• Title/Summary/Keyword: fingerprinting

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Audio Fingerprint Binarization by Minimizing Hinge-Loss Function (경첩 손실 함수 최소화를 통한 오디오 핑거프린트 이진화)

  • Seo, Jin Soo
    • The Journal of the Acoustical Society of Korea
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    • v.32 no.5
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    • pp.415-422
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    • 2013
  • This paper proposes a robust binary audio fingerprinting method by minimizing hinge-loss function. In the proposed method, the type of fingerprints is binary, which is conducive in reducing the size of fingerprint DB. In general, the binarization of features for fingerprinting deteriorates the performance of fingerprinting system, such as robustness and discriminability. Thus it is necessary to minimize such performance loss. Since the similarity between two audio clips is represented by a hinge-like function, we propose a method to derive a binary fingerprinting by minimizing a hinge-loss function. The derived hinge-loss function is minimized by using the minimal loss hashing. Experiments over thousands of songs demonstrate that the identification performance of binary fingerprinting can be improved by minimizing the proposed hinge loss function.

An Innovative Fingerprinting Procedure for Human Identification

  • Kim, Young-Sam;Yoon, Kwang-Sang;Eom, Yong-Bin;Seo, Joong-Seok;Kim, Jong-Bae
    • Biomedical Science Letters
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    • v.15 no.3
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    • pp.187-197
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    • 2009
  • Fingerprinting is a frontier technique that is the most frequently applied for human identification throughout the world. All citizens over 17 year old living in the Republic of Korea must be fingerprinted to obtain a certificate of resident registration. In Korea, for this reason, human identification through fingerprints has been far better developed and used efficiently both in crime scene investigation and in confirmation of an unidentified body. Scientific approaches have been made to accurately extract the metamorphosed fingerprints in various environments. Because most of the studies on fingerprinting have been accomplished with biometric techniques, researches on restoration of human dermal tissue and taking custody data after collecting fingerprints have been comparatively undermined. In this study, a newly innovative method for fingerprint extraction was developed using the polyester film with print powders and the high temperature-moisturizing method. Compared to the conventional fingerprinting method of paper with ink, minutiae numbers of fingerprints were greatly increased in polyester film with print powders after restoration of fingertips by high temperature-moisturization. This newly developed procedure would be an efficient fingerprinting technique which could be utilized in scientific investigation and in personal identification in the future. Furthermore, the new method for restoration and extraction of fingerprints are easy and inexpensive to practice for a number of human identification.

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Enhanced Discrimination of Listeria spp. Using RAPD Fingerprinting Complemented by Ribotyping-PCR (리스테리아균의 특성분석을 위한 Molecular Typing 방법의 상호보완)

  • 임형근;홍종해;박경진;최원상
    • Journal of Life Science
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    • v.13 no.5
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    • pp.699-704
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    • 2003
  • The results typed by random amplification of polymorphic DNA (RAPD) were compared with those obtained by Enterobacterial repititive intergenic consensus (ERIC) fingerprinting and ribotyping-PCR. The discriminatory power of RAPD typing was the best among the methods tested. RAPD typing with two different primers for 13 Listeria spp. reference strains produced 11 patterns each. In contrast, ERIC fingerprinting produced 9 patterns and ribotyping-PCR produced 7 patterns each. Composite of two separate RAPD (Lis 11 and primer 6) results or RAPD (Lis11)/ ribotyping-PCR differentiated all 13 Listeria spp. reference strains. Therefore, composite of 2 separate RAPD (Lis11 and primer 6) or composite of RAPD (Lis11)/ribotyping-PCR is expected the most promising approach for typing field isolated Listeria spp. strains.

Amplified Fragment Length Polymorphism Fingerprinting as a Tool to Study the Genetic Diversity of Staphylococcus aureus Isolated from Food Sources

  • Kim, Young-Sam;Kim, Jong-Bae
    • Biomedical Science Letters
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    • v.8 no.1
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    • pp.39-46
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    • 2002
  • Amplified fragment length polymorphism (AFLP) is a recently developed PCR-based high resolution fingerprinting method that is able to generate complex banding patterns which can be used to delineate intraspecific genetic relationships among bacteria. In this study, we have modified and evaluated a PCR-based technique, amplified fragment length polymorphism (AFLP) analysis, for use in fingerprinting strains of Staphylococcus aureus. Single-enzyme amplified fragment length polymorphism (SE-AFLP) analysis was used to perform strain identification of Staphylococus aureus. By careful selection of AFLP primers, it was possible to obtain reproducible and sensitive identification to strain level. AFLP fingerprinting of 5 reference strains of Staphylococcus aureus and 65 strains of Staphylococcus aureus that were isolated from food sources of different area and diverse genomic types of Staphylococcus aureus were recognized. As a result of this study, we found that the AFLP patterns of Staphylococcus aureus isolated from Seoul, Taejeon and Gwang-Ju indicated the close relation with genetic similarity. The main purpose of this study was to find an alternative and reliable fingerprinting method to study the overall genetic diversity, using Staphylococcus aureus species as an example, and observed if the method can be successfully applied to all staphylococcal species.

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KNN/PFCM Hybrid Algorithm for Indoor Location Determination in WLAN (WLAN 실내 측위 결정을 위한 KNN/PFCM Hybrid 알고리즘)

  • Lee, Jang-Jae;Jung, Min-A;Lee, Seong-Ro
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.47 no.6
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    • pp.146-153
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    • 2010
  • For the indoor location, wireless fingerprinting is most favorable because fingerprinting is most accurate among the technique for wireless network based indoor location which does not require any special equipments dedicated for positioning. As fingerprinting method,k-nearest neighbor(KNN) has been widely applied for indoor location in wireless location area networks(WLAN), but its performance is sensitive to number of neighborsk and positions of reference points(RPs). So possibilistic fuzzy c-means(PFCM) clustering algorithm is applied to improve KNN, which is the KNN/PFCM hybrid algorithm presented in this paper. In the proposed algorithm, through KNN,k RPs are firstly chosen as the data samples of PFCM based on signal to noise ratio(SNR). Then, thek RPs are classified into different clusters through PFCM based on SNR. Experimental results indicate that the proposed KNN/PFCM hybrid algorithm generally outperforms KNN and KNN/FCM algorithm when the locations error is less than 2m.

Performance Analysis of Fingerprinting algorithms for Indoor Positioning (옥내 측위를 위한 지문 방식 알고리즘들의 성능 분석)

  • Yim, Jae-Geol
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.43 no.6 s.312
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    • pp.1-9
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    • 2006
  • For the indoor positioning, wireless fingerprinting is most favorable because fingerprinting is most accurate among the techniques for wireless network based indoor positioning which does not require any special equipments dedicated for positioning. The deployment of a fingerprinting method consists of off-line phase and on-line phase. Off-line phase is not a time critical procedure, but on-line phase is indeed a time-critical procedure. If it is too slow then the user's location can be changed while it is calculating and the positioning method would never be accurate. Even so there is no research of improving efficiency of on-line phase of wireless fingerprinting. This paper proposes a decision-tree method for wireless fingerprinting and performs comparative analysis of the fingerprinting techniques including K-NN, Bayesian and our decision-tree.

Fraud Click Identification Using Fingerprinting Method (핑거프린팅 기법을 이용한 부정 클릭의 식별)

  • Hong, Young-Ran;Kim, Dong-Soo
    • The Journal of Society for e-Business Studies
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    • v.16 no.3
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    • pp.159-168
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    • 2011
  • To identify fraud clicks in the Internet advertisement, existing studies have considered keyword, visit time, and client IP as an independent variable for the standard. These methods have limitations in identifying the fraud clicks that utilize automation tools, for they are methods based on client IP and human activities on the Internet. This paper proposes that fingerprinting values of the variable combination should be used to identify fraud clicks. The proposed model is composed of 3 stages and the fingerprinting values are compared with the other input data at each stage; IP fingerprinting in the first stage, IP and session data fingerprinting in the second stage, and session data and keyword fingerprinting in the third stage. We showed that the proposed model of the fraud click identification is more correct than existing methods through experiments according to the proposed scheme.

Application of Wavelet-Based RF Fingerprinting to Enhance Wireless Network Security

  • Klein, Randall W.;Temple, Michael A.;Mendenhall, Michael J.
    • Journal of Communications and Networks
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    • v.11 no.6
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    • pp.544-555
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    • 2009
  • This work continues a trend of developments aimed at exploiting the physical layer of the open systems interconnection (OSI) model to enhance wireless network security. The goal is to augment activity occurring across other OSI layers and provide improved safeguards against unauthorized access. Relative to intrusion detection and anti-spoofing, this paper provides details for a proof-of-concept investigation involving "air monitor" applications where physical equipment constraints are not overly restrictive. In this case, RF fingerprinting is emerging as a viable security measure for providing device-specific identification (manufacturer, model, and/or serial number). RF fingerprint features can be extracted from various regions of collected bursts, the detection of which has been extensively researched. Given reliable burst detection, the near-term challenge is to find robust fingerprint features to improve device distinguishability. This is addressed here using wavelet domain (WD) RF fingerprinting based on dual-tree complex wavelet transform (DT-$\mathbb{C}WT$) features extracted from the non-transient preamble response of OFDM-based 802.11a signals. Intra-manufacturer classification performance is evaluated using four like-model Cisco devices with dissimilar serial numbers. WD fingerprinting effectiveness is demonstrated using Fisher-based multiple discriminant analysis (MDA) with maximum likelihood (ML) classification. The effects of varying channel SNR, burst detection error and dissimilar SNRs for MDA/ML training and classification are considered. Relative to time domain (TD) RF fingerprinting, WD fingerprinting with DT-$\mathbb{C}WT$ features emerged as the superior alternative for all scenarios at SNRs below 20 dB while achieving performance gains of up to 8 dB at 80% classification accuracy.

Anonymous Fingerprinting Method using the Secret Sharing Scheme (비밀분산법을 이용한 익명성 보장 핑거프린팅 기법)

  • 용승림;이상호
    • Journal of KIISE:Computer Systems and Theory
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    • v.31 no.5_6
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    • pp.353-359
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    • 2004
  • The illegal copying and redistribution of digitally-stored information is a crucial problem to distributors who electronically sell digital data. Fingerprinting scheme is a techniques which supports copyright protection to track redistributors of electronic information using cryptographic techniques. Anonymous fingerprinting schemes, differ from symmetric fingerprinting, prevent the merchant from framing a buyer by making the fingerprinted version known to the buyer only. And the scheme, differ from asymmetric fingerprinting, allows the buyer to purchase goods without revealing her identity to the merchant. In this paper, a new anonymous fingerprinting scheme based on secret sharing is introduced. The merchant finds a sold version that has been distributed, and then he is able to retrieve a buyer's identity and take her to court. And Schnorr's digital signature prevents the buyer from denying the fact he redistributed. The buyer's anonymity relies on the security of discrete logarithm and secure two-party computations.

Differentiation of Four Major Gram-negative Foodborne Pathogenic Bacterial Genera by Using ERIC-PCR Genomic Fingerprinting (ERIC-PCR genomic fingerprinting에 의한 주요 식중독 그람 음성 세균 4속의 구별)

  • Jung, Hye-Jin;Park, Sung-Hee;Seo, Hyeon-A;Kim, Young-Joon;Cho, Joon-Il;Park, Sung-Soo;Song, Dae-Sik;Kim, Keun-Sung
    • Korean Journal of Food Science and Technology
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    • v.37 no.6
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    • pp.1005-1011
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    • 2005
  • Widespread distributions of repetitive DNA elements in bacteria genomes are useful for analysis of genomes and should be exploited to differentiate food-borne pathogenic bacteria among and within species. Enterobacterial repetitive intergenic consensus (ERIC) sequence has been used for ERIC-PCR genomic fingerprinting to identify and differentiate bacterial strains from various environmental sources. ERIC-PCH genomic fingerprinting was applied to detect and differentiate four major Gram-negative food-borne bacterial pathogens, Esherichia coli, Salmonella, Shigella, and Vibrio. Target DNA fragments of pathogens were amplified by ERIC-PCR reactions. Dendrograms of subsequent PCR fingerprinting patterns for each strain were constructed, through which relative similarity coefficients or genetic distances between different strains were obtained numerically. Numerical comparisons revealed ERIC-PCR genotyping is effective for differentiation of strains among and within species of food-borne bacterial pathogens, showing ERIC-PCR fingerprinting methods can be utilized to differentiate isolates from outbreak and to determine their clonal relationships among outbreaks.