• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8C
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• pp.731-740
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• 2012

To offer indoor location-aware services, the needs for efficient and accurate indoor localization system has been increased. In order to meet these requirement, we presented the BLIDx(Bidirectional Location ID exchange) protocol that is efficient localization system based on sensor network. The BLIDx protocol can cope with numerous mobile nodes simultaneously but the precision of the localization is too coarse because that uses cell based localization method. In this paper, in order to compensate for these disadvantage, we propose the fingerprint overlapping method by modifying a fingerprinting methods in WLAN, and localization system using proposed method was designed and implemented. Our experiments show that the proposed method is more accurate and robust to noise than fingerprinting method in WLAN. In this way, it was improved that low location precision of BLIDx protocol.

• Mycobiology
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• v.36 no.3
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• pp.161-166
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• 2008

The retrotransposon marY1 is a gypsy family retroelement, which is detected ubiquitously within the fungal taxonomic groups in which mushrooms are included. To utilize marY1 as a molecular marker for the DNA fingerprinting of mushrooms, oligonucleotides marY1-LTR-L and marY1-LTR-R were designed on the basis of highly conserved regions from the multiple sequence alignment of 30 marY1 sequences retrieved from a nucleotide sequence database. In accordance with $\underline{Re}trotransposon$ $\underline{M}icrosatellite$ $\underline{A}mplified$ $\underline{P}olymorphism$ (REMAP) fingerprinting methodology, the two oligonucleotides were utilized together with the short sequence repeat primers UBC807 and UBC818 for polymerase chain reaction using templates from different mushroom genomic DNAs. Among the tested oligonucleotides, the marY1-LTR-L and UBC807 primer set yielded the greatest amount of abundance and variation in terms of DNA band numbers and patterns. This method was successfully applied to 10 mushroom species, and the primer set successfully discriminated between different commercial mushroom cultivars of the same strains of 14 Pleurotus ostreatus and 16 P. eryngii. REMAP reproducibility was superior to other popular DNA fingerprinting methodologies including the random amplified polymorphic DNA method.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.6
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• pp.187-194
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• 2020

This paper proposes a website fingerprinting method using ensemble learning over a Tor network that guarantees client anonymity and personal information. We construct a training problem for website fingerprinting from the traffic packets collected in the Tor network, and compare the performance of the website fingerprinting system using tree-based ensemble models. A training feature vector is prepared from the general information, burst, cell sequence length, and cell order that are extracted from the traffic sequence, and the features of each website are represented with a fixed length. For experimental evaluation, we define four learning problems (Wang14, BW, CW_T, CW_H) according to the use of website fingerprinting, and compare the performance with the support vector machine model using CUMUL feature vectors. In the experimental evaluation, the proposed statistical-based training feature representation is superior to the CUMUL feature representation except for the BW case.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.99-109
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• 2004

This paper proposes a new method for tracking image contents, which are re-distributed on the Internet using a web-robot and fingerprinting scheme. The fingerprinting is an extended technique of watermarking and embeds identity of the customer into the content as a fingerprint in a way that is very difficult to erase. The fingerprint in the content can be used widely in the field of the copyright protection technique because it identifies the content itself and includes the information about the original customer. In this paper we discuss an active image tracking system using a web-robot and fingerprinting scheme. In the proposed system the information of the original customer is embedded as a fingerprint into the image content before distribution and also stored into DB. The distributed contents are collected by the web-robot and fingerprinting information is extracted from the contents. Finally the identifying of contents is done by comparing the extracted fingerprint with the selling history of the content.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.3
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• pp.551-560
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• 2011

Recently, There has been increasing concern about WLAN-based indoor positioning system. Most of the existing WLAN-based positioning systems use a fingerprinting method as a main approach. In the fingerprinting approach, the accuracy of the location of a mobile objects is proportional to the number of reference points. However, depending on the increasing number of reference points in the training phase, it requires more time and effort to create fingerprint database. To solve these problems, we propose the new indoor positioning algorithm that calculate the distance between a mobile objects and an AP using the information of surrounding environment WLAN based APs and applied the particle filter to the proposed algorithm in order to improve the accuracy of the estimated location in this paper. To implement this algorithm, at first environmental information database such as wall, iron door, glass door, partition etc. existing in the periphery of the AP should be established. The positioning use attenuation model and path loss model. Our experimental results with proposed algorithm are verified that the positioning accuracy was low but solved the problems with fingerprinting, compared with other positioning algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5B
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• pp.443-450
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• 2011

The Internet has become an essential part in our modern life by providing useful information. So, the volume of Internet traffic has been increasing rapidly, which emphasizes the importance of network traffic analysis for effective network operation and management. Signature based analysis have been commonly used, but it is shown that the increase of signatures due to the increase of applications causes the performance degradation of real-time traffic analysis on high-speed network links. In this paper, we propose OS fingerprinting method for real-time traffic analysis. The previous problems can be solved by utilizing the OS information. The OS fingerprinting method for real-time traffic analysis, proposed in this paper, conducts under passive mode, and improves the limitation of a previous method such as low completeness and accuracy. In this paper, we enlarged an input data to improve completeness, and used the User-Agent field in HTTP packet to extract various OS signatures. Also, we changed an input data from packet to flow to improve accuracy.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.9
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• pp.369-376
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• 2017

Recently, an RSSI-based fingerprinting localization technology has been widely used in indoor location-based services. In the conventional fingerprinting method, as many APs as possible are used to increase the accuracy of location estimation. In another study, a part of APs having the strongest RSSI signal intensity are selected and used to reduce the time spent for positioning. However, it does not reflect the influence of RSSI occurred from the changes of the surrounding environments such as human movement or moving obstacles in a real environment. The environmental changes may cause the difference between the predicted RSSI signal strength value and the measured value, and thus occur an unpredictable error in the position estimation. Therefore, in order to mitigate the error caused by environmental factors, it is necessary to select APs suitable for indoor positioning estimation considering the changes in the surrounding environments. In this paper, we propose a method to select stable APs considering the influence of surrounding environments and derive a suitable positioning algorithm. In addition, we compare and analyze the performance of the proposed method with that of the existing AP selection methods through experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1881-1903
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• 2015

With the fast-developing of mobile terminals, positioning techniques based on fingerprinting method draws attention from many researchers even world famous companies. To conquer some shortcomings of the existing fingerprinting systems and further improve its performance, we propose a radio map building and updating technique, which is able to customize the spatial and temporal dependency of radio maps. The method includes indoor propagation and penetration modeling and the analysis of human traffic. Based on the combination of Ray-Tracing Algorithm, Finite-Different Time-Domain and Rough Set Theory, the approach of indoor propagation modeling accurately represents the spatial dependency of the radio map. In terms of temporal dependency, we specifically study the factor of moving people in the interest area. With measurement and statistics, the factor of human traffic is introduced as the temporal updating component. We improve our existing indoor positioning system with the proposed building and updating method, and compare the localization accuracy. The results show that the enhanced system can conquer the influence caused by moving people, and maintain the confidence probability stable during week, which enhance the actual availability and robustness of fingerprinting-based indoor positioning system.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.175-180
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• 2013

For the traitor tracing of multimedia content, this paper presents the classification algorithm of XOR collusion attack types using hamming distance, which applies to the colluded fingerprinting codes. The conventional traitor decision hinges on the colluded fingerprinting code used by a correlation coefficient, but the proposed scheme uses hamming distance. While XOR collusion attack employing a correlation coefficient is impossible to trace the traitors about 50% colluders due to a serious XOR linear problem, our method improves the performance of traceability to trace at least 1 traitor using hamming distance, and thus, the functional behavior of the proposed traitor traceability is coincided with Probability Scheme.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.4
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• pp.16-22
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• 2012

In this paper, the forensic marking algorithm is proposed using psychoacoustic model II and MDCT for high-quality audio. The proposed forensic marking method, that inserts the user fingerprinting code of the audio content into the selected sub-band, in which audio signal energy is lower than the spectrum masking level. In the range of the one frame which has 2,048 samples for FFT of original audio signal, the audio forensic marking is processed in 3 sub-bands. According to the average attack of the fingerprinting codes, one frame's SNR is measured on 100% trace ratio of the collusion codes. When the lower strength 0.1 of the inserted fingerprinting code, SNR is 38.44dB. And in case, the added strength 0.5 of white gaussian noise, SNR is 19.09dB. As a result, it confirms that the proposed audio forensic marking algorithm is maintained the marking robustness of the fingerprinting code and the audio high-quality.