Journal articles: 'Device fingerprint'

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Arai, Fumihito, and Toshio Fukuda. "Fingerprint Image Sensing Using Micromechanical Key and Extraction Algorithm for Sensed Fingerprint Image." Journal of Robotics and Mechatronics 13, no. 5 (October 20, 2001): 458–63. http://dx.doi.org/10.20965/jrm.2001.p0458.

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A novel fingerprint image sensing device, which combines the ID bar code with fingerprints, has been proposed and developed. Due to the use of ID bar codes, higher security and less recognition time can be ensured. The device has been fabricated using new micromachining. The sensed image with this sensing device consists of both fingerprint patterns and ID bar lines. The corresponding extraction algorithm for the sensed fingerprint image has also been researched and developed. The algorithm extracts an ID bar image and a pure fingerprint image without ID bar lines from the single sensed image. The ID code can be extracted from the ID bar image, and the fingerprint image is processed to realize fingerprint identification.

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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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Kurtz, Andreas, Hugo Gascon, Tobias Becker, Konrad Rieck, and Felix Freiling. "Fingerprinting Mobile Devices Using Personalized Configurations." Proceedings on Privacy Enhancing Technologies 2016, no. 1 (January 1, 2016): 4–19. http://dx.doi.org/10.1515/popets-2015-0027.

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Abstract Recently, Apple removed access to various device hardware identifiers that were frequently misused by iOS third-party apps to track users. We are, therefore, now studying the extent to which users of smartphones can still be uniquely identified simply through their personalized device configurations. Using Apple’s iOS as an example, we show how a device fingerprint can be computed using 29 different configuration features. These features can be queried from arbitrary thirdparty apps via the official SDK. Experimental evaluations based on almost 13,000 fingerprints from approximately 8,000 different real-world devices show that (1) all fingerprints are unique and distinguishable; and (2) utilizing a supervised learning approach allows returning users or their devices to be recognized with a total accuracy of 97% over time

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Szweda, Roy. "Holographic fingerprint security device." Network Security 1997, no. 7 (July 1997): 7. http://dx.doi.org/10.1016/s1353-4858(97)89874-1.

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Szczepański, Tomasz, Urszula Więckiewicz, Barbara Konior, and Patryk Pucułek. "Vacuum metal deposition (VMD) – characteristics of the method." Issues of Forensic Science 308 (2020): 40–46. http://dx.doi.org/10.34836/pk.2020.308.1.

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Vacuum metal deposition was introduced in the process of visualization of latent fingermarks already in the 20th century. However, due to the requirement of using specialist equipment to ensure appropriate conditions for the development process, which would have generated significant costs, the method was not available in Poland. Technological developments, however, made it possible to create compact devices with smaller dimensions and lower parameters, which, nowadays, can be used in virtually every forensic fingerprint identification laboratory. The article describes the theoretical basis of the process of developing fingerprints by means of the vacuum metal deposition method with the use of sequential deposition of gold, zinc and silver on the tested surfaces. The device used for the VMD method is also presented along with sample effects of treating fingerprints on various surfaces, including registration in the range of reflected infrared light and with recovering marks on lifting foils. The final part deals with the issue of accrediting forensic service providers performing fingerprint examinations, including problems related to the implementation of vacuum metal deposition in the range of accredited fingerprint visualization techniques.

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Meretukov, Gaysa Mosovich, Vitaliy Viktorovich Pomazanov, and Sergei Ivanovich Gritsaev. "Some issues of using iodine vapour and ozone-air mixture in law-enforcement intelligence operations for finding fingerprints for the purpose of crimes investigation." Полицейская и следственная деятельность, no. 1 (January 2020): 21–25. http://dx.doi.org/10.25136/2409-7810.2020.1.31344.

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The object of research in this article is the activities of a person who had left fingerprints and the activities of a law-enforcement officer using a mobile device generating iodine vapour aimed at the detection of a person suspected of having committed an offence, and the treatment of the detected fingerprint with ozone-air mixture which would decolourise it. A complex of a mobile device for treating fingerprints with iodine vapour, photographic and video equipment, and an ozonator will increase the effectiveness of investigative activities of p[erative units during law-enforcement intelligence operations. The research is based on the dialectical method of cognition, general scientific methods: observation, experiment, comparison, description, measurement, etc., and general logical methods and research techniques. The scientific novelty consists in the creation of a way to use iodine vapour and ozone-air mixture to treat fingerprints, which would help to get the suspect’s fingerprints quickly, without disarranging the evidences, without any traces after the registration of a fingerprint, and without the seizure of the object bearing the fingerprint. Such a mechanism used during law-enforcement intelligence operations would help identify the person suspected of having committed an offence.   

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Drake, Marvin D. "Waveguide hologram fingerprint entry device." Optical Engineering 35, no. 9 (September 1, 1996): 2499. http://dx.doi.org/10.1117/1.600843.

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Lalovic, Komlen, Milan Milosavljevic, Ivan Tot, and Nemanja Macek. "Device for biometric verification of maternity." Serbian Journal of Electrical Engineering 12, no. 3 (2015): 293–302. http://dx.doi.org/10.2298/sjee1503293l.

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Biometry is the scientific discipline and technology that measures and analyzes physiological or behavioral characteristics of people and is widely deployed in modern society security systems. Device for biometric identification of maternity is a dual fingerprint scanner that acquires fingerprint templates of the mother and the child at the very moment of birth, generates unique ID reference, and further guarantees mother-child relationship with that reference. Technical issue that is solved with this work and the proposed device is scanning, processing, and storing encrypted biometric templates with a goal to provide a 100% guarantee maternity for each new born child. Scanning the fingerprints of both mother and the child simultaneously, at moment of birth, and pairing them with unique ID reference removes potential fears occurring from hospital negligence to malicious activities, while the data encryption raises the whole process to the highest level of security and confidentiality. The main contribution of the device that removes the fear that almost every mother has in this period as it provides an answer to the question: ?Is this my baby?? with a 100% guarantee ?It?s certainly yours!?

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Subpratatsavee, Puchong, and Narinwat Pubpruankun. "A Design and Implementation of Attendance System Using Smallest Wireless Fingerprint with Arduino Yún Embedded Board." Applied Mechanics and Materials 752-753 (April 2015): 1057–61. http://dx.doi.org/10.4028/www.scientific.net/amm.752-753.1057.

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The purpose of this research is a design and implementation of a smallest wireless fingerprint device based on Arduino Yún board. This system applies for using in class attendance checking in school or university. The exper-imental of class attendance using wireless fingerprint in this research is examinations in Kasetsart University Siracha Campus, Thailand for case study. All hardware environments of this system-using platform of Arduino Yún board and Ubuntu OS apply with computer program like MySQL, JavaScript, Apache server, and wireless network for building an embedded fingerprint authentication system. Design of a new smallest wireless fingerprint in this research is small and easy to use. It has a LCD screen for show the result of identifying after users scan they fingerprint on it. This system is applying to use in class attendance. When student come in a class he or she scan his fingerprint on our device for checking and authentications. After device receive data from his fingerprint then device send this data to server using wireless network. When server get the data by device from network already, it will send this data to fingerprint authentications program for loading and checking data of fingerprint in database. If his fingerprint data is match one of data in database the server will be sent the name and information of matching fingerprint data back to LCD screen of device and show valid text on the screen and update the status of fingerprint owner to attendance system. If his fingerprint not math in all of data in database, it invalid. This research help an instructor for reduce time for checking student attendance; solve the problem about some student absent but his or her friend fake attendance for him. And in the future this device will be replacing the student ID card

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COLI, PIETRO, GIAN LUCA MARCIALIS, and FABIO ROLI. "FINGERPRINT SILICON REPLICAS: STATIC AND DYNAMIC FEATURES FOR VITALITY DETECTION USING AN OPTICAL CAPTURE DEVICE." International Journal of Image and Graphics 08, no. 04 (October 2008): 495–512. http://dx.doi.org/10.1142/s0219467808003209.

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The automatic vitality detection of a fingerprint has become an important issue in personal verification systems based on this biometric. It has been shown that fake fingerprints made using materials like gelatine or silicon can deceive commonly used sensors. Recently, the extraction of vitality features from fingerprint images has been proposed to address this problem. Among others, static and dynamic features have been separately studied so far, thus their respective merits are not yet clear; especially because reported results were often obtained with different sensors and using small data sets which could have obscured relative merits, due to the potential small sample-size issues. In this paper, we compare some static and dynamic features by experiments on a larger data set and using the same optical sensor for the extraction of both feature sets. We dealt with fingerprint stamps made using liquid silicon rubber. Reported results show the relative merits of static and dynamic features and the performance improvement achievable by using such features together.

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Kokkinis, Akis, Loizos Kanaris, Antonio Liotta, and Stavros Stavrou. "RSS Indoor Localization Based on a Single Access Point." Sensors 19, no. 17 (August 27, 2019): 3711. http://dx.doi.org/10.3390/s19173711.

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This research work investigates how RSS information fusion from a single, multi-antenna access point (AP) can be used to perform device localization in indoor RSS based localization systems. The proposed approach demonstrates that different RSS values can be obtained by carefully modifying each AP antenna orientation and polarization, allowing the generation of unique, low correlation fingerprints, for the area of interest. Each AP antenna can be used to generate a set of fingerprint radiomaps for different antenna orientations and/or polarization. The RSS fingerprints generated from all antennas of the single AP can be then combined to create a multi-layer fingerprint radiomap. In order to select the optimum fingerprint layers in the multilayer radiomap the proposed methodology evaluates the obtained localization accuracy, for each fingerprint radio map combination, for various well-known deterministic and probabilistic algorithms (Weighted k-Nearest-Neighbor—WKNN and Minimum Mean Square Error—MMSE). The optimum candidate multi-layer radiomap is then examined by calculating the correlation level of each fingerprint pair by using the “Tolerance Based—Normal Probability Distribution (TBNPD)” algorithm. Both steps take place during the offline phase, and it is demonstrated that this approach results in selecting the optimum multi-layer fingerprint radiomap combination. The proposed approach can be used to provide localisation services in areas served only by a single AP.

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NOMURA, Toshio. "Friction Measuring Device using Fingerprint Detector." Journal of The Surface Finishing Society of Japan 70, no. 3 (March 1, 2019): 147–50. http://dx.doi.org/10.4139/sfj.70.147.

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Reinders, Stephanie, Li Lin, Wenhao Chen, Yong Guan, and Jennifer Newman. "Score-based likelihood ratios for camera device identification." Electronic Imaging 2020, no. 4 (January 26, 2020): 215–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.4.mwsf-215.

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Many areas of forensics are moving away from the notion of classifying evidence simply as a match or non-match. Instead, some use score-based likelihood ratios (SLR) to quantify the similarity between two pieces of evidence, such as a fingerprint obtained from a crime scene and a fingerprint obtained from a suspect. We apply trace-anchored score-based likelihood ratios to the camera device identification problem. We use photo-response non-uniformity (PRNU) as a camera fingerprint and one minus the normalized correlation as a similarity score. We calculate trace-anchored SLRs for 10,000 images from seven camera devices from the BOSSbase image dataset. We include a comparison between our results the universal detector method.

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Liu, Guiqi, Zhihong Qian, and Xue Wang. "An Indoor WLAN Location Algorithm Based on Fingerprint Database Processing." International Journal of Pattern Recognition and Artificial Intelligence 34, no. 10 (January 8, 2020): 2050026. http://dx.doi.org/10.1142/s0218001420500263.

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Indoor positioning technology based on the Wireless Local Area Network (WLAN) fingerprinting method is becoming a promising choice as for ubiquitous WLAN infrastructure. The technology mainly compares the received signal strength (RSS) of a mobile device with an RSS fingerprint in the fingerprint database, and uses the matching rule to find the closest match as the estimated position of the device. The quality of the fingerprint database construction can directly affect the positioning results. This work proposes a three-stage fingerprint database processing method. In the first stage, the original fingerprint database is divided into several small sub-fingerprint databases according to the specified rules. In the second stage, every sub-fingerprint database is processed using the principal component analysis method to achieve a reduced dimension fingerprint dataset. In the third stage, the k-d tree method is used to process each dimension-reduced sub-fingerprint database for obtaining a hierarchical sub-fingerprint database. In addition, in the online phase, the best bin first (BBF) method is applied to the search engine of sub-fingerprint database to complete the location determination of the device. This method can improve positioning performance through simulation research.

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Jiang, Jehn-Ruey, Hanas Subakti, and Hui-Sung Liang. "Fingerprint Feature Extraction for Indoor Localization." Sensors 21, no. 16 (August 12, 2021): 5434. http://dx.doi.org/10.3390/s21165434.

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This paper proposes a fingerprint-based indoor localization method, named FPFE (fingerprint feature extraction), to locate a target device (TD) whose location is unknown. Bluetooth low energy (BLE) beacon nodes (BNs) are deployed in the localization area to emit beacon packets periodically. The received signal strength indication (RSSI) values of beacon packets sent by various BNs are measured at different reference points (RPs) and saved as RPs’ fingerprints in a database. For the purpose of localization, the TD also obtains its fingerprint by measuring the beacon packet RSSI values for various BNs. FPFE then applies either the autoencoder (AE) or principal component analysis (PCA) to extract fingerprint features. It then measures the similarity between the features of PRs and the TD with the Minkowski distance. Afterwards, k RPs associated with the k smallest Minkowski distances are selected to estimate the TD’s location. Experiments are conducted to evaluate the localization error of FPFE. The experimental results show that FPFE achieves an average error of 0.68 m, which is better than those of other related BLE fingerprint-based indoor localization methods.

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Tian, Qiao, Yun Lin, Xinghao Guo, Jin Wang, Osama AlFarraj, and Amr Tolba. "An Identity Authentication Method of a MIoT Device Based on Radio Frequency (RF) Fingerprint Technology." Sensors 20, no. 4 (February 22, 2020): 1213. http://dx.doi.org/10.3390/s20041213.

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With the continuous development of science and engineering technology, our society has entered the era of the mobile Internet of Things (MIoT). MIoT refers to the combination of advanced manufacturing technologies with the Internet of Things (IoT) to create a flexible digital manufacturing ecosystem. The wireless communication technology in the Internet of Things is a bridge between mobile devices. Therefore, the introduction of machine learning (ML) algorithms into MIoT wireless communication has become a research direction of concern. However, the traditional key-based wireless communication method demonstrates security problems and cannot meet the security requirements of the MIoT. Based on the research on the communication of the physical layer and the support vector data description (SVDD) algorithm, this paper establishes a radio frequency fingerprint (RFF or RF fingerprint) authentication model for a communication device. The communication device in the MIoT is accurately and efficiently identified by extracting the radio frequency fingerprint of the communication signal. In the simulation experiment, this paper introduces the neighborhood component analysis (NCA) method and the SVDD method to establish a communication device authentication model. At a signal-to-noise ratio (SNR) of 15 dB, the authentic devices authentication success rate (ASR) and the rogue devices detection success rate (RSR) are both 90%.

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Kim, Jae-Hoon, Kyoung Sik Min, and Woon-Young Yeo. "A Design of Irregular Grid Map for Large-Scale Wi-Fi LAN Fingerprint Positioning Systems." Scientific World Journal 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/203419.

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The rapid growth of mobile communication and the proliferation of smartphones have drawn significant attention to location-based services (LBSs). One of the most important factors in the vitalization of LBSs is the accurate position estimation of a mobile device. The Wi-Fi positioning system (WPS) is a new positioning method that measures received signal strength indication (RSSI) data from all Wi-Fi access points (APs) and stores them in a large database as a form of radio fingerprint map. Because of the millions of APs in urban areas, radio fingerprints are seriously contaminated and confused. Moreover, the algorithmic advances for positioning face computational limitation. Therefore, we present a novel irregular grid structure and data analytics for efficient fingerprint map management. The usefulness of the proposed methodology is presented using the actual radio fingerprint measurements taken throughout Seoul, Korea.

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Furman, Susanne M., Mary Theofanos, John Libert, John Grantham, and Brian Stanton. "Mobile Phone Fingerprinting: A Picture is Worth a Thousand Words." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, no. 1 (September 2018): 1326–30. http://dx.doi.org/10.1177/1541931218621303.

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The United States Department of Homeland Security (DHS) relies on the use of biometrics as an important component of its mission to keep America safe. Risks are involved with the current systems that use contact fingerprint technology such as the transmission of pathogens by contacting the scanner. Touchless systems address this risk but also introduce new challenges. Sixty National Institute of Standards and Technology (NIST) employees participated in the study to determine the usability of three mobile phone devices as well as the image quality of the resulting fingerprint images. All participants had previous experience with capturing their prints using a contact device and as a result tried to touch the screen on the mobile phone to capture their fingerprints. All the participants had mobile phones and were aware of the phone’s features including a camera and capture process for the mobile phone devices involved using the phone’s camera to take a photo of fingerprints. We believe that participants did not equate the capture process to taking a photo of their fingers and were using an existing mental model for capturing their fingerprints and as a result they touched the phone’s glass screen. The devices provided little if any or often somewhat confusing instructions to assist the user and little if any feedback regarding the success of the capture. To study the image quality of the prints, we assisted the participants in collecting a set of prints using both the mobile phone devices and the contact field devices. We compared the image quality and the interoperability of the contactless captures with the legacy contact captures. Currently the image quality and interoperability is less than desirable.

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Lalovic, Komlen. "Patent overview: Device for fingerprint identity guarantee." Vojnotehnički glasnik 66, no. 2 (2018): 366–79. http://dx.doi.org/10.5937/vojtehg66-15868.

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Lin, Jhe-Syuan, and Wen-Shing Sun. "A Hidden Fingerprint Device on an Opaque Display Panel." Applied Sciences 10, no. 6 (March 23, 2020): 2188. http://dx.doi.org/10.3390/app10062188.

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In recent years, fingerprint recognition has become more and more widely used in mobile phones. A fingerprint recognition device hidden under an opaque display panel designed based on a waveguide and frustrated total internal reflection (FTIR) is proposed and demonstrated herein. In order to meet the demand for a high screen ratio for mobile phone displays, we use a symmetrical zoom-in and zoom-out coupler design. With this comprehensive coupler and waveguide design, not only can fingerprint recognition be achieved using an opaque display panel, but it also meets the appearance requirements for a mobile phone with a high screen ratio.

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Dari, Yohanes Erwin, Suyoto Suyoto Suyoto, and Pranowo Pranowo Pranowo. "CAPTURE: A Mobile Based Indoor Positioning System using Wireless Indoor Positioning System." International Journal of Interactive Mobile Technologies (iJIM) 12, no. 1 (January 23, 2018): 61. http://dx.doi.org/10.3991/ijim.v12i1.7632.

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The existence of mobile devices as a location pointing device using Global Positioning System (GPS) is a very common thing nowadays. The use of GPS as a tool to determine the location of course has a shortage when used indoors. Therefore, the used of indoor location-based services in a room that leverages the use of Access Point (AP) is very important. By using the information of the Received Signal Strength (RSS) obtained from AP, then the location of the device can be determined without the need to use GPS. This technique is called the location fingerprint technique using the characteristics of received RSS’s fingerprint, then use it to determine the position. To get a more accurate position then authors used the K-Nearest Neighbor (KNN) method. KNN will use some of the data that obtained from some AP to assist in positioning the device. This solution of course would be able to determine the position of the devices in a storied building.

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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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Han, Jinho. "Fingerprint Authentication Schemes for Mobile Devices." International Journal of Electrical and Computer Engineering (IJECE) 5, no. 3 (June 1, 2015): 579. http://dx.doi.org/10.11591/ijece.v5i3.pp579-585.

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In certain applications, fingerprint authentication systems require templates to be stored in databases. The possible leakage of these fingerprint templates can lead to serious security and privacy threats. Therefore, with the frequent use of fingerprint authentication on mobile devices, it has become increasingly important to keep fingerprint data safe. Due to rapid developments in optical equipment, biometric systems are now able to gain the same biometric images repeatedly, so strong features can be selected with precision. Strong features refer to high-quality features which can be easily distinguished from other features in biometric raw images. In this paper, we introduce an algorithm that identifies these strong features with certain probability from a given fingerprint image. Once values are extracted from these features, they are used as the authentication data. Using the geometric information of these strong features, a cancelable fingerprint template can be produced, and the process of extracting values and geometric information is further explained. Because this is a light-weight authentication scheme, this template has practical usage for low performance mobile devices. Finally, we demonstrate that our proposed schemes are secure and that the user’s biometric raw data of the fingerprint are safe, even when the mobile device is lost or stolen.

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Chaudhary, Sumit, Monika Garg, and Neha Singh. "IMPLEMENTATION OF FINGER TOKEN AUTHENTICATION TECHNIQUE USING ARTIFICIAL INTELLIGENCE APPROACH IN NTT MICROSYSTEMS." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 3, no. 3 (November 30, 2012): 428–32. http://dx.doi.org/10.24297/ijct.v3i3a.2950.

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Personal authentication that correctly identifies valid users in an indispensable security technology for enabling people to enjoy the access to data services with a sense of confidence and assurance. Passwords have been extensively used to identify authorized users in the past, but passwords alone are vulnerable because people tend to choose weak password relating to some aspect of them (e.g. birthday, phone number, family name) that can be guessed. This has led to growing interest in biometric authentication using fingerprints that make it possible to identify personal authentication correctly. It eliminates problems of forgotten passwords or lost cards and is currently becoming more popular for convenient and secure authentication. NTT Microsystems is a new and exclusive technology that overcomes the limitations of previous systems and sets a new standard for compact, reliable and low-cost fingerprint authentication. NTT laboratories have developed Finger Token, a portable fingerprint identification device that substitutes a fingerprint instead of password for authentication

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Tang, Kai, Aijia Liu, Wei Wang, Pengfei Li, and Xi Chen. "A Novel Fingerprint Sensing Technology Based on Electrostatic Imaging." Sensors 18, no. 9 (September 12, 2018): 3050. http://dx.doi.org/10.3390/s18093050.

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In this paper, we propose a new fingerprint sensing technology based on electrostatic imaging, which can greatly improve fingerprint sensing distance. This can solve the problem of the existing capacitive fingerprint identification device being easy to damage due to limited detection distance and a protective coating that is too thin. The fingerprint recognition sensor can also be placed under a glass screen to meet the needs of the full screen design of the mobile phone. In this paper, the electric field distribution around the fingerprint is analyzed. The electrostatic imaging sensor design is carried out based on the electrostatic detection principle and MEMS (micro-electro-mechanical system) technology. The MEMS electrostatic imaging array, analog, and digital signal processing circuit structure are designed. Simulation and testing are carried out as well. According to the simulation and prototype test device test results, it is confirmed that our proposed electrostatic imaging-based fingerprint sensing technology can increase fingerprint recognition distance by 46% compared to the existing capacitive fingerprint sensing technology. A distance of more than 439 μm is reached.

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Lee, Sanghoon, and Ik Rae Jeong. "A Cancelable Template for the Low-Quality Fingerprints from Wearable Devices." Security and Communication Networks 2019 (June 2, 2019): 1–8. http://dx.doi.org/10.1155/2019/4202671.

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Biometric authentication in wearable devices is different from the common biometric authentication systems. First of all, sensitive information such as fingerprint and iris of a user is stored in a wearable device owned by the user rather than being stored in a remote database. Wearable devices are portable, and there is a risk that the devices might be lost or stolen. In addition, the quality of the extracted image from the wearable devices is lower than that of the common biometric acquisition sensor. In the paper, we propose a novel cancelable fingerprint template which is irreversible to the original biometrics and has excellent accuracy even in low quality images.

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Bao, Ya Ping, Li Liu, Yuan Wang, and Qian Song. "Fingerprint Identification System Based on DSP." Advanced Materials Research 468-471 (February 2012): 920–23. http://dx.doi.org/10.4028/www.scientific.net/amr.468-471.920.

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This paper introduced a fast fingerprint identification system based on TMS320VC5416 DSP chip and MBF200 solidity fingerprint sensor. It precipitates fingerprint identification device developing into the direction of miniaturization, embedded and automatic.It recommends fingerprint identification system hardware and software design and the main system processing flow, aim at fingerprint identification arithmetic, the influence of system operation speed is being researched at the same time. High-speed data acquisition system is been built in order to achieve a DSP fingerprint identification system with high efficiency and low cost.

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Tolentino, Efren Victor Jr N. "Design of an Automobile Anti-Theft Device Using Sequential Fingerprint and Voice Biometrics." Journal of Advanced Research in Dynamical and Control Systems 12, no. 01-Special Issue (February 13, 2020): 170–76. http://dx.doi.org/10.5373/jardcs/v12sp1/20201060.

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Mohammed and Yassin. "Efficient and Flexible Multi-Factor Authentication Protocol Based on Fuzzy Extractor of Administrator’s Fingerprint and Smart Mobile Device." Cryptography 3, no. 3 (September 9, 2019): 24. http://dx.doi.org/10.3390/cryptography3030024.

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In an era of tremendous development in information technology and the Internet of Things (IoT), security plays a key role in safety devices connected with the Internet. Authentication is vital in the security field, and to achieve a strong authentication scheme, there are several systems using a Multi-Factor Authentication (MFA) scheme based on a smart card, token, and biometric. However, these schemes have suffered from the extra cost; lost, stolen or broken factor, and malicious attacks. In this paper, we design an MFA protocol to be the authenticated administrator of IoT’s devices. The main components of our protocol are a smart mobile device and the fuzzy extractor of the administrator’s fingerprint. The information of the authenticated user is stored in an anomalous manner in mobile devices and servers to resist well-known attacks, and, as a result, the attacker fails to authenticate the system when they obtain a mobile device or password. Our work overcomes the above-mentioned issues and does not require extra cost for a fingerprint device. By using the AVISPA tool to analysis protocol security, the results are good and safe against known attacks.

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Zhang Mingwang, 张明旺, 肖延辉 Xiao Yanhui, 田华伟 Tian Huawei, 郝昕泽 Hao Xinze, and 李丽华 Li Lihua. "Review of Device Fingerprint Extraction Techniques in Image." Laser & Optoelectronics Progress 57, no. 22 (2020): 220003. http://dx.doi.org/10.3788/lop57.220003.

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Sebastian, Alycia, and K. Siva Sankar. "A secure and reliable method to protect usb data." APTIKOM Journal on Computer Science and Information Technologies 4, no. 2 (January 27, 2020): 57–60. http://dx.doi.org/10.34306/csit.v4i2.91.

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With technology advancement people have started using different type of memory devices for storing dataand keeping it secure has become concern in today’s world. Universal Serial Bus (USB) flash drives are leadingportable storage device for storage and easy transfer of data from one computer to another. The usage of USB hasgrown exponentially and without security the data on the disk is at risk. Nowadays USB manufacturers offer passwordprotection and fingerprint authentication to secure the USB data. In this paper, USB is devised as a highly securedportable boot medium with fingerprint authentication to secure the data.

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32

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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33

Shojania, S., M. E. McComb, R. D. Oleschuk, H. Perreault, H. D. Gesser, and A. Chow. "Article." Canadian Journal of Chemistry 77, no. 11 (November 1, 1999): 1716–27. http://dx.doi.org/10.1139/v99-142.

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An alternative sampling technique for fingerprint analysis of complex mixtures of petroleum-based products is presented. Fingerprint chromatograms of the volatile organic compounds (VOCs) for class 0-5 accelerants can be readily obtained using the recently developed inside needle capillary adsorption trap (INCAT) device. The concentration of VOCs from the static headspace of these complex mixtures, onto the adsorbing carbon coating of the INCAT device, avoids some problems associated with conventional headspace gas chromatography (HS-GC). The INCAT sampling method is a solventless extraction technique in which the analytes adsorbed inside the device are thermally desorbed inside the heated injection port of a gas chromatograph (GC), or a gas chromatograph coupled with a mass spectrometer (GC-MS). The presented method of active sampling with the INCAT device was used to obtain fingerprint chromatograms of the headspace of various gasolines, paint thinners, and lighter fluids. The static headspace chromatograms, from active sampling with the INCAT device, were compared with direct liquid injection of the samples. The INCAT chromatograms showed preferential adsorption of aromatic compounds over lighter, more volatile, but less polar compounds. Each class of the accelerant can be positively identified from the fingerprint chromatogram using only a few characteristic peaks. In addition, the ability to detect these volatile components of gasoline in aqueous samples at environmentally significant levels was also investigated.Key words: VOC, fingerprinting, INCAT, petroleum, headspace GC.

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34

Sebastian, Alycia, and K. Siva Sankar. "A Secure and Reliable Method to Protect USB Data." APTIKOM Journal on Computer Science and Information Technologies 4, no. 2 (July 1, 2019): 57–60. http://dx.doi.org/10.11591/aptikom.j.csit.34.

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With technology advancement people have started using different type of memory devices for storing data and keeping it secure has become concern in today’s world. Universal Serial Bus (USB) flash drives are leading portable storage device for storage and easy transfer of data from one computer to another. The usage of USB has grown exponentially and without security the data on the disk is at risk. Nowadays USB manufacturers offer password protection and fingerprint authentication to secure the USB data. In this paper, USB is devised as a highly secured portable boot medium with fingerprint authentication to secure the data.

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35

Johnson, Anju P., Hussain Al-Aqrabi, and Richard Hill. "Bio-Inspired Approaches to Safety and Security in IoT-Enabled Cyber-Physical Systems." Sensors 20, no. 3 (February 5, 2020): 844. http://dx.doi.org/10.3390/s20030844.

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Internet of Things (IoT) and Cyber-Physical Systems (CPS) have profoundly influenced the way individuals and enterprises interact with the world. Although attacks on IoT devices are becoming more commonplace, security metrics often focus on software, network, and cloud security. For CPS systems employed in IoT applications, the implementation of hardware security is crucial. The identity of electronic circuits measured in terms of device parameters serves as a fingerprint. Estimating the parameters of this fingerprint assists the identification and prevention of Trojan attacks in a CPS. We demonstrate a bio-inspired approach for hardware Trojan detection using unsupervised learning methods. The bio-inspired principles of pattern identification use a Spiking Neural Network (SNN), and glial cells form the basis of this work. When hardware device parameters are in an acceptable range, the design produces a stable firing pattern. When unbalanced, the firing rate reduces to zero, indicating the presence of a Trojan. This network is tunable to accommodate natural variations in device parameters and to avoid false triggering of Trojan alerts. The tolerance is tuned using bio-inspired principles for various security requirements, such as forming high-alert systems for safety-critical missions. The Trojan detection circuit is resilient to a range of faults and attacks, both intentional and unintentional. Also, we devise a design-for-trust architecture by developing a bio-inspired device-locking mechanism. The proposed architecture is implemented on a Xilinx Artix-7 Field Programmable Gate Array (FPGA) device. Results demonstrate the suitability of the proposal for resource-constrained environments with minimal hardware and power dissipation profiles. The design is tested with a wide range of device parameters to demonstrate the effectiveness of Trojan detection. This work serves as a new approach to enable secure CPSs and to employ bio-inspired unsupervised machine intelligence.

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36

Nakayama, Keizo. "Optical security device providing fingerprint and designed pattern indicator using fingerprint texture in liquid crystal." Optical Engineering 51, no. 4 (April 20, 2012): 040506. http://dx.doi.org/10.1117/1.oe.51.4.040506.

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37

Zhang, Liye, Xiaoliang Meng, and Chao Fang. "Linear Regression Algorithm against Device Diversity for the WLAN Indoor Localization System." Wireless Communications and Mobile Computing 2021 (April 8, 2021): 1–15. http://dx.doi.org/10.1155/2021/5530396.

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Recent years have witnessed a growing interest in using WLAN fingerprint-based methods for the indoor localization system because of their cost-effectiveness and availability compared to other localization systems. In this system, the received signal strength (RSS) values are measured as the fingerprint from the access points (AP) at each reference point (RP) in the offline phase. However, signal strength variations across diverse devices become a major problem in this system, especially in the crowdsourcing-based localization system. In this paper, the device diversity problem and the adverse effects caused by this problem are analyzed firstly. Then, the intrinsic relationship between different RSS values collected by different devices is mined by the linear regression (LR) algorithm. Based on the analysis, the LR algorithm is proposed to create a unique radio map in the offline phase and precisely estimate the user’s location in the online phase. After applying the LR algorithm in the crowdsourcing systems, the device diversity problem is solved effectively. Finally, we verify the LR algorithm using the theoretical study of the probability of error detection. Experimental results in a typical office building show that the proposed method results in a higher reliability and localization accuracy.

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38

Gulyás, Gábor György, Gergely Acs, and Claude Castelluccia. "Near-Optimal Fingerprinting with Constraints." Proceedings on Privacy Enhancing Technologies 2016, no. 4 (October 1, 2016): 470–87. http://dx.doi.org/10.1515/popets-2016-0051.

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Abstract Several recent studies have demonstrated that people show large behavioural uniqueness. This has serious privacy implications as most individuals become increasingly re-identifiable in large datasets or can be tracked, while they are browsing the web, using only a couple of their attributes, called as their fingerprints. Often, the success of these attacks depends on explicit constraints on the number of attributes learnable about individuals, i.e., the size of their fingerprints. These constraints can be budget as well as technical constraints imposed by the data holder. For instance, Apple restricts the number of applications that can be called by another application on iOS in order to mitigate the potential privacy threats of leaking the list of installed applications on a device. In this work, we address the problem of identifying the attributes (e.g., smartphone applications) that can serve as a fingerprint of users given constraints on the size of the fingerprint. We give the best fingerprinting algorithms in general, and evaluate their effectiveness on several real-world datasets. Our results show that current privacy guards limiting the number of attributes that can be queried about individuals is insufficient to mitigate their potential privacy risks in many practical cases.

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Ghouzali, Sanaa, Maryam Lafkih, Wadood Abdul, Mounia Mikram, Mohammed El Haziti, and Driss Aboutajdine. "Trace Attack against Biometric Mobile Applications." Mobile Information Systems 2016 (2016): 1–15. http://dx.doi.org/10.1155/2016/2065948.

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With the exponential increase in the dependence on mobile devices in everyday life, there is a growing concern related to privacy and security issues in the Gulf countries; therefore, it is imperative that security threats should be analyzed in detail. Mobile devices store enormous amounts of personal and financial information, unfortunately without any security. In order to secure mobile devices against different threats, biometrics has been applied and shown to be effective. However, biometric mobile applications are also vulnerable to several types of attacks that can decrease their security. Biometric information itself is considered sensitive data; for example, fingerprints can leave traces in touched objects and facial images can be captured everywhere or accessed by the attacker if the facial image is stored in the mobile device (lost or stolen). Hence, an attacker can easily forge the identity of a legitimate user and access data on a device. In this paper, the effects of a trace attack on the sensitivity of biometric mobile applications are investigated in terms of security and user privacy. Experimental results carried out on facial and fingerprint mobile authentication applications using different databases have shown that these mobile applications are vulnerable to the proposed attack, which poses a serious threat to the overall system security and user privacy.

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40

Schaumont, P., D. Hwang, and I. Verbauwhede. "Platform-based design for an embedded-fingerprint-authentication device." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 24, no. 12 (December 2005): 1929–36. http://dx.doi.org/10.1109/tcad.2005.853709.

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41

Mager, Brad, Philip Lundrigan, and Neal Patwari. "Fingerprint-Based Device-Free Localization Performance in Changing Environments." IEEE Journal on Selected Areas in Communications 33, no. 11 (November 2015): 2429–38. http://dx.doi.org/10.1109/jsac.2015.2430515.

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42

Adam, Lisanne, and Greg Barns. "Digital strip searches in Australia: A threat to the privilege against self-incrimination." Alternative Law Journal 45, no. 3 (May 11, 2020): 222–27. http://dx.doi.org/10.1177/1037969x20923073.

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Law enforcement has experienced difficulties retrieving information stored on the mobile devices of suspects. Over the last years, a number of Australian jurisdictions enacted legislation that allows police officers to compel an individual to unlock their device (such as providing a PIN or fingerprint to unlock the device). Non-compliance with these legislative provisions is punishable by imprisonment. The refusal by suspects to comply with an order to unlock their devices has been addressed in a number of Australian courts. In this article, the authors will discuss this legislative activity and the courts’ responses in light of the privilege against self-incrimination.

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Huang, Wenbin, Cong-long Yuan, Dong Shen, and Zhi-gang Zheng. "Dynamically manipulated lasing enabled by a reconfigured fingerprint texture of a cholesteric self-organized superstructure." Journal of Materials Chemistry C 5, no. 28 (2017): 6923–28. http://dx.doi.org/10.1039/c7tc02076g.

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Laser emission based on an electrically reconfigured fingerprint texture of a cholesteric liquid crystal helical superstructure is achieved by judiciously designing the composition of the device material and the device structure.

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44

Dang, Xiaochao, Xuhao Tang, Zhanjun Hao, and Yang Liu. "A Device-Free Indoor Localization Method Using CSI with Wi-Fi Signals." Sensors 19, no. 14 (July 23, 2019): 3233. http://dx.doi.org/10.3390/s19143233.

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Amid the ever-accelerated development of wireless communication technology, we have become increasingly demanding for location-based service; thus, passive indoor positioning has gained widespread attention. Channel State Information (CSI), as it can provide more detailed and fine-grained information, has been followed by researchers. Existing indoor positioning methods, however, are vulnerable to the environment and thus fail to fully reflect all the position features, due to limited accuracy of the fingerprint. As a solution, a CSI-based passive indoor positioning method was proposed, Wavelet Domain Denoising (WDD) was adopted to deal with the collected CSI amplitude, and the CSI phase information was unwound and transformed linearly in the offline phase. The post-processed amplitude and phase were taken as fingerprint data to build a fingerprint database, correlating with reference point position information. Results of experimental data analyzed under two different environments show that the present method boasts lower positioning error and higher stability than similar methods and can offer decimeter-level positioning accuracy.

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45

Guo, Ruolin, Danyang Qin, Min Zhao, and Xinxin Wang. "Indoor Radio Map Construction Based on Position Adjustment and Equipment Calibration." Sensors 20, no. 10 (May 15, 2020): 2818. http://dx.doi.org/10.3390/s20102818.

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The crowdsourcing-based wireless local area network (WLAN) indoor localization system has been widely promoted for the effective reduction of the workload from the offline phase data collection while constructing radio maps. Aiming at the problem of the diverse terminal devices and the inaccurate location annotation of the crowdsourced samples, which will result in the construction of the wrong radio map, an effective indoor radio map construction scheme (RMPAEC) is proposed based on position adjustment and equipment calibration. The RMPAEC consists of three main modules: terminal equipment calibration, pedestrian dead reckoning (PDR) estimated position adjustment, and fingerprint amendment. A position adjustment algorithm based on selective particle filtering is used by RMPAEC to reduce the cumulative error in PDR tracking. Moreover, an inter-device calibration algorithm is put forward based on receiver pattern analysis to obtain a device-independent grid fingerprint. The experimental results demonstrate that the proposed solution achieves higher localization accuracy than the peer schemes, and it possesses good effectiveness at the same time.

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Gao, Zhang, Xiao, and Li. "Kullback–Leibler Divergence Based Probabilistic Approach for Device-Free Localization Using Channel State Information." Sensors 19, no. 21 (November 3, 2019): 4783. http://dx.doi.org/10.3390/s19214783.

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Recently, people have become more and more interested in wireless sensing applications, among which indoor localization is one of the most attractive. Generally, indoor localization can be classified as device-based and device-free localization (DFL). The former requires a target to carry certain devices or sensors to assist the localization process, whereas the latter has no such requirement, which merely requires the wireless network to be deployed around the environment to sense the target, rendering it much more challenging. Channel State Information (CSI)—a kind of information collected in the physical layer—is composed of multiple subcarriers, boasting highly fined granularity, which has gradually become a focus of indoor localization applications. In this paper, we propose an approach to performing DFL tasks by exploiting the uncertainty of CSI. We respectively utilize the CSI amplitudes and phases of multiple communication links to construct fingerprints, each of which is a set of multivariate Gaussian distributions that reflect the uncertainty information of CSI. Additionally, we propose a kind of combined fingerprints to simultaneously utilize the CSI amplitudes and phases, hoping to improve localization accuracy. Then, we adopt a Kullback–Leibler divergence (KL-divergence) based kernel function to calculate the probabilities that a testing fingerprint belongs to all the reference locations. Next, to localize the target, we utilize the computed probabilities as weights to average the reference locations. Experimental results show that the proposed approach, whatever type of fingerprints is used, outperforms the existing Pilot and Nuzzer systems in two typical indoor environments. We conduct extensive experiments to explore the effects of different parameters on localization performance, and the results demonstrate the efficiency of the proposed approach.

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Sohn, Ho-Jin, Seung-Won Oh, Yeongyu Choi, Seong-Min Ji, and Tae-Hoon Yoon. "A Switchable Cholesteric Phase Grating with a Low Operating Voltage." Crystals 11, no. 2 (January 25, 2021): 100. http://dx.doi.org/10.3390/cryst11020100.

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We demonstrate a simple fabrication method of a uniform-lying-helix (ULH) cholesteric liquid crystal (ChLC) cell for phase grating device applications. To utilize a stable ULH state, we set the pitches of ChLCs as half of the cell gap to obtain the fingerprint texture with homeotropic anchoring. With the given grating period, the diffraction efficiency of the ULH cell can be maximized by optimizing the cell gap. We found that the fabricated grating device can provide a large diffraction angle of 10° and a low operating voltage of 3 V with a diffraction efficiency of 30%. We expect potential applications of the device for diffraction optics, optical interconnects, and beam steering devices.

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48

Acosta, Nelson, Juan Toloza, and Carlos Kornuta. "Fingerprint Database Variations for WiFi Positioning." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 11, no. 10 (December 5, 2013): 3101–7. http://dx.doi.org/10.24297/ijct.v11i10.2979.

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Indoor positioning systems calculate the position of a mobile device (MD) in an enclosed environment with relative precision. Most systems use WiFi infrastructure and several positioning techniques, where the most commonly used parameter is RSSI (Received Signal Strength Indicator). In this paper, we analyze the fingerprinting technique to calculate the error window obtained with the Euclidian distance as main metric. Build variations are presented for the Fingerprint database analyzing various statistical values to compare the precision achieved with different indicators.

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Avram, Camelia, Jose Machado, and Adina Aştilean. "Hardware Passwords Manager Based on Biometric Authentication." Engineering Proceedings 6, no. 1 (May 17, 2021): 31. http://dx.doi.org/10.3390/i3s2021dresden-10085.

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This paper presents a portable passwords manager which has a two-stage biometric-based access procedure. Data security using biometric methods was chosen as a variant of reduced complexity but was very effective in preventing cyber theft. The implementation of biometrics for the purpose of identification in high-security systems has become essential with the evolution of technology and the spike in identity theft. Unlike passwords or IDs, a biometric feature is an identifier that cannot be lost, stolen, or replicated, which provides biometric authentication systems with an increased level of security. During the first accessing step, the 3DPassManager portable device measures the heartbeat and uses fingerprint and iris features to realize a unique biometric-based authentication. While the specific characteristics of fingerprint and iris features are integrated to ensure that the person using the device is the rightful owner, the pulse is utilized to verify if previously acquired static images are not used. During the second accessing step, a password is generated based on fingerprint details, valid only for a small-time interval. The fingerprint is stored in a secret key with a 1024-bit length. Once access is allowed, the passwords are made available through an extension installed on the web browser. The device is the size of a cigarette pack and communicates with the PC by scanning a QR code. It is safe and was previously tested for dictionary and brute force attacks.

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Robyns, Pieter, Bram Bonné, Peter Quax, and Wim Lamotte. "Noncooperative 802.11 MAC Layer Fingerprinting and Tracking of Mobile Devices." Security and Communication Networks 2017 (2017): 1–21. http://dx.doi.org/10.1155/2017/6235484.

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We present two novel noncooperative MAC layer fingerprinting and tracking techniques for Wi-Fi (802.11) enabled mobile devices. Our first technique demonstrates how a per-bit entropy analysis of a single captured frame allows an adversary to construct a fingerprint of the transmitter that is 80.0 to 67.6 percent unique for 50 to 100 observed devices and 33.0 to 15.1 percent unique for 1,000 to 10,000 observed devices. We show how existing mitigation strategies such as MAC address randomization can be circumvented using only this fingerprint and temporal information. Our second technique leverages peer-to-peer 802.11u Generic Advertisement Service (GAS) requests and 802.11e Block Acknowledgement (BA) requests to instigate transmissions on demand from devices that support these protocols. We validate these techniques using two datasets, one of which was recorded at a music festival containing 28,048 unique devices and the other at our research lab containing 138 unique devices. Finally, we discuss a number of countermeasures that can be put in place by mobile device vendors in order to prevent noncooperative tracking through the discussed techniques.

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Journal articles on the topic 'Device fingerprint'

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