DIGITAL SIGNATURE IN CYBER SECURITY

For secure exchanges over open organizations, the Digital Signature method is basic. It is having assortments of uses to guarantee the uprightness of information traded or put away and to demonstrate the character of the originator to the beneficiary. Computerized Signature plans are regularly utilized in cryptographic conventions to offer types of assistance like element verification, confirmed key vehicle and validated key arrangement. Multi-biometric frameworks are as a rule perpetually sent in some huge scope biometric applications (e.g., FBI-IAFIS, UIDAI plot in India) since they have many points of interest, for example, second rate mistake rates and more prominent people inclusion contrasted with uni-biometric frameworks. In this paper, we propose a component level combination system to all the while ensure various layouts of a client as a sole secure sketch. Our main commitments include: 1) useful execution of the proposed highlight level combination development utilizing two notable biometric cryptosystems, in particular, fluffy vault and fluffy responsibility, and 2) nitty gritty investigation of the compromise between coordinating exactness and security in the proposed multibiometric cryptosystems dependent on two divergent information bases (one genuine and one virtual multimodal information base), each containing the three most famous biometric modalities, to be specific, unique mark, iris, and face. Test results give subtleties that together the multibiometric cryptosystems proposed here have progressed safe-haven and equal execution contrasted with their uni-biometric partners

System for Recognition of 3D Hand Geometry

V posledním desetiletí došlo ke zvýšení zájmu o užití 3D dat k biometrické identifikaci osob. Možná vůbec největší výzkum proběhl v oblasti 3D rozpoznávání podle obličeje, přičemž je v současné době dostupných vícero komerčních zařízení. V oblastni rozpoznávání podle 3D geometrie ruky byl v minulých letech proveden určitý výzkum jehož výsledkem však nebylo žádné komerční zařízení. Nezávisle na tomto výzkumu se v posledních letech velmi rozšířil trh s cenově dostupnými 3D sensory, což potenciálně umožňuje jejich nasazení v mnoha typech biometrických systémů. Hlavním cílem této práce je vytvořit funkční vzorek bezdotykového systému pro rozpoznávání osob podle 3D geometrie ruky, který bude používat novou levnou kameru RealSense 3D vyvíjenou v současné době firmou Intel. Jedním z problémů při použití RealSense kamery je její velmi malý form factor, který je příčinou nižší kvality výsledných snímků v porovnání s velmi drahými alternativami, které byly použity v již dříve zmíněném výzkumu 3D biometrických systémů. Práce se snaží analyzovat robustnost různých 2D a 3D příznaků a vyzkoušet několik různých přístupů k jejich fúzi. Rovněž je vyhodnocena výkonnost výsledného systému, kde je ukázáno, že navržené řešení dosahuje výsledků porovnatelných se state-of-the-art. In the last decade, there has been an increased interest in using 3D data for biometric person recognition. Perhaps the most widely researched application is 3D face recognition, where several commercial products are currently available on the market. There have been some research works on the 3D hand recognition as well, however, no commercially viable systems are currently known. Independently, in the recent years inexpensive 3D sensors have become a commodity, potentially enabling a wide range of 3D biometric applications. The main goal of this work is to develop a functioning prototype of a touchless 3D hand recognition system based on a new cheap RealSense 3D camera developed by Intel. One of the challenges in using the RealSense camera is that due to this small form factor, it produces relatively low quality samples in comparison to the more expensive acquisition hardware used in the previous research on the 3D hand biometrics. We analyze the robustness of different 2D and 3D features and study several methods for their fusion. We evaluate the performance of the system, showing that it achieves results comparable with the state-of-the-art.

Hand-Based Biometric Analysis

Hand-based biometric analysis systems and techniques are described which provide robust hand-based identification and verification. An image of a hand is obtained, which is then segmented into a palm region and separate finger regions. Acquisition of the image is performed without requiring particular orientation or placement restrictions. Segmentation is performed without the use of reference points on the images. Each segment is analyzed by calculating a set of Zernike moment descriptors for the segment. The feature parameters thus obtained are then fused and compared to stored sets of descriptors in enrollment templates to arrive at an identity decision. By using Zernike moments, and through additional manipulation, the biometric analysis is invariant to rotation, scale, or translation or an in put image. Additionally, the analysis utilizes re-use of commonly-seen terms in Zernike calculations to achieve additional efficiencies over traditional Zernike moment calculation

Reconhecimento biométrico baseado na geometria da mão

Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 201