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RISS 인기검색어
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- 저자 : Abdullah Al Rahat Kutubi (검색결과 3 건)
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An Offline Electronic Payment System Based on an Untraceable Blind Signature Scheme
( Md. Abdullah Al Rahat Kutubi ),( Kazi Md. Rokibul Alam ),( Rafaf Tahsin ),( G. G. Md Nawaz Ali ),( Peter Han Joo Chong ),( Yasuhiko Morimoto ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.5
This paper proposes a new offline electronic payment (e-payment) system that satisfies the major security requirements of e-payment, i.e. anonymity, unlinkability, unforgeability, double spending control, conditional traceability, and fraud prevention. The central idea is the use of Hwang et al.`s RSA-based untraceable blind signature (BS), which disables the link between the e-coin and its owner and ensures the anonymity of both the customer and the merchant. It attaches an expiration, a deposit and the transaction dates to each e-coin in order to manage the database of the bank effectively, to correctly calculate the interest on the e-coin and to aid arbitration if a dishonest customer attempts to double-spend the coin. It also ensures the anonymity of the customer as long as the coin is spent legitimately. Only when a fraudulent e-coin transaction is detected can the bank, with the help of the central authority (a trusted entity), determine the identity of the dishonest customer. The system is referred to as offline since the bank does not need to be concurrently involved in transactions between a customer and a merchant. Finally, analyses of the performance of the prototype and the primary security requirements of the proposed system are also presented.
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Abdullah Al Rahat Kutubi,홍민기,김천 대한원격탐사학회 2018 大韓遠隔探査學會誌 Vol.34 No.1
This paper compares the four selections of performance used in the application of genetic algorithms (GAs) to automatically optimize multispectral pixel cluster for unsupervised classification from KOMPSAT-3 data, since the selection among three main types of operators including crossover and mutation is the driving force to determine the overall operations in the clustering GAs. Experimental results demonstrate that the tournament selection obtains a better performance than the other selections, especially for both the number of generation and the convergence rate. However, it is computationally more expensive than the elitism selection with the slowest convergence rate in the comparison, which has less probability of getting optimum cluster centers than the other selections. Both the ranked-based selection and the proportional roulette wheel selection show similar performance in the average Euclidean distance using the pixel clustering, even the ranked-based is computationally much more expensive than the proportional roulette. With respect to finding global optimum, the tournament selection has higher potential to reach the global optimum prior to the ranked-based selection which spends a lot of computational time in fitness smoothing. The tournament selection-based clustering GA is used to successfully classify the KOMPSAT-3 multispectral data achieving the sufficient thematic accuracy assessment (namely, the achieved Kappa coefficient value of 0.923).
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Kutubi, Abdullah Al Rahat,Hong, Min-Gee,Kim, Choen The Korean Society of Remote Sensing 2018 大韓遠隔探査學會誌 Vol.34 No.1
This paper compares the four selections of performance used in the application of genetic algorithms (GAs) to automatically optimize multispectral pixel cluster for unsupervised classification from KOMPSAT-3 data, since the selection among three main types of operators including crossover and mutation is the driving force to determine the overall operations in the clustering GAs. Experimental results demonstrate that the tournament selection obtains a better performance than the other selections, especially for both the number of generation and the convergence rate. However, it is computationally more expensive than the elitism selection with the slowest convergence rate in the comparison, which has less probability of getting optimum cluster centers than the other selections. Both the ranked-based selection and the proportional roulette wheel selection show similar performance in the average Euclidean distance using the pixel clustering, even the ranked-based is computationally much more expensive than the proportional roulette. With respect to finding global optimum, the tournament selection has higher potential to reach the global optimum prior to the ranked-based selection which spends a lot of computational time in fitness smoothing. The tournament selection-based clustering GA is used to successfully classify the KOMPSAT-3 multispectral data achieving the sufficient the matic accuracy assessment (namely, the achieved Kappa coefficient value of 0.923).
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