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Journal articles on the topic 'User fingerprint'

Author: Grafiati
Published: 28 June 2021
Last updated: 10 February 2022

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1

Sharma, Uttam, Pradeep Tomar, Syed Sadaf Ali, Neetesh Saxena, and Robin Singh Bhadoria. "Optimized Authentication System with High Security and Privacy." Electronics 10, no. 4 (February 13, 2021): 458. http://dx.doi.org/10.3390/electronics10040458.

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Authentication and privacy play an important role in the present electronic world. Biometrics and especially fingerprint-based authentication are extremely useful for unlocking doors, mobile phones, etc. Fingerprint biometrics usually store the attributes of the minutia point of a fingerprint directly in the database as a user template. Existing research works have shown that from such insecure user templates, original fingerprints can be constructed. If the database gets compromised, the attacker may construct the fingerprint of a user, which is a serious security and privacy issue. Security of original fingerprints is therefore extremely important. Ali et al. have designed a system for secure fingerprint biometrics; however, their technique has various limitations and is not optimized. In this paper, first we have proposed a secure technique which is highly robust, optimized, and fast. Secondly, unlike most of the fingerprint biometrics apart from the minutiae point location and orientation, we have used the quality of minutiae points as well to construct an optimized template. Third, the template constructed is in 3D shell shape. We have rigorously evaluated the technique on nine different fingerprint databases. The obtained results from the experiments are highly promising and show the effectiveness of the technique.
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2

Jiang, Bin, Yikun Zhao, Hongmei Yi, Yongxue Huo, Haotian Wu, Jie Ren, Jianrong Ge, Jiuran Zhao, and Fengge Wang. "PIDS: A User-Friendly Plant DNA Fingerprint Database Management System." Genes 11, no. 4 (March 30, 2020): 373. http://dx.doi.org/10.3390/genes11040373.

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The high variability and somatic stability of DNA fingerprints can be used to identify individuals, which is of great value in plant breeding. DNA fingerprint databases are essential and important tools for plant molecular research because they provide powerful technical and information support for crop breeding, variety quality control, variety right protection, and molecular marker-assisted breeding. Building a DNA fingerprint database involves the production of large amounts of heterogeneous data for which storage, analysis, and retrieval are time and resource consuming. To process the large amounts of data generated by laboratories and conduct quality control, a database management system is urgently needed to track samples and analyze data. We developed the plant international DNA-fingerprinting system (PIDS) using an open source web server and free software that has automatic collection, storage, and efficient management functions based on merging and comparison algorithms to handle massive microsatellite DNA fingerprint data. PIDS also can perform genetic analyses. This system can match a corresponding capillary electrophoresis image on each primer locus as fingerprint data to upload to the server. PIDS provides free customization and extension of back-end functions to meet the requirements of different laboratories. This system can be a significant tool for plant breeders and can be applied in forensic science for human fingerprint identification, as well as in virus and microorganism research.
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Gabryel, Marcin, Konrad Grzanek, and Yoichi Hayashi. "Browser Fingerprint Coding Methods Increasing the Effectiveness of User Identification in the Web Traffic." Journal of Artificial Intelligence and Soft Computing Research 10, no. 4 (October 1, 2020): 243–53. http://dx.doi.org/10.2478/jaiscr-2020-0016.

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AbstractWeb-based browser fingerprint (or device fingerprint) is a tool used to identify and track user activity in web traffic. It is also used to identify computers that are abusing online advertising and also to prevent credit card fraud. A device fingerprint is created by extracting multiple parameter values from a browser API (e.g. operating system type or browser version). The acquired parameter values are then used to create a hash using the hash function. The disadvantage of using this method is too high susceptibility to small, normally occurring changes (e.g. when changing the browser version number or screen resolution). Minor changes in the input values generate a completely different fingerprint hash, making it impossible to find similar ones in the database. On the other hand, omitting these unstable values when creating a hash, significantly limits the ability of the fingerprint to distinguish between devices. This weak point is commonly exploited by fraudsters who knowingly evade this form of protection by deliberately changing the value of device parameters. The paper presents methods that significantly limit this type of activity. New algorithms for coding and comparing fingerprints are presented, in which the values of parameters with low stability and low entropy are especially taken into account. The fingerprint generation methods are based on popular Minhash, the LSH, and autoencoder methods. The effectiveness of coding and comparing each of the presented methods was also examined in comparison with the currently used hash generation method. Authentic data of the devices and browsers of users visiting 186 different websites were collected for the research.
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Ju, Seung-hwan, Hee-suk Seo, Sung-hyu Han, Jae-cheol Ryou, and Jin Kwak. "A Study on User Authentication Methodology Using Numeric Password and Fingerprint Biometric Information." BioMed Research International 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/427542.

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The prevalence of computers and the development of the Internet made us able to easily access information. As people are concerned about user information security, the interest of the user authentication method is growing. The most common computer authentication method is the use of alphanumerical usernames and passwords. The password authentication systems currently used are easy, but only if you know the password, as the user authentication is vulnerable. User authentication using fingerprints, only the user with the information that is specific to the authentication security is strong. But there are disadvantage such as the user cannot change the authentication key. In this study, we proposed authentication methodology that combines numeric-based password and biometric-based fingerprint authentication system. Use the information in the user's fingerprint, authentication keys to obtain security. Also, using numeric-based password can to easily change the password; the authentication keys were designed to provide flexibility.
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5

Agarwal, Rohit, A. S. Jalal, and K. V. Arya. "A review on presentation attack detection system for fake fingerprint." Modern Physics Letters B 34, no. 05 (February 3, 2020): 2030001. http://dx.doi.org/10.1142/s021798492030001x.

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Fingerprint recognition systems are susceptible to artificial spoof fingerprint attacks, like molds manufactured from polymer, gelatin or Play-Doh. Presentation attack is an open issue for fingerprint recognition systems. In a presentation attack, synthetic fingerprint which is reproduced from a real user is submitted for authentication. Different sensors are used to capture the live and fake fingerprint images. A liveness detection system has been designed to defeat different classes of spoof attacks by differentiating the features of live and fake fingerprint images. In the past few years, many hardware- and software-based approaches are suggested by researchers. However, the issues still remain challenging in terms of robustness, effectiveness and efficiency. In this paper, we explore all kinds of software-based solution to differentiate between real and fake fingerprints and present a comprehensive survey of efforts in the past to address this problem.
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6

Diaz Pineda, Mabel Rocio, Maria Alejandra Dueñas, and Karen Dayanna Acevedo. "Fingerprints detection using neural networks suitable to physical changes of fingerprint." Revista CINTEX 22, no. 2 (December 30, 2017): 35–50. http://dx.doi.org/10.33131/24222208.271.

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This working paper shows the results of finished research, using image processing techniques to improve the fingerprint obtained from a database, where the image is normalized and segmented to get only the section of the image with the fingerprint. Then, the Gabor filter is applied, and it corrects defects in ridges and valleys, allowing continuity. That way, if the fingerprint has a physical defect, the filter can correct it as long as the segment orientation to be correct. Once improved, the fingerprint, it is binarized and thinned for minutiae extraction. The false minutiae are filtered and eliminated in order to ensure the operation of the algorithm. Finally, it is necessary training with the minutiae of all fingerprints in the database, to individually determine which user belongs the fingerprint entered. The system has a reliability of 81% of the process, with the pre-processing part being crucial to guarantee the correct extraction of the characteristics of fingerprints.
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7

Alakhras, Marwan, Mousa Hussein, and Mourad Oussalah. "Location Fixing and Fingerprint Matching Fingerprint Map Construction for Indoor Localization." Journal of Sensors 2020 (January 17, 2020): 1–14. http://dx.doi.org/10.1155/2020/7801752.

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Building the fingerprint map for indoor localization problems is a labour-intensive and time-consuming process. However, due to its direct influence on the location estimation accuracy, finding a proper mechanism to construct the fingerprint map is essential to enhance the position estimation accuracy. Therefore, in this work, we present a fingerprint map construction technique based on location fix determination and fingerprint matching motivated by the availability of advanced sensing capabilities in smartphones to reduce the time and labour cost required for the site survey. The proposed Location Fixing and Finger Matching (LFFM) method use a landmark graph-based localization approach to automatically estimate the location fixes for the Reference Points and matching the collected fingerprints, without requiring active user participation. Experimental results show that the proposed LFFM is faster than the manual fingerprint map construction method and remarkably improves the positioning accuracy.
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8

Sanchez-Reillo, R., L. Mengibar-Pozo, and C. Sanchez-Avila. "Microprocessor smart cards with fingerprint user authentication." IEEE Aerospace and Electronic Systems Magazine 18, no. 3 (March 2003): 22–24. http://dx.doi.org/10.1109/maes.2003.1193715.

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9

Cahyaningtiyas, Rizqia, Efy Yosrita, and Rakhmat Arianto. "THE AUTOMATIC DOORS INTEGRATED ABSENCE AND USER ACCESS USING FINGERPRINT." Jurnal Ilmiah FIFO 8, no. 2 (November 1, 2016): 147. http://dx.doi.org/10.22441/fifo.v8i2.1309.

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This research aims to design Accompanied Door Access System Automation Absence and User Access Rights Using Integrated Fingerprint Database on Basic Computer Lab Informatics STT-PLN. What is meant by "Absent Automation and User Access Rights" among other computerized attendance automatically using fingerprint and right into a room on a predetermined schedule of lectures on computer lab space. System design method used is the method of evolutionary prototype, using MySQL database and coding using Visual C # .NET. These results indicate that the Door Access System Automation Accompanied Absence and User Access Rights Using Integrated Fingerprint Database can help assistants in attendance processing, computer lab room becomes more secure and computerized
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10

Stanton, Brian, Mary Theofanos, Shahram Orandi, Ross Micheals, and Nien-Fan Zhang. "Effects of Scanner Height on Fingerprint Capture." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 51, no. 10 (October 2007): 592–96. http://dx.doi.org/10.1177/154193120705101005.

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Although the deployment of biometric technologies such as fingerprints is becoming more widespread, little attention is being paid to the human-computer interaction that such technologies involve. Most biometric systems employ both hardware and software measures to maximize the capture quality of the biometric data. The physical presentation of the biometric data by the participant to the system involves many anthropometric and ergonomic factors that have been largely ignored. This study examined the effect of the height of the sensor on the quality and the time required to collect fingerprints. User performance, both fingerprint quality and timing, was impacted by scanner height.
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11

IWASOKUN, Gabriel B. "A Fingerprint-Based Scheme for ATM User Authentication." International Journal of Information Security and Cybercrime 5, no. 2 (December 29, 2016): 71–86. http://dx.doi.org/10.19107/ijisc.2016.02.07.

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12

Vibert, Benoit, Jean-Marie Le Bars, Christophe Charrier, and Christophe Rosenberger. "Logical Attacks and Countermeasures for Fingerprint On-Card-Comparison Systems." Sensors 20, no. 18 (September 21, 2020): 5410. http://dx.doi.org/10.3390/s20185410.

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Digital fingerprints are being used more and more to secure applications for logical and physical access control. In order to guarantee security and privacy trends, a biometric system is often implemented on a secure element to store the biometric reference template and for the matching with a probe template (on-card-comparison). In order to assess the performance and robustness against attacks of these systems, it is necessary to better understand which information could help an attacker successfully impersonate a legitimate user. The first part of the paper details a new attack based on the use of a priori information (such as the fingerprint classification, sensor type, image resolution or number of minutiae in the biometric reference) that could be exploited by an attacker. In the second part, a new countermeasure against brute force and zero effort attacks based on fingerprint classification given a minutiae template is proposed. These two contributions show how fingerprint classification could have an impact for attacks and countermeasures in embedded biometric systems. Experiments show interesting results on significant fingerprint datasets.
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13

F.W. Onifade, Olufade, Paul Akinde, and Folasade Olubusola Isinkaye. "Circular Gabor wavelet algorithm for fingerprint liveness detection." Journal of Advanced Computer Science & Technology 9, no. 1 (January 11, 2020): 1. http://dx.doi.org/10.14419/jacst.v9i1.29908.

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Biometrics usage is growing daily and fingerprint-based recognition system is among the most effective and popular methods of personality identification. The conventional fingerprint sensor functions on total internal reflectance (TIR), which is a method that captures the external features of the finger that is presented to it. Hence, this opens it up to spoof attacks. Liveness detection is an anti-spoofing approach that has the potentials to identify physiological features in fingerprints. It has been demonstrated that spoof fingerprint made of gelatin, gummy and play-doh can easily deceive sensor. Therefore, the security of such sensor is not guaranteed. Here, we established a secure and robust fake-spoof fingerprint identification algorithm using Circular Gabor Wavelet for texture segmentation of the captured images. The samples were exposed to feature extraction processing using circular Gabor wavelet algorithm developed for texture segmentations. The result was evaluated using FAR which measures if a user presented is accepted under a false claimed identity. The FAR result was 0.03125 with an accuracy of 99.968% which showed distinct difference between live and spoof fingerprint.
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14

Yassin, Ali A. "Efficiency and Flexibility of Fingerprint Scheme Using Partial Encryption and Discrete Wavelet Transform to Verify User in Cloud Computing." International Scholarly Research Notices 2014 (September 24, 2014): 1–13. http://dx.doi.org/10.1155/2014/351696.

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Now, the security of digital images is considered more and more essential and fingerprint plays the main role in the world of image. Furthermore, fingerprint recognition is a scheme of biometric verification that applies pattern recognition techniques depending on image of fingerprint individually. In the cloud environment, an adversary has the ability to intercept information and must be secured from eavesdroppers. Unluckily, encryption and decryption functions are slow and they are often hard. Fingerprint techniques required extra hardware and software; it is masqueraded by artificial gummy fingers (spoof attacks). Additionally, when a large number of users are being verified at the same time, the mechanism will become slow. In this paper, we employed each of the partial encryptions of user’s fingerprint and discrete wavelet transform to obtain a new scheme of fingerprint verification. Moreover, our proposed scheme can overcome those problems; it does not require cost, reduces the computational supplies for huge volumes of fingerprint images, and resists well-known attacks. In addition, experimental results illustrate that our proposed scheme has a good performance of user’s fingerprint verification.
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15

Praseetha, V. M., Saad Bayezeed, and S. Vadivel. "Secure Fingerprint Authentication Using Deep Learning and Minutiae Verification." Journal of Intelligent Systems 29, no. 1 (April 10, 2019): 1379–87. http://dx.doi.org/10.1515/jisys-2018-0289.

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Abstract Nowadays, there has been an increase in security concerns regarding fingerprint biometrics. This problem arises due to technological advancements in bypassing and hacking methodologies. This has sparked the need for a more secure platform for identification. In this paper, we have used a deep Convolutional Neural Network as a pre-verification filter to filter out bad or malicious fingerprints. As deep learning allows the system to be more accurate at detecting and reducing false identification by training itself again and again with test samples, the proposed method improves the security and accuracy by multiple folds. The implementation of a novel secure fingerprint verification platform that takes the optical image of a fingerprint as input is explained in this paper. The given input is pre-verified using Google’s pre-trained inception model for deep learning applications, and then passed through a minutia-based algorithm for user authentication. Then, the results are compared with existing models.
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16

Ntoutsi, Eirini, Myra Spiliopoulou, and Yannis Theodoridis. "FINGERPRINT." International Journal of Data Warehousing and Mining 8, no. 3 (July 2012): 27–44. http://dx.doi.org/10.4018/jdwm.2012070102.

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Monitoring and interpretation of changing patterns is a task of paramount importance for data mining applications in dynamic environments. While there is much research in adapting patterns in the presence of drift or shift, there is less research on how to maintain an overview of pattern changes over time. A major challenge is summarizing changes in an effective way, so that the nature of change can be understood by the user, while the demand on resources remains low. To this end, the authors propose FINGERPRINT, an environment for the summarization of cluster evolution. Cluster changes are captured into an “evolution graph,” which is then summarized based on cluster similarity into a fingerprint of evolution by merging similar clusters. The authors propose a batch summarization method that traverses and summarizes the Evolution Graph as a whole and an incremental method that is applied during the process of cluster transition discovery. They present experiments on different data streams and discuss the space reduction and information preservation achieved by the two methods.
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Zhang, Shuai, Jiming Guo, Nianxue Luo, Lei Wang, Wei Wang, and Kai Wen. "Improving Wi-Fi Fingerprint Positioning with a Pose Recognition-Assisted SVM Algorithm." Remote Sensing 11, no. 6 (March 17, 2019): 652. http://dx.doi.org/10.3390/rs11060652.

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The fingerprint method has been widely adopted for Wi-Fi indoor positioning. In the fingerprint matching process, user poses and user body shadowing have serious impact on the received signal strength (RSS) data and degrade matching accuracy; however, this impact has not attracted large attention. In this study, we systematically investigate the impact of user poses and user body shadowing on the collected RSS data and propose a new method called the pose recognition-assisted support vector machine algorithm (PRASVM). It fully exploits the characteristics of different user poses and improves the support vector machine (SVM) positioning performance by introducing a pose recognition procedure. This proposed method firstly establishes a fingerprint database with RSS and sensor data corresponding to different poses in the offline phase, and fingerprints of different poses in the database are extracted to train reference point (RP) classifiers of different poses and a pose classifier using an SVM algorithm. Secondly, in the online phase, the poses of RSS data measured online are recognised by a pose classifier, and RSS data measured online are grouped with different poses. Then online RSS data from each group at an unknown user location are reclassified as corresponding RPs by the RP classifiers of the corresponding poses. Finally, user location is determined by grouped RSS data corresponding to coordinates of the RPs. By considering the user pose and user body shadowing, the observed RSS data matches the fingerprint database better, and the classification accuracy of grouped online RSS data is remarkably improved. To verify performances of the proposed method, experiments are carried out: one in an office setting, and the other in a lecture hall. The experimental results show that the positioning accuracies of the proposed PRASVM algorithm outperform the conventional weighted k-nearest neighbour (WKNN) algorithm by 52.29% and 40.89%, outperform the SVM algorithm by 73.74% and 60.45%, and outperform the pose recognition-assisted WKNN algorithm by 34.76% and 21.86%, respectively. As a result, the PRASVM algorithm noticeably improves positioning accuracy.
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18

Lee, J. K., S. R. Ryu, and K. Y. Yoo. "Fingerprint-based remote user authentication scheme using smart cards." Electronics Letters 38, no. 12 (2002): 554. http://dx.doi.org/10.1049/el:20020380.

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19

Vilardy O., Juan M., María S. Millán, and Elisabet Pérez-Cabré. "Image Encryption System Based on a Nonlinear Joint Transform Correlator for the Simultaneous Authentication of Two Users." Photonics 6, no. 4 (December 14, 2019): 128. http://dx.doi.org/10.3390/photonics6040128.

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We propose a new encryption system based on a nonlinear joint transform correlator (JTC) using the information of two biometrics (one digital fingerprint for each user) as security keys of the encryption system. In order to perform the decryption and authentication in a proper way, it is necessary to have the two digital fingerprints from the respective users whose simultaneous authentication is pursued. The proposed security system is developed in the Fourier domain. The nonlinearity of the JTC along with the five security keys given by the three random phase masks and the two digital fingerprints of the two users allow an increase of the system security against brute force and plaintext attacks. The feasibility and validity of this proposal is demonstrated using digital fingerprints as biometrics in numerical experiments.
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20

Chen, Ching-Han, Chen-Shuo An, and Ching-Yi Chen. "Fingerprint Quality Assessment based on Texture and Geometric Features." Journal of Imaging Science and Technology 64, no. 4 (July 1, 2020): 40403–1. http://dx.doi.org/10.2352/j.imagingsci.technol.2020.64.4.040403.

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Abstract Fingerprint quality assessments are generally used to evaluate the quality of images obtained from fingerprint sensors, and effective fingerprint quality assessment methods are crucial to establishing high-performance biometric identification systems. The use of fingerprint quality assessments helps improve the accuracy of fingerprint registration and user satisfaction. NIST Fingerprint Image Quality (NFIQ) is a popular fingerprint quality assessment algorithm; however, it is unable to provide high-quality assessments for some partial fingerprint images obtained from mobile device sensors. In this study, a hybrid fingerprint assessment framework that integrated texture and geometric features was examined. The final quality assessment values obtained by the framework were higher than those obtained using NFIQ, effectively elevating the performance of existing NFIQ algorithms and expanding its scope of application for different fingerprint images.
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21

Selvarani, P., and N. Malarvizhi. "Secure data in cloud with multimodal key generation." International Journal of Engineering & Technology 7, no. 1.7 (February 5, 2018): 27. http://dx.doi.org/10.14419/ijet.v7i1.7.9382.

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Data Security is the Major problem in Cloud Computing. In order to overcome the data security problem the proposed technique utilizes effective data storage using biometric-based cryptographic authentication to support the user authentication for the cloud environment. For user authentication here we are considering iris and fingerprint. Initially the feature values are extracted from the iris and fingerprint using local binary pattern and Minutiae extraction respectively. Local binary pattern operator works with the eight neighbors of a pixel, using the value of this center pixel as a threshold. Minutiae points are the major features of a fingerprint image and are used in the matching of fingerprints. These minutiae points are used to determine the uniqueness of a fingerprint image. Based on that the proposed feature values are extracted from the iris and fingerprint image. In order to improve the security, the suggested technique utilizes the optimal features. For selecting the optimal features hybrid particle swarm optimization and genetic algorithm (HPSOGA) is utilized. Particle swarm optimization (PSO) is a population based stochastic optimization technique. The system is initialized with a population of random solutions and searches for optima by updating generations. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. Genetic Algorithms (GAs) are adaptive heuristic search algorithm based on the evolutionary ideas of natural selection and genetics. In our proposed method these two optimization algorithm is hybrid for more secure. From the optimization algorithm the suggested technique selects the optimal features. and then the optimal features are used to encrypt the input data. For encryption and decryption, the proposed technique utilizes Triple DES algorithm. Finally the encrypted data is stored in cloud. The performance of the proposed technique is evaluated in terms of encryption and decryption time, memory utilization and overall execution time. Our proposed data storage using biometric-based authentication is implemented with the help of Cloud simulator in the working platform of java.
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Iskhakov, A. Y., and A. A. Salomatin. "Estimation of the time for calculating the attributes of browser fingerprints in the user authentication task." E3S Web of Conferences 224 (2020): 01030. http://dx.doi.org/10.1051/e3sconf/202022401030.

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This paper presents an overview of the essence of web space which may contain information required to identify and authenticate users on the Internet in order to prevent attempts at malicious acts. Essences with a common content or the same detection method are structured into groups. The greatest attention is paid to one of these groups of entities: «the browser fingerprint» group. An approach and software have been proposed that allow for automated search of the values of entities belonging to this group and for estimating the time of this search for a specific infrastructure in order to develop adaptive authentication mechanisms. Moreover, an analysis of the average time to calculate the values of attributes has been carried out for the most informative browser fingerprints.
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23

Qian, Jiansheng, and Mingzhi Song. "Research and Application of Underground WLAN Adaptive Radio Fingerprint Database." Sensors 20, no. 4 (February 21, 2020): 1182. http://dx.doi.org/10.3390/s20041182.

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Fingerprint positioning based on WiFi in coal mines has received much attention because of the widespread application of WiFi. Fingerprinting techniques have developed rapidly due to the efforts of many researchers. However, the off-line construction of the radio fingerprint database is a tedious and time-consuming process. When the underground environments change, it may be necessary to update the signal received signal strength indication (RSSI) of all reference points, which will affect the normal working of a personnel positioning system. To solve this problem, an adaptive construction and update method based on a quantum-behaved particle swarm optimization–user-location trajectory feedback (QPSO–ULTF) for a radio fingerprint database is proposed. The principle of ULTF is that the mobile terminal records and uploads the related dataset in the process of user’s walking, and it forms the user-location track with RSSI through the analysis and processing of the positioning system server. QPSO algorithm is used for the optimal radio fingerprint match between the RSSI of the access point (AP) contained in the dataset of user-location track and the calibration samples to achieve the adaptive generation and update of the radio fingerprint samples. The experimental results show that the radio fingerprint database generated by the QPSO–ULTF is similar to the traditional radio fingerprint database in the statistical distribution characteristics of the signal received signal strength (RSS) at each reference point. Therefore, the adaptive radio fingerprint database can replace the traditional radio fingerprint database. The comparable results of well-known traditional positioning methods demonstrate that the radio fingerprint database generated or updated by the QPSO–ULTF has a good positioning effect, which can ensure the normal operation of a personnel positioning system.
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D. Mahesh Kumar, Aravinda H. S., Thejaswini P. ,. Anu H. ,. "AN ADAPTIVE ALGORITHM BASED AUTHENTICATION SYSTEM FOR REAL-TIME BIOMETRIC TIME-ATTENDANCE SYSTEM." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 1 (February 18, 2021): 77–90. http://dx.doi.org/10.17762/itii.v9i1.104.

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Biometric features are physical and biological characteristics that are unique to a person and can be used to accomplish authentication based on the particular modality. The main purpose of implementation of an Adaptive auto-correction technique for biometric time-attendance system is to improve the matching rate of fingerprint verification under the condition when fingerprint patterns vary due to environmental parameter like temperature. An Adaptive auto-correction technique is proposed which auto-corrects the reference fingerprint template at the time of genuine user rejection. The proposed technique is implemented on commercially available biometric device which uses Innovatrics, a standard commercially available extractor and matcher. Evaluation is carried out on 250 fingerprint templates of 10-users captured at varying temperature from 250C to 00C. The experimental analysis will be carried out to improve the recognition rate.
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Singh, Law Kumar, Munish Khanna, and Hitendra Garg. "Multimodal Biometric Based on Fusion of Ridge Features with Minutiae Features and Face Features." International Journal of Information System Modeling and Design 11, no. 1 (January 2020): 37–57. http://dx.doi.org/10.4018/ijismd.2020010103.

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Multimodal biometrics refers to the exploiting combination of two or more biometric modalities in an identification of a system. Fingerprint, face, retina, iris, hand geometry, DNA, and palm print are physiological traits while voice, signature, keystrokes, gait are behavioural traits used for identification by a system. Single biometric features like faces, fingerprints, irises, retinas, etc., deteriorate or change with time, environment, user mode, physiological defects, and circumstance therefore integrating multi features of biometric traits increase robustness of the system. The proposed multimodal biometrics system presents recognition based on face detection and fingerprint physiological traits. This proposed system increases the efficiency, accuracy and decreases execution time of the system as compared to the existing systems. The performance of proposed method is reported in terms of parameters such as False Rejection Rate (FRR), False Acceptance Rate (FAR) and Equal Error Rate (EER) and accuracy is reported at 95.389%.
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Theofanos, Mary, Brian Stanton, Charles Sheppard, Ross Micheals, and Nien-Fan Zhang. "Does the Angle of a Fingerprint Scanner Affect User Performance?" Proceedings of the Human Factors and Ergonomics Society Annual Meeting 52, no. 24 (September 2008): 1989–93. http://dx.doi.org/10.1177/154193120805202415.

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27

Budiman, Muhammad Arif, and I. Gusti Agung Widagda. "Fingerprints Image Recognition by Using Perceptron Artificial Neural Network." BULETIN FISIKA 21, no. 2 (May 5, 2020): 37. http://dx.doi.org/10.24843/bf.2020.v21.i02.p01.

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Security systems that use passwords or identity cards can be hacked and misused. One of alternative security system is to use biometric identification. The biometric system that is popularly used is fingerprints, because the system is safe and comfortable. Fingerprints have a distinctive pattern for each individual and this makes fingerprints relatively difficult to fake, so the system is safe. Comfortable because the verification process is easily done. The problem that often occurs on the system of fingerprint scanner is found an error and the user has difficulty when accessing. To handle with these problems has developed an artificial intelligence system. One of arificial intelligence in pattern identification is artificial neural networks (ANN). From some of the results of previous research showed that the ANN method is reliable in pattern identification. Based on these facts, the method used in this research is the perceptron ANN method with values learning rate varying. In the research the program conducted by testing 20 samples showed that the performance of the perceptron ANN method is relatively good method in fingerprint image recognition. This can be indicated from the value of accuracy (0.95), precision (0.83), TP rate (1), and FP rate (0.07)). In addition, the location of the point coordinate (FP rate; TP rate) is (0.07; 1) in ROC graphs is located on the upper left (perfect classifier region).
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Yang, Chao, Junwei Zhang, Jingjing Guo, Yu Zheng, Li Yang, and Jianfeng Ma. "Fingerprint Protected Password Authentication Protocol." Security and Communication Networks 2019 (June 26, 2019): 1–12. http://dx.doi.org/10.1155/2019/1694702.

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With the rapid development of industrial Internet of things (IIOT), a variety of cloud services have been deployed to store and process the big data of IIOT. The traditional password only authentication is unable to meet the needs of security situation in IIOT. Therefore, a lot of mobile phone assisted password authentication schemes have been proposed. However, in existing schemes, the secret information is required to be stored in the user’s mobile phone. Once the phone is lost, the secret information may be obtained by the opponent, which will bring irreparable loss to the user. To address the above problems, we propose a fingerprint protected password authentication scheme which has no need to store the secret parameter in the mobile phone. When a user logs in, he uses his mobile phone to generate the private key which is used to decrypt the encrypted text generated during the registration phase. The process of generating the private key needs to enter the password and the fingerprint. When the computer interacts with the mobile phone, the user’s password will be blinded so that it can protect the user’s password from adversary’s attacks. Theoretical analysis and experimental results show that our scheme improves the security of the user’s secret. Meanwhile, our scheme can resist the opponent’s dictionary attacks, replay attacks, and phishing attack. Our scheme can reduce the storage pressure of the mobile phone and is easy to deploy.
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Husseis, Anas, Judith Liu-Jimenez, and Raul Sanchez-Reillo. "The Impact of Pressure on the Fingerprint Impression: Presentation Attack Detection Scheme." Applied Sciences 11, no. 17 (August 26, 2021): 7883. http://dx.doi.org/10.3390/app11177883.

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Fingerprint recognition systems have been widely deployed in authentication and verification applications, ranging from personal smartphones to border control systems. Recently, the biometric society has raised concerns about presentation attacks that aim to manipulate the biometric system’s final decision by presenting artificial fingerprint traits to the sensor. In this paper, we propose a presentation attack detection scheme that exploits the natural fingerprint phenomena, and analyzes the dynamic variation of a fingerprint’s impression when the user applies additional pressure during the presentation. For that purpose, we collected a novel dynamic dataset with an instructed acquisition scenario. Two sensing technologies are used in the data collection, thermal and optical. Additionally, we collected attack presentations using seven presentation attack instrument species considering the same acquisition circumstances. The proposed mechanism is evaluated following the directives of the standard ISO/IEC 30107. The comparison between ordinary and pressure presentations shows higher accuracy and generalizability for the latter. The proposed approach demonstrates efficient capability of detecting presentation attacks with low bona fide presentation classification error rate (BPCER) where BPCER is 0% for an optical sensor and 1.66% for a thermal sensor at 5% attack presentation classification error rate (APCER) for both.
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Selvarani, P., and N. Malarvizhi. "Multibiometric authentication with MATLAB simulation." International Journal of Engineering & Technology 7, no. 1.7 (February 5, 2018): 47. http://dx.doi.org/10.14419/ijet.v7i1.7.9389.

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Multimodal Biometric Authentication has been used as more security purpose for establishing the user Identification, Authentication and Verification purpose. Multimodal Biometric like Fingerprint and iris are used in this research work for authentication purpose using Matlab simulation. Fingerprint recognition process like Image Enhancement, binarization, Segmentation, thinning, Minutia marking, and Matching are performed with various techniques like Histogram Equalization, Adaptive Binarization, Morphological operations, Minutiae based techniques etc.,Iris recognition process like Segmentation, Normalization, Encoding and Matching are performed with various techniques like Canny edge detection, Daughman’s Rubber sheet model, Hamming Distance etc., can be applied for Fingerprint and iris recognition for authentication purpose. Finally Performance the measure of Precision, Recall, F-Score and Accuracy has evaluated in both fingerprint and iris. It can be concluded Iris Accuracy is higher 0.96% compared with fingerprint accuracy 0.81%.
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Bai, Junhang, Yongliang Sun, Weixiao Meng, and Cheng Li. "Wi-Fi Fingerprint-Based Indoor Mobile User Localization Using Deep Learning." Wireless Communications and Mobile Computing 2021 (January 8, 2021): 1–12. http://dx.doi.org/10.1155/2021/6660990.

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In recent years, deep learning has been used for Wi-Fi fingerprint-based localization to achieve a remarkable performance, which is expected to satisfy the increasing requirements of indoor location-based service (LBS). In this paper, we propose a Wi-Fi fingerprint-based indoor mobile user localization method that integrates a stacked improved sparse autoencoder (SISAE) and a recurrent neural network (RNN). We improve the sparse autoencoder by adding an activity penalty term in its loss function to control the neuron outputs in the hidden layer. The encoders of three improved sparse autoencoders are stacked to obtain high-level feature representations of received signal strength (RSS) vectors, and an SISAE is constructed for localization by adding a logistic regression layer as the output layer to the stacked encoders. Meanwhile, using the previous location coordinates computed by the trained SISAE as extra inputs, an RNN is employed to compute more accurate current location coordinates for mobile users. The experimental results demonstrate that the mean error of the proposed SISAE-RNN for mobile user localization can be reduced to 1.60 m.
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Bai, Junhang, Yongliang Sun, Weixiao Meng, and Cheng Li. "Wi-Fi Fingerprint-Based Indoor Mobile User Localization Using Deep Learning." Wireless Communications and Mobile Computing 2021 (January 8, 2021): 1–12. http://dx.doi.org/10.1155/2021/6660990.

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In recent years, deep learning has been used for Wi-Fi fingerprint-based localization to achieve a remarkable performance, which is expected to satisfy the increasing requirements of indoor location-based service (LBS). In this paper, we propose a Wi-Fi fingerprint-based indoor mobile user localization method that integrates a stacked improved sparse autoencoder (SISAE) and a recurrent neural network (RNN). We improve the sparse autoencoder by adding an activity penalty term in its loss function to control the neuron outputs in the hidden layer. The encoders of three improved sparse autoencoders are stacked to obtain high-level feature representations of received signal strength (RSS) vectors, and an SISAE is constructed for localization by adding a logistic regression layer as the output layer to the stacked encoders. Meanwhile, using the previous location coordinates computed by the trained SISAE as extra inputs, an RNN is employed to compute more accurate current location coordinates for mobile users. The experimental results demonstrate that the mean error of the proposed SISAE-RNN for mobile user localization can be reduced to 1.60 m.
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Wei, Jie, Fang Zhao, and Haiyong Luo. "SP-Loc: A crowdsourcing fingerprint based shop-level indoor localization algorithm integrating shop popularity without the indoor map." International Journal of Distributed Sensor Networks 14, no. 11 (November 2018): 155014771881563. http://dx.doi.org/10.1177/1550147718815637.

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With the development of indoor localization technology, the location-based services such as product advertising recommendation in the shopping mall attract widespread attention, as precise user location significantly improves the efficiency of advertising push and brings broader profits. However, most of the Wi-Fi-based indoor localization approaches requiring professionals to deploy expensive beacon devices and intensively collect fingerprints in each location grid, which severely limits its extensive promotion. We introduce a zero-cost indoor localization algorithm utilizing crowdsourcing fingerprints to obtain the shop recognition where the user is located. Naturally utilizing the Wi-Fi, GPS, and time-stamp fingerprints collected from the smartphone when user paid as the crowdsourcing fingerprint, we avoid the requirement for indoor map and get rid of both devices cost and manual signal collecting process. Moreover, a shop-level hierarchical indoor localization framework is proposed, and high robustness features based on Wi-Fi sequences variation pattern in the same shop analysis are designed to avoid the received signal strength fluctuations. Besides, we also pay more attention to mine the popularity properties of shops and explore GPS features to improve localization accuracy in the Wi-Fi absence situation effectively. Massive experiments indicate that SP-Loc achieves more than 93% localization accuracy.
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Moskovchenko, Valeriy, Danil Stolyarov, Aleksandr Gorbunov, and Vladislav Belyanin. "The Analysis of Technologies Protecting from Web Browsers Identification." NBI Technologies, no. 1 (August 2018): 34–39. http://dx.doi.org/10.15688/nbit.jvolsu.2018.1.6.

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In the age of information technology, it is becoming increasingly difficult to maintain privacy. Sometimes anonymity on the Internet helps to protect everyone’s right. Anonymity on the Internet also helps to protect against possible illegal actions of third parties. There is a number of technologies that you can use to monitor site user activity. These include technologies such as cookies and fingerprints. Today, cookies technology is an important component of most operations on the Internet. This technology is considered to be one of the main tools that Internet resource owners use to track customers. However, this technique is gradually becoming obsolete and often does not give the desired effect. Fingerprint technology is a global identifier. Browser typos make its owner more recognizable not only on frequently visited Internet resources, but also in other electronic sources. Fingerprints capture the holistic picture that a resource receives from a web browser. This allows you to identify the client even if you make changes to your browser settings. This article deals with the problem of anonymity preservation in a network. The authors describe the main technologies for tracking the users’ website activity, the principles of their work, and the protection methods against these technologies. The advantages and disadvantages of the cookies and fingerprint technologies have also been determined.
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35

Rashid, Mofeed, and Huda Zaki. "RSA Cryptographic Key Generation Using Fingerprint Minutiae." Iraqi Journal for Computers and Informatics 41, no. 1 (December 31, 2014): 66–69. http://dx.doi.org/10.25195/ijci.v41i1.101.

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Human users find difficult to remember long cryptographic keys. Therefore, researchers, for a long time period, have beeninvestigating ways to use biometric features of the user rather than memorable password or passphrase, in an attempt to produce tough andunrepeatable cryptographic keys and to construct the key unpredictable to a hacker who is deficient of important knowledge about theuser's biometrics. In this paper, generating the strong bio-crypt key based on fingerprint minutiae is presented. At first, the minutiae pointsare extracted from the fingerprint image based on image processing algorithms. Then, the extracted fingerprint minutiae are used forgenerating a 1024 bit prime numbers that used in RSA cypher algorithm to generate 2048 cryptographic key.
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36

Hu, Chia Shing, and Chia Shing Hu. "Fingerprint Identification Based on Mopso in SVM." Applied Mechanics and Materials 479-480 (December 2013): 810–17. http://dx.doi.org/10.4028/www.scientific.net/amm.479-480.810.

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Abstract. The problem of fingerprint classification is discussed for many years. Support Vector Machine (SVM) is a traditional artificial intelligence algorithm developed for dealing classification problems. In this paper, we used the idea of multi-objective optimization to transform SVM into a new form, since the core concept of SVM is built up on a single optimization equation, and some parameters for this algorithm still need user to make tons of experiment to determine. Our algorithm has successfully proved that user do not need to make experiment to determine the penalty parameter C. NIST-4 database is used to assess our proposed algorithm. The experiment results show our method can get good classification results.
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37

Han, Yoon Chung, and Byeong-jun Han. "Skin Pattern Sonification as a New Timbral Expression." Leonardo Music Journal 24 (December 2014): 41–43. http://dx.doi.org/10.1162/lmj_a_00199.

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The authors discuss two sonification projects that transform fingerprint and skin patterns into audio: (1) Digiti Sonus, an interactive installation performing fingerprint sonification and visualization and (2) skin pattern sonification, which converts pore networks into sound. The projects include novel techniques for representing user-intended fingerprint expression and skin pattern selection as audio parameters.
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38

Kwao, Lazarus. "User Authentication Model for Securing E-Health System using Fingerprint Biometrics." International Journal for Research in Applied Science and Engineering Technology 7, no. 11 (November 30, 2019): 285–93. http://dx.doi.org/10.22214/ijraset.2019.11046.

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39

Firdaus, Firdaus, Noor Azurati Ahmad, and Shamsul Sahibuddin. "Fingerprint indoor positioning based on user orientations and minimum computation time." TELKOMNIKA (Telecommunication Computing Electronics and Control) 17, no. 4 (August 1, 2019): 1740. http://dx.doi.org/10.12928/telkomnika.v17i4.12774.

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40

Theofanos, Mary, Brian Stanton, Shahram Orandi, Ross Micheals, and Nien-Fan Zhang. "Ten-Print Fingerprint Capture: Effect of Instructional Modes on User Performance." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 51, no. 10 (October 2007): 597–601. http://dx.doi.org/10.1177/154193120705101006.

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Despite the increased deployment of biometric technologies in United States government applications, not enough attention is being paid to the human factors that such technologies involve. The use of biometric applications will be unfamiliar to many users, who may neither understand nor be comfortable with the technology. Currently, U.S. Customs and Border Protection (CBP) Officers are critical in communicating and training users in the acquisition of fingerprints. Since user behavior can affect both the throughput of the system as well as the quality of the captured images, guidelines for developing interactions with biometric applications that increase throughput and image quality would be valuable. This study examines the effect of instructional modes on user performance. Posters were not as effective in providing instructions to users as video or verbal instructions.
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41

Ku, W. C., S. T. Chang, and M. H. Chiang. "Further cryptanalysis of fingerprint-based remote user authentication scheme using smartcards." Electronics Letters 41, no. 5 (2005): 240. http://dx.doi.org/10.1049/el:20047658.

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42

Chang, Chin-Chen, and Iuon-Chang Lin. "Remarks on fingerprint-based remote user authentication scheme using smart cards." ACM SIGOPS Operating Systems Review 38, no. 4 (October 2004): 91–96. http://dx.doi.org/10.1145/1031154.1031165.

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43

Shigematsu, Satoshi, Takahiro Hatano, Hiroki Morimura, Katsuyuki Machida, and Yukio Okazaki. "Ubiquitous user authentication system with wireless battery-powered fingerprint identification module." IEEJ Transactions on Electrical and Electronic Engineering 2, no. 6 (2007): 643–50. http://dx.doi.org/10.1002/tee.20220.

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44

Shapovalova, N. N., I. O. Dotsenko, and V. O. Shcherbyna. "User system identification by fingerprint on the basis artificial intelligence methods." Jornal of Kryvyi Rih National University, no. 47 (2018): 81–84. http://dx.doi.org/10.31721/2306-5451-2018-1-47-81-84.

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45

Gupta, Himanshu, and Kapil Chauhan. "Role of Biometric security for The Enhancement of Data Security." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 14, no. 10 (July 27, 2015): 6184–89. http://dx.doi.org/10.24297/ijct.v14i10.1832.

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In today's society, data security is the big problem for every business organization or an individual. Most found threat is theft of personal data and information. With time digital data become more prevalent, personnel try to secure their information by using highly encrypted passwords and authentication identities, but, the misuse and theft of these security measures are rising in lot of theft cases Taking advantage of security flaws in authentication identities ends up in cards being duplicated or counterfeited and hence misused. This increasing fight with cyber security has been the sole reason of making biometric security systems, the important area of concern is that how do one can implement the biometric security for increasing of data security. First unique feature which is found different in every human is Fingerprints; Humans have used fingerprints for personal identification. Presently, most of the organisation use fingerprint recognition for authentication process it is one of the oldest and most commonly used biometrics, with high accuracy & generally easy and efficient and fast. In this paper we propose the idea to use fingerprint recognition along with the user authentication password or to access the data or information. Since the only person who can access information is the person linked to it, no thief can gain access. It also makes your data, very hard for cyber criminals to hack into.
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Jiang, Xing Chen, and Jian De Zheng. "An Indirect Fingerprint Authentication Scheme in Cloud Computing." Applied Mechanics and Materials 484-485 (January 2014): 986–90. http://dx.doi.org/10.4028/www.scientific.net/amm.484-485.986.

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The cloud computing offers dynamically scalable online resources provisioned as a service over the Internet cheaply. However, the security challenges it poses are equally striking. The reliable user authentication techniques are required to combat the rising security threat in cloud communications. Due to the non-denial requirements of remote user authentication scheme, it is most commonly achieved using some form of biometrics-based method. Fingerprint authentication is one of the popular and effective approaches to allow the only authorized users to access the cryptographic keys. While the critical issue in remote biometric cryptosystem is to protect the template of a user stored in a database. The biometric template is not secure and the stolen templates cannot be revoked, which is easy to leak user identity information. To overcome these shortcomings, in this paper, an indirect fingerprint authentication scheme is proposed. Further, we apply this secure scheme to the cloud system combing with PKI mechanism. At last, a comprehensive and detailed security analysis of the proposed scheme in cloud computing is provided.
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47

Et.al, Dilip Agarwal. "SmartUAV’sDelivery System using Fingerprint Authentication." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (April 11, 2021): 3185–91. http://dx.doi.org/10.17762/turcomat.v12i3.1560.

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In general, it is not possible to complete the delivery of the package competently because the main challenge is insufficient smart technology to identify the user for a package authentication. Therefore, fingerprint authentication is one of the intelligent authentication ideas of the package used as one solution to the above reference problem. The model should be properly prepared with regard to behavioral design in order to incorporate the UAV transport system in cities. The drone activity preparation and fingerprint authentication model for providing solutions is suggested in this regard. In terms of the computing time of the UAV and the optimality difference, the experimental results indicate a feasible solution and provide an efficient solution model.
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Gufron, Muhammad, Eko Budi Cahyono, and Gita Indah Marthasari. "Sistem Pelaporan Identifikasi Karakter Seorang Anak Berdasarkan Pola Sidik Jari dan Sudut Tangan." Jurnal Repositor 1, no. 1 (October 8, 2019): 17. http://dx.doi.org/10.22219/repositor.v1i1.6.

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Hand-fingerprint analysis is one of the biometric methods for knowing a person's character. Fingerprint analysis was developed as one of the methods to find out the most dominant brain functions affecting one's genetic potential. Through the interpretation of fingerprint patterns and measurements of the lines at the end of each finger can be read potential, motivation, learning style, work style, even the potential stress of a person who was born from birth. The existence of the relationship between the pattern of fingerprint with the character of a person raises the idea to create a system that can be used to analyze the characteristics of a child based on the type of fingerprint pattern it has. The system can perform analysis based on the fingerprint and hand angle patterns to get the type of spelling, learning style and character in the child in order to facilitate user in analyzing automatically based on fingerprint pattern and hand corner of input to get the output type of spiritedness, learning style and character in child.
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Rathore, Aditya Singh, Chenhan Xu, and Wenyao Xu. "Sonicprint." GetMobile: Mobile Computing and Communications 24, no. 4 (March 15, 2021): 43–46. http://dx.doi.org/10.1145/3457356.3457369.

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Although fingerprint technology holds great promise for user authentication, commercial scanners face significant challenges in terms of security (e.g., fake finger) and adoptability (e.g., wearables). SonicPrint pushes the boundary of fingerprint biometrics beyond smartphones to any smart devices without the need for specialized hardware. To achieve this, it listens for fingerprintinduced sonic effect (FiSe) caused when a user swipes his/her fingertip on smart device surface. Compared to other biometrics including physiological patterns and passive sensing, SonicPrint is a low-cost, privacyoriented and secure approach to identify users across smart devices of unique form-factors.
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Mary Bastina, A. Amali, and N. Rama. "Biometric Identification and Authentication Providence using Fingerprint for Cloud Data Access." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 1 (February 1, 2017): 408. http://dx.doi.org/10.11591/ijece.v7i1.pp408-416.

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<div><p>The raise in the recent security incidents of cloud computing and its challenges is to secure the data. To solve this problem, the integration of mobile with cloud computing, Mobile biometric authentication in cloud computing is presented in this paper. To enhance the security, the biometric authentication is being used, since the Mobile cloud computing is popular among the mobile user. This paper examines how the mobile cloud computing (MCC) is used in security issue with finger biometric authentication model. Through this fingerprint biometric, the secret code is generated by entropy value. This enables the person to request for accessing the data in the desk computer. When the person requests the access to the authorized user through Bluetooth in mobile, the Authorized user sends the permit access through fingerprint secret code. Finally this fingerprint is verified with the database in the Desk computer. If it is matched, then the computer can be accessed by the requested person.</p></div>
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