• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38A no.8
• /
• pp.638-643
• /
• 2013

Chaos communication system has a sensitive characteristic to initial conditions, because completely another signal is generated when initial condition of chaos equation is changed subtly. Also, chaos communication systems have the characteristics of non-periodic, non-predictability, the broadband signal, such as ease of implementation. Due to these characteristics, security of chaos communication system generally is evaluated better than other systems. However, BER(Bit Error Rate) performance is evaluated worse than other digital system, because existing chaos communication system's transmitter and receiver are strong influence by interference signal and noise. So, research to improve the BER performance of the chaotic communication system is performed continuously. In this paper, We will propose a new CDSK(Correlation Delay Shift Keying) receiver for BER performance improvement. After we compare to the performance of existing CDSK receiver and proposed CDSK receiver, BER performance of proposed CDSK receiver evaluate. Also, when using the new CDSK receiver, we evaluate the BER performance according to the spreading factors and find an optimum spreading factor. If chaos communication system use a new CDSK receiver, BER performance is improved than existing CDSK receiver. Also, if spreading factor's value is increased, BER performance is improved, because it is not nearly affected by interference signal and noise.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.10
• /
• pp.4923-4939
• /
• 2019

In this paper, a secure transmission scheme based on the artificial noise is proposed for D2D communications underlaying the full-duplex cellular network, and a secure power allocation scheme to maximize the overall secrecy rate of both the cellular user and D2D transmitter node is presented. Firstly, the full-duplex base station transmits the artificial noise to guarantee the secure communications when it receives signals of cellular uplinks. Under this secure framework, it is found that improving the transmission power of the cellular user or the D2D transmitter node will degrade the secrecy rate of the other, although will improve itself secrecy rate obviously. Hence, a secure power allocation scheme to maximize the overall secrecy rate is presented subject to the security requirement of the cellular user. However, the original power optimization problem is non-convex. To efficiently solve it, we recast the original problem into a convex program problem by utilizing the proper relaxation and the successive convex approximation algorithm. Simulation results evaluate the effectiveness of the proposed scheme.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.1C
• /
• pp.86-93
• /
• 2007

In this paper, we present an electronic voting system based on cryptographic techniques. Recently, some countries have used e-voting systems using an electronic voting device instead of a voting sheet. These e-voting systems are the early stage which is not online voting. Many cryptographers have studied on-line e-voting systems based on cryptographic techniques. The existing 1-out-of-L e-voting systems are based on E1Gamal cryptosystem. To reduce computational complexity, we use r-th residue encryption scheme and compare the computational complexity of our 1-out-of-L e-voting system with that of the 1-out-of-L e-voting system based on E1Gamal cryptosystem. Moreover, we extend the proposed 1-out-of-L e-voting system to ballot-cancellation property The existing e-voting systems had been overlooked the ballot-cancellation property. There is the reason that the ballot is cancelled according to an election law. For our e-voting system with ballot-cancellation property, we extend the homomorphic property based on r-th residue encryption. The extended homomorphic property is used to cancel votes with guaranteeing privacy and universal verifiability.

• Journal of the Society of Disaster Information
• /
• v.9 no.3
• /
• pp.358-364
• /
• 2013

Conventional disaster resources management systems among the several institutes are not mutually connected. In case of NDMS(National Disaster Management System), the data of the system is confined to the resources of the local governments and not connected with any other disaster resource management systems. Therefore, it is difficult to find the needed resources, when the large scale disaster is occurred. In this paper, we developed the integrated model of the distributed resources management framework considering the current resource management environment among the institutes. It is loosely coupling model under the centralized system, called IDRM(Integrated Disaster Resource Manager). The system will be verified with the test sites including Korea Expressway Corporation, JeonBuk local government, and Korea Construction Equipment Association. Via the field testing, the system will be the base of the real available system in the future.

• KIPS Transactions on Computer and Communication Systems
• /
• v.7 no.10
• /
• pp.251-258
• /
• 2018

Ransomware, a malicious software that requires a ransom by encrypting a file, is becoming more threatening with its rapid propagation and intelligence. Rapid detection and risk analysis are required, but real-time analysis and reporting are lacking. In this paper, we propose a ransomware infection detection system using social big data mining technology to enable real-time analysis. The system analyzes the twitter stream in real time and crawls tweets with keywords related to ransomware. It also extracts keywords related to ransomware by crawling the news server through the news feed parser and extracts news or statistical data on the servers of the security company or search engine. The collected data is analyzed by data mining algorithms. By comparing the number of related tweets, google trends (statistical information), and articles related wannacry and locky ransomware infection spreading in 2017, we show that our system has the possibility of ransomware infection detection using tweets. Moreover, the performance of proposed system is shown through entropy and chi-square analysis.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.1
• /
• pp.124-130
• /
• 2007

RFID technology is considered as a promising solution to increase efficiency of port logistics. Especially active RFID technology, such as e-Seal for container security, is receiving attention nowadays. If active RFID system is combined with passive RFID and legacy bar-code system overall efficiency of port logistics can be improved However, due to the device dependent control interface of RFID readers, there are many difficulties in making active-passive combined RFID system environment. In this paper, we introduce Smart Reader Interface (SRI) system, which provides a device independent RFID reader interrace to control different kinds of RFID readers by hiding device dependent control interface through adapter architecture which is similar to device driver of conventional operating systems. The key design objectives of SRI are the followings; conformance to the related standard. efficiency in processing, easy addition of an adapter for a new RFID reader. Actually, the implemented SRI system can support various kinds of commercial RFID readers, and through the test carried out not only in laboratory but also in the container terminal in the GwangYang Port, its practicality is verified.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.1
• /
• pp.50-55
• /
• 2021

Multi-path system is a system in which utilizes various networks simultaneously. It is expected that multi-path system can enhance communication speed, reliability, security of network. In this paper, we focus on path selection in multi-path system. To select optimal path, we propose deep reinforcement learning algorithm which is rewarded by the round-trip-time (RTT) of each networks. Unlike multi-armed bandit model, deep Q learning is applied to consider rapidly changing situations. Due to the delay of RTT data, we also suggest compensation algorithm of the delayed reward. Moreover, we implement testbed learning server to evaluate the performance of proposed algorithm. The learning server contains distributed database and tensorflow module to efficiently operate deep learning algorithm. By means of simulation, we showed that the proposed algorithm has better performance than lowest RTT about 20%.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.10
• /
• pp.1298-1304
• /
• 2019

Since the 9·11 terror attack in 2001, the Maritime Logistics Security System has been strengthened and required X-ray image for every imported cargos from manufacturing countries to United States. For scanning cargos, the container inspection systems use high energy X-rays for examination of contents of a container to check the nuclear, explosive, dangerous and illegal materials. Nowadays, the X-ray cargo scanners are established and used by global technologies for inspection of suspected cargos in the customs agency but these technologies have not been localized and developed sufficiently. In this paper, we propose the X-ray array detector system which is a core component of the container scanning system. For implementation of X-ray array detector, the analog and digital signal processing units are fabricated with integrated hardware, FPGA logics and GUI software for real-time X-ray images. The implemented system is superior in terms of resolution and power consumption compared to the existing products currently used in ports.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• 2006.11a
• /
• pp.167-172
• /
• 2006

It follows recently in an order augmentation of overseas construction market plant field and the project of oil gas field is increasing. Consequently, the hazard which secures the competitive power of the overseas plant enterprise of the domestic building industry enterprises the technical competitiveness security which stands, productivity improvement and strategy management propulsion back positive disposal plan establishment are demanded. Even from in that oil gas field of overseas plant enterprise for an industrial competitive power improvement the application of EPC circulation information which relates with a project accomplishment is more demanded, the EPC phased star efficiently it manages the circulation information contents which occurs from the business which is various it is not presented it cannot there is a contents classification system for. If with him about lower the draft the problem point of information omission back of occurrence and business subject for of the fringe land and duplication business occurs, about lower the productivity decrease actual condition is appearing with such problem point. The research which it sees consequently in order to improve the use characteristic of the augmentation of practical application of the contents management system of oil gas field and building industry information civil official establishhes the contents management system the BPM for (Business Process Management) to present the contents classification system of base, it does to sleep. The part of Business Process materiality the knowledge which is demanded, contents information and system anger it analyzes system anger of industrial equipment circulation information it takes a triangular position and to sleep it does.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_2
• /
• pp.1623-1631
• /
• 2022

Since oil spills can be a significant threat to the marine ecosystem, it is necessary to obtain information on the current contamination status quickly to minimize the damage. Satellite-based detection of marine oil spills has the advantage of spatiotemporal coverage because it can monitor a wide area compared to aircraft. Due to the recent development of computer vision and deep learning, marine oil spill detection can also be facilitated by deep learning. Unlike the existing studies based on Synthetic Aperture Radar (SAR) images, we conducted a deep learning modeling using PlanetScope optical satellite images. The blind test of the DeepLabV3+ model for oil spill detection showed the performance statistics with an accuracy of 0.885, a precision of 0.888, a recall of 0.886, an F1-score of 0.883, and a Mean Intersection over Union (mIOU) of 0.793.