Analogs of Ridge Skin and Papillary Patterns in the Nature and the Significance of Their Study for Forensic Science and Forensic Examination

Patterns similar to the papillary patterns of human fingers, palms, and soles can be found in living and inanimate nature. Studying such patterns and the structure of the ridged skin of humans and primates in comparison with similar formations on other objects is necessary for forensic science, forensic traceology, fingerprinting, and biometric identification. The article analyzes the history of the study of the ridged skin of humans, primates, and other animals by forensic scientists, zoologists, anthropologists, and representatives of other sciences.The author proposes systemizing and classifying the information about the analogs of papillary patterns and ridged skin on such grounds as the genus and type of carrier objects, relief structure, degree of comparability with the papillary pattern of human hands and soles.The article presents the most indicative varieties of analogs of papillary patterns in mammals, birds, fish, insects, corals, plants, and fungi. The author has studied and systemized structural features of the striped pattern of the skin of tigers and zebras, crests and stripes in corals, stripes and ridged patterns in fish. The data obtained on ridge formations, which are similar in structure and shape to the papillary patterns of human fingers and palms, will help to avoid expert errors during fingerprinting examination or erroneous placement of images of such formations in forensic databases.Knowledge of the structural features and properties of striped patterns of skins of specially protected wild animals, as well as the crest surface of paleontological museum objects, should be used for their identification by photo and video images in cases of embezzlement, smuggling, illegal hunting, and illegal trafficking.

Multimodal Biometric Authentication for Smartphones

Smartphones have become a crucial way of storing sensitive information; therefore, the user's privacy needs to be highly secured. This can be accomplished by employing the most reliable and accurate biometric identification system available currently which is, Eye recognition. However, the unimodal eye biometric system is not able to qualify the level of acceptability, speed, and reliability needed. There are other limitations such as constrained authentication in real time applications due to noise in sensed data, spoof attacks, data quality, lack of distinctiveness, restricted amount of freedom, lack of universality and other factors. Therefore, multimodal biometric systems have come into existence in order to increase security as well as to achieve better performance.[1] This paper provides an overview of different multimodal biometric (multibiometric) systems for smartphones being employed till now and also proposes a multimodal biometric system which can possibly overcome the limitations of the current biometric systems. Keywords: Biometrics, Unimodal, Multimodal, Fusion, Multibiometric Systems

Building a classifier in the personality recognition system based on eye tracking data

Identification systems that use biometric characteristics to solve the problem of access to information systems are becoming more common. The article proposes a new method of biometric identification of computer systems users, based on the determination of the integral Volterra model of the human oculo-motor system (OMS) according to experimental research "input-output" using innovative eye tracking technology. With the help of the Tobii Pro TX300 eye tracker, the data of OMC responses to test visual stimuli were obtained, displayed as bright dots on the computer screen at different distances from the start position in the "horizontal" direction. Based on the data obtained, the transition functions of the first, second and third orders of the OMS for two people were determined. To construct a personality classifier, the informativeness of the proposed heuristic features, determined on the basis of the transition functions in terms of the probability of correct recognition (PCR), is investigated. Pairs of features are established that are resistant to computational errors and have a high PCR value - in the range 0.92 - 0.97. Fig.: 8. Table: 5. Bibliography: 30 items. Key words: biometric identification, personality recognition, Volterra model, oculo-motor system, eye tracking technology, informativeness of features, classification.

Leakage or Identification

The convenience of laptops brings with it the risk of information leakage, and conventional security systems based on the password or the explicit biometric do little to alleviate this problem. Biometric identification based on anatomical features provides far stronger security; however, a lack of suitable sensors on laptops limits the applicability of this technology. In this paper, we developed a behavior-irrelevant user identification system applicable to laptops with a metal casing. The proposed scheme, referred to as LeakPrint, is based on leakage current, wherein the system uses an earphone to capture current leaking through the body and then transmits the corresponding signal to a server for identification. The user identification is achieved via denoising, dimension reduction, and feature extraction. Compared to other biometric identification methods, the proposed system is less dependent on external hardware and more robust to environmental noise. The experiments in real-world environments demonstrated that LeakPrint can verify user identity with high accuracy (93.6%), while providing effective defense against replay attacks (96.5%) and mimicry attacks (90.9%).

FEATURES OF USING A TWO-DIMENSIONAL BARCODE FOR CLASSIFYING THE PERSONALITY OF A PRISONER: A COMPARATIVE ANALYSIS OF THE APPLICATION IN THE RUSSIAN FEDERATION AND FOREIGN COUNTRIES

В настоящее время набирает популярность использование на территории организаций, аэропортов и в других сферах, в том числе в исправительных учреждениях Российской Федерации (далее - ИУ РФ) и зарубежных стран двухмерного штрих-кода для передачи информации. Безусловно, применение данного штрих-кода в биометрической идентификации личности имеет огромное преимущество перед осуществлением аналогичной деятельности непосредственно сотрудниками уголовно-исполнительной системы Российской Федерации (далее - УИС), которое выражается в усиленном контроле пропуска и безопасности сотрудников и осужденных от несанкционированного прохода посторонних лиц. Биометрическая идентификация личности производится путем сканирования сетчатки глаза, отпечатков пальцев, сканирования биометрии лица, измерения температуры тела и распознавания голоса. Однако даже такая современная система имеет определенные недостатки, выявленные специалистами в сфере инженерно-технического обеспечения, которым посвящен ряд научных работ, рассмотренных в данной статье. Также авторами проанализированы основные разновидности 2D-кодов, такие как Stackedlinear и Matrixcode. Отмечается, что 2D-кодировка применяется во многих отраслях: при производстве, транспортировке грузов, идентификации личности, шифровки данных документов и отчетов, проведении инвентаризации. Nowadays using a two-dimensional barcode for transmitting information becomes more popular in the territory of organizations, airports, and in other spheres such as correctional facilities of the Russian Federation (hereinafter - CF RF) and in abroad counties. Undoubtedly, the application of this barcode in biomedical identification of personality has a huge advantage over similar activities, which has been realized by penal officers (hereinafter - FPS ). This dignity includes enhanced control and safety of employees and convicts from an unauthorized passage of unauthorized persons. Biometric identification of personality conducted by retinal scan, fingerprint scan, facial biometrics scan, body temperature measurement, and voice recognition. However, even such a system has several disadvantages, which were identified by engendering specialists. Lots of scientific works are dedicated to these flaws, which we are going to consider in the article. Also the main varieties of 2D codes were analysed in this article, such as Stackedlinear and Matrixcode. It was found out that 2D coding is used in many different industries: in the process of production, transportation of goods, person identification, encryption of these documents and reports, inventory.

Hough Transform for Distinctive Edge Detection to Images in Fingerprint Recognition Matching Transformation

Biometric Identification is a globally renowned procedure, which has been utilised to achieve a successful and accurate level of identification. In the sea of biometrics, fingerprints are deemed more popular when it comes to verification. This results from the presence of the ridges on the fingerprints that are completely exclusive to each individual. Besides that, fingerprints are expansively employed to ascertain and authenticate people individually. Therefore, this study had proposed to employ distinctive Edge Detection techniques together with the Hough Transform to match the images of the fingerprints in a fingerprint matching system. The Hough Transform is a superior procedure carried out to get an accurate series of finer points or lines. The finer points or lines would then distinguish the fingerprints. Nevertheless, it was still a challenge to extract finer points or lines from the fingerprints under uninhibited conditions. Therefore, this paper was organised based on four distinctive steps. First, different Edge Detection operators were employed to perform the fingerprint matching algorithm. Next, the fingerprint matching algorithm was applied twice to the same Edge Detection operators. Thirdly, the Edge Detection operators had been substituted with the Transformation Method for the same matching procedure. For example, the proposed fingerprint matching algorithm comprised of the Hough Transform and same Edge Detection operators. Finally, distinct Edge Detection operators based on the decision making algorithm were used to calculate and determine the percentage of matching. Therefore, this study proved that the prints obtained via the Prewitt Edge Detection together with Hough Transform were in an agreement.