Система виявлення та запобігання спуфінг-атакам під час біометричної ідентифікації за обличчям людини

Магістерська дисертація містить 122 сторінку, 58 рисунків, 34 таблиць, 8 додатків, 67 джерел. Тема: Тема магістерської дисертації “ Система виявлення та запобігання спуфінг-атакам під час біометричної ідентифікації за обличчям людини”. Актуальність: Актуальність магістерської дисертації полягає в тому, що сучасні системи захисту смартфонів та ноутбуків все частіше використовують біометричні дані користувача для ідентифікації та автентифікації, в тому числі обличчя людини. Такі світові корпорації як Apple, Samsung та Google використовують підсистеми ідентифікації користувача за обличчям у своїх пристроях, в тому числі смартфонах, що мають доступ до банківських даних людей, через системи Apple Pay та Google Pay, тому захист таких систем ідентифікації є вкрай важливим на сьогоднішній день. Мета: Метою роботи є створення системи з виявлення та протидії спуфнінг- атакам, яка б надавала показник HTER менше 1%, а також могла працювати як незалежна система напряму з сенсором, так і в заємодіїї з іншими системами через відповідний інтерфейс. Задачі: задачами роботи для досягнення мети є: - Дослідження існуючих видів спуфінг-атак; - Аналіз існучих алгоритмів виявлення спуфінг-атак, їх порівняння; - Розробка власної систему виявлення спуфінг-атак; - Тестування та порівння системи з існуючими рішеннями. Об’єкт: Об’єктом дослідження є спуфінг-атаки на системи ідентифікації за біометрією обличчя. Предмет дослідження: Предметом дослідження є системи виявлення та протидія спуфінг-атакам у системах ідентифікації за біометрією обличчя.The master's thesis contains 122 pages, 58 figures, 34 tables, 8 appendices, 67 sources. The topic of the master's thesis " System for detecting and preventing face spoofing attacks". Relevance: The relevance of the master's thesis lies in the fact that modern smartphone and laptop protection systems increasingly use the user's biometric data for identification and authentication, including a person's face. Global corporations such as Apple, Samsung, and Google use subsystems of user identification based on their faces in their devices, including smartphones, which have access to people's banking data through the Apple Pay and Google Pay systems, so the protection of such identification systems is extremely important today. Purpose: The purpose of the work is to create a system for detecting and countering spoofing attacks, which would provide an HTER rate of less than 1% and could also work as an independent system directly with a sensor, and also in interaction with other systems through the appropriate interface. The tasks: to achieve the goal there are several tasks for the work: - Research of existing types of spoofing attacks; - Analysis of existing algorithms for detecting spoofing attacks, comparing them according to the HTER indicator and the number of types of attacks they can detect; - Development of own spoofing attack detection system; - Testing and comparing the system with existing solutions. Object: The object of the study is spoofing attacks on facial biometric identification systems. Subject: The subject of the study is detection systems and countermeasures against spoofing attacks in facial biometrics identification systems

Face Spoofing Detection with Highlight Removal Effect and Distortions

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Vision-based spoofing face detection using polarised light

Computer vision is an image understanding discipline that studies how to reconstruct, interpret and understand a 3D scene from its 2D images. One of the goals is to automate the analysis of images through the use of computer software and hardware. Meanwhile, biometrics refer to the automated authentication process that rely on measureable physical characteristics such as individual’s unique fingerprints, iris, face, palmprint, gait and voice. Amongst these biometric identification schemes, face biometric is said to be the most popular where face authentication systems have been rapidly developed mainly for security reasons. However, the resistance of face biometric system to spoofing attack, which is an act to impersonate a valid user by placing fake face in front of the sensor to gain access, has become a critical issue. Thus, anti-spoofing technique is required to counter the attacks. Different materials have their own reflection properties. These reflection differences have been manipulated by researches for particular reasons such as in object classification. Many ways can be used to measure the reflection differences of each object. One of them is by using polarised light. Since none of the existing studies applied polarised light in face spoofing detection, therefore in this thesis, polarisation imaging technique was implemented to distinguish between genuine face and two types of spoofing attacks: printed photos and iPad displayed faces. From the investigations, several research findings can be listed. Firstly, unpolarised visible light could not be used in a polarisation imaging system to capture polarised images for designated purpose. Secondly, polarised light is able to differentiate between surface and subsurface reflections of real and fake faces. However, both of these reflections could not be used as one of the classification methods between real face and printed photos. Thirdly, polarised image could contribute to enhance the performance of face recognition system against spoofing attacks in which the newly proposed formula, SDOLP3F achieves higher accuracy rate. Next, near infrared (NIR) light in a polarisation imaging system do not provide significant differences between real face and the two face attacks. Apart from polarised spoofing face detection analysis, experiments to investigate the accuracy of depth data captured by three depth sensors was carried out. This investigation was conducted due to the concerns over the stability of the depth pixels involved in 3D spoofing face reconstruction in a publicly available spoofing face database known as 3DMAD. From the analysis, none of the three depth sensors which are the Kinect for Xbox 360, Kinect for Windows version 2.0 and Asus Xtion Pro Live are suitable for 3D face reconstruction for the purpose of spoofing detection due to the potential errors made by the fluctuated pixels. As a conclusion, polarisation imaging technique has the potential to protect face biometric system from printed photos and iPad displayed attacks. Further investigations using the same polarised light approach could be carried out on other future work as proposed at the end of this thesis