The traditional methods used for the identification of individuals such as personal identification numbers (PINs), identification tags, etc., are vulnerable as they are easily compromised by the hackers. In this paper, we aim to focus on the existing multibiometric systems that use hand based modalities for the identification of individuals. We cover the existing multibiometric systems in the context of various feature extraction schemes, along with an analysis of their performance using one of the performance measures used for biometric systems. Later, we cover the literature on template protection including various cancelable biometrics and biometric cryptosystems and provide a brief comment about the methods used for multibiometric template protection. Finally, we discuss various open issues and challenges faced by researchers and propose some future directions that can enhance the security of multibiometric templates.
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http://dx.doi.org/10.7717/peerj-cs.707 | DOI Listing |
Comput Intell Neurosci
July 2023
Department of Electrical Engineering, Shahed University, Tehran, Iran.
The need for information security and the adoption of the relevant regulations is becoming an overwhelming demand worldwide. As an efficient solution, hybrid multimodal biometric systems utilize fusion to combine multiple biometric traits and sources with improving recognition accuracy, higher security assurance, and to cope with the limitations of the uni-biometric system. In this paper, three strategies for dealing with a feature-level deep fusion of five biometric traits (face, both irises, and two fingerprints) derived from three sources of evidence are proposed and compared.
View Article and Find Full Text PDFMultimed Tools Appl
April 2023
Department of Electrical Engineering, Prince Sattam Bin Abdulaziz University, Al-Kharj, 16278 Saudi Arabia.
With the growing use of mobile devices and Online Social Networks (OSNs), sharing digital content, especially digital images is extremely high as well as popular. This made us convenient to handle the ongoing COVID-19 crisis which has brought about years of change in the sharing of digital content online. On the other hand, the digital image processing tools which are powerful enough to make the perfect image duplication compromises the privacy of the transmitted digital content.
View Article and Find Full Text PDFComput Intell Neurosci
March 2023
China Foreign Affairs University, Beijing, China.
With the continuous development of computer technology, many institutions in society have higher requirements for the efficiency and reliability of identification systems. In sectors with a high-security level, the use of traditional key and smart card system has been replaced by the identification system of biometric technology. The use of fingerprint and face recognition in biometric technology is a biometric technology that does not constitute an infringement on the human body and is convenient and reliable.
View Article and Find Full Text PDFJ Imaging
November 2022
Department of Computer Science, University of Salerno, I-84084 Fisciano, SA, Italy.
In recent years, the study of soft biometrics has gained increasing interest in the security and business sectors. These characteristics provide limited biometric information about the individual; hence, it is possible to increase performance by combining numerous data sources to overcome the accuracy limitations of a single trait. In this research, we provide a study on the fusion of periocular features taken from pupils, fixations, and blinks to achieve a demographic classification, i.
View Article and Find Full Text PDFJ Med Signals Sens
July 2022
Department of Electrical Engineering, Shahed University, Tehran, Iran.
Background: The most significant motivations for designing multi-biometric systems are high-accuracy recognition, high-security assurances as well as overcoming the limitations like non-universality, noisy sensor data, and large intra-user variations. Therefore, choosing data for fusion is of high significance for the design of a multimodal biometric system. The feature vectors contain richer information than the scores, decisions and even raw data, thereby making feature-level fusion more effective than other levels.
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