Evaluation of biometric spoofing in a multimodal system

Rodrigues, Ricardo; Kamat, Niranjan; Govindaraju, Venu

doi:10.1109/btas.2010.5634531

Cited by 45 publications

(43 citation statements)

References 13 publications

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“…This is highly dependent on the used fusion algorithm, which has inspired fusion schemes specifically designed to increase the robustness to spoofing. Most notable are [21] which explores fuzzy logic, and [20] which extends the LLR scheme by introducing hidden variables denoting the probability of a spoofing attack. None of the mentioned work employs an algorithm specialized to detect spoofing attacks.…”

Section: Related Workmentioning

confidence: 99%

Anti-spoofing in Action: Joint Operation with a Verification System

Chingovska

Anjos

Marcel

2013

2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops

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Besides the recognition task, today's biometric systems need to cope with additional problem: spoofing attacks. Up to date, academic research considers spoofing as a binary classification problem: systems are trained to discriminate between real accesses and attacks. However, spoofing counter-measures are not designated to operate stand-alone, but as a part of a recognition system they will protect. In this paper, we study techniques for decisionlevel and score-level fusion to integrate a recognition and anti-spoofing systems, using an open-source framework that handles the ternary classification problem (clients, impostors and attacks) transparently. By doing so, we are able to report the impact of different spoofing counter-measures, fusion techniques and thresholding on the overall performance of the final recognition system. For a specific usecase covering face verification, experiments show to what extent simple fusion improves the trustworthiness of the system when exposed to spoofing attacks.

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Section: Related Workmentioning

confidence: 99%

Anti-spoofing in Action: Joint Operation with a Verification System

Chingovska

Anjos

Marcel

2013

2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops

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“…However, a hacker may fake only a subset of the fused biometric traits. Recently, researchers demonstrated that the existing multimodal systems can be deceived also when only a subset of the fused modalities is spoofed [6]. Rodrigues et al proposed an approach to measure the security of a multimodal system, where the contribution provided by each single modality matcher is weighted based on the ease to spoof that biometric trait.…”

Section: Introductionmentioning

confidence: 99%

Increase the Security of Multibiometric Systems by Incorporating a Spoofing Detection Algorithm in the Fusion Mechanism

Marasco

Johnson

Sansone

et al. 2011

Multiple Classifier Systems

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Abstract. The use of multimodal biometric systems has been encouraged by the threat of spoofing, where an impostor fakes a biometric trait. The reason lies on the assumption that, an impostor must fake all the fused modalities to be accepted. Recent studies showed that there is a vulnerability of the existing fusion schemes in presence of attacks where only a subset of the fused modalities is spoofed. In this paper, we demonstrated that, by incorporating a liveness detection algorithm in the fusion scheme, the multimodal system results robust in presence of spoof attacks involving only a subset of the fused modalities. The experiments were carried out by analyzing different fusion rules on the Biosecure multimodal database.

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“…Unfortunately, a biometric spoofing attack is fairly simple to execute [179]. Even though biometrics can improve the performance of the MFA system, they can also increase the number of vulnerabilities that can be exploited by an intruder.…”

Section: Security and Privacymentioning

confidence: 99%

Multi-Factor Authentication: A Survey

et al. 2018

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Today, digitalization decisively penetrates all the sides of the modern society. One of the key enablers to maintain this process secure is authentication. It covers many different areas of a hyper-connected world, including online payments, communications, access right management, etc. This work sheds light on the evolution of authentication systems towards Multi-Factor Authentication (MFA) starting from Single-Factor Authentication (SFA) and through Two-Factor Authentication (2FA). Particularly, MFA is expected to be utilized for human-to-everything interactions by enabling fast, user-friendly, and reliable authentication when accessing a service. This paper surveys the already available and emerging sensors (factor providers) that allow for authenticating a user with the system directly or by involving the cloud. The corresponding challenges from the user as well as the service provider perspective are also reviewed. The MFA system based on reversed Lagrange polynomial within Shamir's Secret Sharing (SSS) scheme is further proposed to enable more flexible authentication. This solution covers the cases of authenticating the user even if some of the factors are mismatched or absent. Our framework allows for qualifying the missing factors by authenticating the user without disclosing sensitive biometric data to the verification entity. Finally, a vision of the future trends in MFA is discussed.

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Evaluation of biometric spoofing in a multimodal system

Cited by 45 publications

References 13 publications

Anti-spoofing in Action: Joint Operation with a Verification System

Anti-spoofing in Action: Joint Operation with a Verification System

Increase the Security of Multibiometric Systems by Incorporating a Spoofing Detection Algorithm in the Fusion Mechanism

Multi-Factor Authentication: A Survey

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