010

In the daily multi-reservoir operating problem, monthly storage targets can be used as principal operational guidelines. In this study, we tested the use of a simple back-propagation Artificial Neural Network (ANN) model to derive monthly storage guideline for daily Coordinated Multi-reservoir Operating Model (CoMOM) of the Han-River basin. This approach is based on the belief that the optimum solution of the daily CoMOM has a good performance, and the ANN model trained with the results of daily CoMOM would produce effective monthly operating guidelines. The optimum results of daily CoMOM is used as the training set for the back-propagation ANN model, which is designed to derive monthly reservoir storage targets in the basin. For the input patterns of the ANN model, we adopted the ratios of initial storage of each dam to the storage of Paldang dam, ratios of monthly expected inflow of each dam to the total inflow of the whole basin, ratios of monthly demand at each dam to the total demand of the whole basin, ratio of total storage of the whole basin to the active storage of Paldang dam, and the ratio of total inflow of the whole basin to the active storage of the whole basin. And the output pattern of ANN model is the optimal final storages that are generated by the daily CoMOM. Then, we analyzed the performance of the ANN model by using a real-time simulation procedure for the multi-reservoir system of the Han-river basin, assuming that historical inflows from October 1st, 2004 to June 30th, 2007 (except July, August, September) were occurred. The simulation results showed that by utilizing the monthly storage target provided by the ANN model, we could reduce the spillages, increase hydropower generation, and secure more water at the end of the planning horizon compared to the historical records.

• The KIPS Transactions:PartA
• /
• v.14A no.1 s.105
• /
• pp.1-14
• /
• 2007

MPICH-G2 is an MPI implementation to solve complex computational problems by utilizing geographically dispersed computing resources in grid environments. However, the computation nodes in MPICH-G2 are exposed to the external network due to the lack of supporting the private IP clusters, which raises the possibility of malicious security attacks. In order to address this problem, we propose MPICH-GP with a new relay scheme combining NAT(Network Address Translation) service and an user-level proxy. The proxy running on the front-end system of private IP clusters forwards the incoming connection requests to the systems inside the clusters. The outgoing connection requests out of the cluster are forwarded through the NAT service on the front-end system. Through the connection path between the pair of processes, the requested MPI jobs can be successfully executed in grid environments with various clusters including private IP clusters. By simulations, we show that the performance of MPICH-GP reaches over 80% of the performance of MPICH-G2, and over 95% in ease of using RANK management method.

• The KIPS Transactions:PartC
• /
• v.16C no.1
• /
• pp.21-26
• /
• 2009

Presently, the demand for IPTV, to satisfy a variety of goals, is exploding. IPTV is coming into the spotlight as a killer application in upcoming IP convergence networks such as triple play which is the delivery of voice, internet, and video service to a subscriber. IPTV utilizes CAS, which controls the subscriber access to content for a profit. Although the current CAS scheme provides access control via subscriber authentication, there is no authentication scheme for the content transmitted from service providers. Thus, there is a vulnerability of security, through which an adversary can forge content between the service provider and subscribers and distribute malicious content to subscribers. In this paper, based on a hash tree scheme, we proposed efficient and strong source authentication protocols which remove the vulnerability of the current IPTV system. We also evaluate our protocol from a view of IPTV requirements.

• Journal of Digital Convergence
• /
• v.18 no.7
• /
• pp.223-228
• /
• 2020

The stock price reflects people's psychology, and factors affecting the entire stock market include economic growth rate, economic rate, interest rate, trade balance, exchange rate, and currency. The domestic stock market is heavily influenced by the stock index of the United States and neighboring countries on the previous day, and the representative stock indexes are the Dow index, NASDAQ, and S & P500. Recently, research on stock price analysis using stock news has been actively conducted, and research is underway to predict the future based on past time series data through artificial intelligence-based analysis. However, even if the stock market is hit for a short period of time by the forecasting system, the market will no longer move according to the short-term strategy, and it will have to change anew. Therefore, this model monitored Samsung Electronics' stock data and news information through text mining, and presented a predictable model by showing the analyzed results.

• Journal of Satellite, Information and Communications
• /
• v.8 no.2
• /
• pp.94-98
• /
• 2013

A report of security problems and simultaneous operation limits of Standard tone currently used for FTS introduces the development of a next generation FTS. In this paper, BER performance by modulations and channel coding methods for EFTS are compared. Simulation results show that coherent modulations have better BER performance than noncoherent modulations. However the environments of a lunching vehicle may cause serious problems in achieving and maintaining synchronization and the increasing complexity of coherent systems also increases reliability problems. Therefore noncoherent systems are suitable for FTS even though BER performace of noncoherent systems is lower than coherent systems. Noncoherent DPSK has better BER performance than noncoherent CPFSK. However the PEP of noncoherent DPSK is 0.8dB higher than noncoherent CPFSK. Therefore a transmitter of noncoherent DPSK has more output power than noncoherent CPFSK. Convoltional code has better BER performance than RS code. However RS code has a tendency of steeply decreasing BER near the wanted $E_b/N_0$.

• Korean Journal of Occupational Health Nursing
• /
• v.28 no.4
• /
• pp.208-220
• /
• 2019

Purpose: This study aimed to determine health problems experienced by workers in special employment relationships (WSER) and identify coping strategies used when such problems occur. Methods: This qualitative study used the focus group interview method. Thirteen study participants included five home-visit tutors, five insurance salespersons, and three credit card recruiters. The interviews were conducted from November 2018 through January 2019, with each occupational group interview lasting about 2 hours. Analysis based on phenomenological research was independently performed by two researchers. Results: Most participants had common health problems involving vocal cord symptoms, and stress related to emotional labor and traffic accidents. The unique health problems included cystitis, musculoskeletal, and digestive symptoms in home-visit tutors; reduced vision and hearing in insurance salespersons; and mental distress in credit card recruiters. There was no protection system for their health coverage, and the company emphasized their self-employed status to avoid taking responsibility for them. Twelve participants did not purchase occupational accident insurance owing to both not having adequate information and economic burden concerning premium status. Conclusion: WSER experienced both physical and mental health problems. These problems were caused by their unstable employment status, and the social security system for their coverage being non-functioning.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.43 no.4
• /
• pp.190-197
• /
• 2020

Recently there was an incident that military radars, coastal CCTVs and other surveillance equipment captured a small rubber boat smuggling a group of illegal immigrants into South Korea, but guards on duty failed to notice it until after they reached the shore and fled. After that, the detection of such vessels before it reach to the Korean shore has emerged as an important issue to be solved. In the fields of marine navigation, Automatic Identification System (AIS) is widely equipped in vessels, and the vessels incessantly transmits its position information. In this paper, we propose a method of automatically identifying abnormally behaving vessels with AIS using convolutional autoencoder (CAE). Vessel anomaly detection can be referred to as the process of detecting its trajectory that significantly deviated from the majority of the trajectories. In this method, the normal vessel trajectory is gridded as an image, and CAE are trained with images from historical normal vessel trajectories to reconstruct the input image. Features of normal trajectories are captured into weights in CAE. As a result, images of the trajectories of abnormal behaving vessels are poorly reconstructed and end up with large reconstruction errors. We show how correctly the model detects simulated abnormal trajectories shifted a few pixel from normal trajectories. Since the proposed model identifies abnormally behaving ships using actual AIS data, it is expected to contribute to the strengthening of security level when it is applied to various maritime surveillance systems.

• Journal of Internet of Things and Convergence
• /
• v.8 no.1
• /
• pp.65-72
• /
• 2022

The Internet of Things (IoT) provides data convergence and sharing functions, and IoT technology is the most fundamental core technology in creating new services by convergence of various cutting-edge technologies. However, there are different classification systems for the Internet of Things, and when it is limited to the domestic public sector, it is difficult to properly grasp the current status of which devices are installed and operated with what share, and systematic data or research The results are very difficult to find. Therefore, in this study, the relevance of the classification system for IoT devices was analyzed according to reality based on sales, shipments, and growth rate, and based on this, the actual share of IoT devices among domestic public institutions was analyzed in detail. The derived detailed analysis results are expected to be efficiently utilized in the process of selecting IoT devices for research and analysis to advance information protection technology such as responding to malicious code attacks on IoT devices, analyzing incidents, and strengthening security vulnerabilities.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.19 no.1
• /
• pp.165-172
• /
• 2024

In this paper, we designed a smart home system that can be used intuitively and easily in everyday life, such as sending text messages to users, providing various information and scheduling using smart AI, and providing lighting and atmosphere suitable for the atmosphere in situations such as listening to music using neopixels, as well as using ESP32, RFID, and Google Cloude Console using raspberry pie. As a result of the experiment, it was confirmed that security characters were normally sent to users when RFID was recognized on ESP32 connected to Wi-Fi even if the power was reconnected, and smart AI using Neopixel lighting, Raspberry Pie, and voice recognition, which calculated frequency, also changed the recognition rate over distance, but it worked.