IRJET-Secure Face Spoof Detection on Smartphone (original) (raw)
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Face Spoofing and Counter-Spoofing: A Survey of State-of-the-art Algorithms
Transactions on Machine Learning and Artificial Intelligence, 2017
In the current scenario of biometric-based identity verification, a face is still being proved to be an essential physiological evidence for successful person identification without letting know the target. Nevertheless, repeated attacks of intruders can cause the face recognition system insecure because of easy availability of face images or pictures of a person in social networks or in other networked resources. Spoofing facial identity in a biometric system is not a difficult task for intruders. When an intruder presents a photograph or a video containing a face of a person in front of a networked camera which is integrated with a face biometric system, spoofing is referred to as presentation attack. Without anti-spoofing mechanisms, biometric systems are at high risk in case of susceptible attacks. Thus, detecting face spoof in a face biometric system is a challenging research field. The aim of this book is to summarize some of the most popular face spoof detection techniques wh...
Survey on Secure Face: Spoof Detection
Spoofing attack against biometric systems is still an important issue. Face spoofing is a form of attack that is presenting a fake sample to the acquisition sensor with facial information of a valid user. Compared to various attacks against fingerprint, speech or iris recognition systems, the ubiquitous nature of image acquisition devices, such as cameras and smartphones, allows attackers to acquire facial images of a user easily and discretely. This paper presents a literature survey on spoof detection methods and proposes a method to detect whether the input face is spoofed or not. Edge Adaptive Hybrid Filter is used for image enhancement and Naive Bayes classifier is used for classification to detect spoofed face.
The Comprehensive Review of Face Anti-Spoofing Techniques
International Journal of Advanced Science and Technology, 2020
Assorted robust security systems are using different biometric modalities such as face, eyes, fingers, palms, voice, etc. Among them, face recognition is the one which needs no cooperation from user and is contactless. Increase in use of face biometric systems have raised many new challenges in day to day applications such as smartphones, laptops, banking sector, airports, criminal identification, online exams or interviews, etc. Spoofing refers to bypassing biometric security systems by acquiring unauthorized access. Numerous face recognition systems lack face liveness detection functionality. Hence these systems are liable to suffer from various face spoofing attacks such as mask attack, photo attack, video replay attack, cut photo attack, etc. Photo attack is mostly preferred because of its low cost and simplicity. This paper gives a brief overview of various face presentation attacks (FPA) and face anti-spoofing techniques. This paper also covers different methodologies for face spoofing detection, description of the experimentation databases available for face spoofing detection and aims to provide new research direction in this field.
A Review on Face Anti-Spoofing
IJITEE (International Journal of Information Technology and Electrical Engineering), 2021
The biometric system is a security technology that uses information based on a living person's characteristics to verify or recognize the identity, such as facial recognition. Face recognition has numerous applications in the real world, such as access control and surveillance. But face recognition has a security issue of spoofing. A face anti-spoofing, a task to prevent fake authorization by breaching the face recognition systems using a photo, video, mask, or a different substitute for an authorized person's face, is used to overcome this challenge. There is also increasing research of new datasets by providing new types of attack or diversity to reach a better generalization. This paper review of the recent development includes a general understanding of face spoofing, anti-spoofing methods, and the latest development to solve the problem against various spoof types.
Antispoofing in face biometrics: a comprehensive study on software-based techniques
Computer Science and Information Technologies
The vulnerability of the face recognition system to spoofing attacks has piqued the biometric community's interest, motivating them to develop anti-spoofing techniques to secure it. Photo, video, or mask attacks can compromise face biometric systems (types of presentation attacks). Spoofing attacks are detected using liveness detection techniques, which determine whether the facial image presented at a biometric system is a live face or a fake version of it. We discuss the classification of face anti-spoofing techniques in this paper. Anti-spoofing techniques are divided into two categories: hardware and software methods. Hardware-based techniques are summarized briefly. A comprehensive study on software-based countermeasures for presentation attacks is discussed, which are further divided into static and dynamic methods. We cited a few publicly available presentation attack datasets and calculated a few metrics to demonstrate the value of anti-spoofing techniques.
The Implementation of Face Security for Authentication Implemented on Mobile Phone
2011
In this paper we are presenting the face recognition security for mobile phones. The model which has been applied for face recognition is Eigenface. The implementation consists from two parts: MATLAB and Droid Emulator for ANDROID mobile phones. The proposed implementation model has come as an idea, since today's mobile phones are computers in medium. We run our e-mails, agendas, storing data, using it for financial applications for viewing stock markets etc., and we would like to provide the approach of security model which will be based on face recognition as a biometric approach for authentication on mobile phones. Due the PIN vulnerability, as the most used mobile phone authentication mechanism we are presenting the approach which will enable a new level of mobile phone user's security. This has been tested with the database which consists from many images of facial expression. The algorithm which was implemented for mobile face recognition on MATLAB side is PCA. Limited with hardware capabilities we made of substitution between accuracy and computation complexity on the application. Proliferation of application and data has aim to increase the user need to protect the data which exist in mobile devices.
To detect duplication of identity during authentication of online payment on mobile or personal computer, the automatic face recognition is widely used now days. The biometric presentation attacks can be performed to gain access to these systems. It is performed by presenting the authorized person"s photo or video. Hence it is important to study the various face spoof attacks. Currently proposed face spoof detection techniques have less generalization ability as these are not considering all factors and do not detect the spoofing medium.The four features such as specular reflection, blurriness, chromatic moment and color diversity are used to analyze the image distortion. The different classifiers are trained for printed photo attack and video replay attack to differentiate between genuine and spoof faces. We also propose an approach to detect the spoofing medium by checking the boundary of the captured image during the photo attack and video attack and an approach to detect the blinking of eye for detecting liveness. It gives us high efficiency rather than existing methods.
Masquerade Attack Analysis for Secured Face Biometric System
IJRTE, 2021
Biometrics systems are mostly used to establish an automated way for validating or recognising a living or nonliving person's identity based on physiological and behavioural features. Now a day's biometric system has become trend in personal identification for security purpose in various fields like online banking, e-payment, organizations, institutions and so on. Face biometric is the second largest biometric trait used for unique identification while fingerprint is being the first. But face recognition systems are susceptible to spoof attacks made by nonreal faces mainly known as masquerade attack. The masquerade attack is performed using authorized users' artifact biometric data that may be artifact facial masks, photo or iris photo or any latex finger. This type of attack in Liveness detection has become counter problem in the today's world. To prevent such spoofing attack, we proposed Liveness detection of face by considering the countermeasures and texture analysis of face and also a hybrid approach which combine both passive and active liveness detection is used. Our proposed approach achieves accuracy of 99.33 percentage for face anti-spoofing detection. Also we performed active face spoofing by providing several task (turn face left, turn face right, blink eye, etc) that performed by user on live camera for liveness detection.
A Case Study on Face Spoof Detection
IRJET, 2022
User authentication is a vital step in protecting information, and facial bio metrics might assist in this regard. Face bio metrics seems to be more natural, simple to use, and less intrusive to humans. Unfortunately, emerging research has revealed that face bio metrics are extremely sensitive to spoofing assaults. A spoofing attack occurs when a person tries to masquerade as someone else by falsifying data and thereby gaining illegitimate access. Inspired by image quality assessment, characterization of printing artifacts, and differences in light reflection, we propose to approach the problem of spoofing detection from texture analysis point of view. This report discusses many types of assaults against visual spectrum facial recognition systems. We propose comprehensive data sets for assessing the susceptibility of recognition systems and the effectiveness of countermeasures. Finally, we give a brief overview of anti-spoofing strategies for visual spectrum face identification, as well as a viewpoint on difficulties that remain unresolved.
Fingerphoto spoofing in mobile devices: A preliminary study
2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS), 2016
Biometric-based authentication for smart handheld devices promises to provide a reliable and alternate security mechanism compared to traditional methods such as pins, patterns, and passwords. Although fingerprints are a viable source for authentication, they generally require installation of an additional hardware such as optical and swipe sensors on mobile devices, and are only available in expensive, high-end smartphones. Alternatively, fingerphoto images captured using the smartphone camera for authentication is one of the promising biometric approaches. However, using fingerphotos for authentication brings along a major challenge of fingerphoto spoofing. This research is aimed at understanding the effect of spoofing on fingerphotos. There are three major contributions of this research: (i) create a large spoofed fingerphoto database and make it publicly available for research, (ii) to establish the effect of print attack and photo attack in fingerphoto spoofing, and (iii) understand the performance of existing spoofing detection algorithms on fingerphoto spoofing.