Survey of Various Face Liveness Detection Techniques for Biometric Antispoofing Applications (original) (raw)
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An Overview of Face Liveness Detection
International Journal on Information Theory, 2014
Face recognition is a widely used biometric approach. Face recognition technology has developed rapidly in recent years and it is more direct, user friendly and convenient compared to other methods. But face recognition systems are vulnerable to spoof attacks made by non-real faces. It is an easy way to spoof face recognition systems by facial pictures such as portrait photographs. A secure system needs Liveness detection in order to guard against such spoofing. In this work, face liveness detection approaches are categorized based on the various types techniques used for liveness detection. This categorization helps understanding different spoof attacks scenarios and their relation to the developed solutions. A review of the latest works regarding face liveness detection works is presented. The main aim is to provide a simple path for the future development of novel and more secured face liveness detection approach.
—Face recognition is a widely used biometric approach. Face recognition technology has developed rapidly in recent years and it is more direct, user friendly and convenient compared to other methods. But face recognition systems are vulnerable to spoof attacks made by non-real faces. It is an easy way to spoof face recognition systems by facial pictures such as portrait photographs. A secure system needs Liveness detection in order to guard against such spoofing. In this work, face liveness detection approaches are categorized based on the various types techniques used for liveness detection. This categorization helps understanding different spoof attacks scenarios and their relation to the developed solutions. A review of the latest works regarding face liveness detection works is presented. The main aim is to provide a simple path for the future development of novel and more secured face liveness detection approach.
A Study of Liveness Detection in Face Biometric Systems
International Journal of Computer Applications, 2014
"Biometrics" refers to the technologies that measure and analyze human body characteristics for security purposes. The need of privacy and security in our daily life leads to this new area. Biometric systems have more accuracy when compared to traditional methods (password, key etc). It identifies and verifies the identity of a person based on one or more physiological and behavioral characteristics. That is Human body as password. The most common physical biometric traits includes fingerprint, face, ear, iris, retina, hand geometry, palmprint, DNA etc. Behavioral biometric traits include signature, gait, key strokes, speech patterns etc. Each biometric has its own strength and limitations and accordingly each biometric is used in identification (authentication) application. This paper concentrates on spoof attack against face recognition system, i.e. in this type of attack a fake biometric can be presented to sensor. This paper discusses about Introduction to The Face biometric system, Spoofing attack in Face recognition system, Liveness detection in face recognition system, Literature survey on Face Liveness detection and conclusion.
Face Liveness Detection : An Overview
International Journal of Scientific Research in Science and Technology, 2021
As the world becomes more and more digitized, the threat to security grows at an alarming rate. The mass usage of technology has garnered the attention and curiosity of people with foul intentions, whose aim is to exploit this use of technology to commit theft and other heinous crimes. One such technology used for security purposes is “Facial Recognition”. Face recognition is a popular biometric technique. Face recognition technology has advanced fast in recent years, and when compared to other ways, it is more direct, user-friendly, and convenient. Face recognition systems, on the other hand, are vulnerable to spoof assaults by non-real faces. To protect against spoofing, a secure system requires liveness detection. This study examines researchers' attempts to address the problem of spoofing and liveness detection, including mapping the research overview from the literature survey into a suitable taxonomy, exploring the fundamental properties of the field, motivation for using liveness detection methods in face recognition, and problems that may limit the benefits.
IRJET-Prevention of Spoofing Attacks in Face Recognition System Using Liveness Detection
Biometric system has gained wide selection of motivations and applications in security domain. Biometric systems relay on the biometric characteristics/data taken from the user for authentication. sadly such biometric information is stolen or duplicated by the imposters/unauthorized users. Most of the biometry systems rely strictly on distinguishing the physiological characteristics of the user. It becomes easier to spoof in these biometric systems with the help of faux biometric it any reduces the dependability and security of biometric system. Spoof fools the system through the method of deception and impersonating others to create out that they're licensed so as to achieve access in to the biometric system. Now a day’s spoofing has become quite common on the net that therefore ends up in determine stealing and fraud. There are several level of spoofing attacks like putting faux biometry on the detector, replay attack, attacking the entrance centre corrupting the intermediator, attacking the application etc. These successively can cut back the extent of security and dependability of biometric system. liveness identification using the facial expression also has been receiving a lot of attention compared to other biometric modalities. prevention of spoof attack in biometric system is done by detecting the liveness of the user with the assistance of native facial expression like eye blinking, lip movement, forehead and chin movement pattern of the face detected with real-time generic web-camera. within the planned work, a good authentication system using face biometric modality by developing the aliveness detection model using the variations within the facial movements.
Face Liveness Detection – A Comprehensive Survey Based on Dynamic and Static Techniques
Abstract - With the wide acceptance of online systems, the desire for accurate biometric authentication based on face recognition has increased. One of the fundamental limitations of existing systems is their vulnerability to false verification via a picture or video of the person. Thus, face liveness detection before face authentication can be performed is of vital importance. Many new algorithms and techniques for liveness detection are being developed. This paper presents a comprehensive survey of the most recent approaches and their comparison to each other. Even though some systems use hardware-based liveness detection, we focus on the software-based approaches, in particular, the important algorithms that allow for an accurate liveness detection in real-time. This paper also serves as a tutorial on some of the important, recent algorithms in this field. Although a recent paper achieved an accuracy of over 98% on the liveness NUAA benchmark, we believe that this can be further improved through incorporation of deep learning. Index Terms — Face Recognition, Liveness Detection, Biometric Authentication System, Face Anti-Spoofing Attack. International Journal of Computer Science and Information Security (IJCSIS), Vol. 13, No. 10, October 2015 https://sites.google.com/site/ijcsis/ ISSN 1947-5500
A robust anti-spoofing technique for face liveness detection with morphological operations
Optik, 2017
Face liveness detection is an advanced research topic nowadays due to its significant security applications in various fields and is of utmost paramountcy to ascertain the physical presence of person. The spoofing problem is a ferocious threat to security of the face recognition systems and it can be minimized by detecting the face liveness. In this paper, a robust antispoofing technique for face liveness detection with morphological operations has been proposed by considering eyeblink and mouth movements for procuring maximum reliability during face liveness detection. ZJU Eyeblink dataset, Print-Attack Replay dataset and inhouse dataset created in our university have been used for experimental purpose. ZJU Eyeblink dataset has been used to capture eyeblink, Print-Attack Replay dataset has been used to detect photo and video attack based on eyeblink while both eyeblink and mouth movements have been detected simultaneously using in-house dataset. The experimental results show that the proposed anti-spoofing technique significantly improves the security of a face recognition system by detecting face liveness. The efficiency of the proposed technique has been prosperously evaluated by detecting photo and video spoofing attacks.
A survey of Techniques for Face Liveness Recognition
2018
Automatic face recognition is now widely used in applications ranging from de duplication of identity to authentication of mobile payment. This popularity of face recognition has raised concerns about face spoof attacks (also known as biometric sensor presentation attacks), where a photo or video of an authorized person’s face could be used to gain access to facilities or services. While a number of face spoof detection techniques have been proposed, their generalization ability has not been adequately addressed. We propose an efficient and rather robust face spoof detection algorithm based on image distortion analysis (IDA). Four different features (specular reflection, blurriness, chromatic moment, and color diversity) are extracted to form the IDA feature vector. An ensemble classifier, consisting of multiple SVM classifiers trained for different face spoof attacks is used to distinguish between genuine (live) and spoof faces. The proposed approach is extended to multiframe 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.
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.