2,357 research outputs found

    Pseudo Identities Based on Fingerprint Characteristics

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    This paper presents the integrated project TURBINE which is funded under the EU 7th research framework programme. This research is a multi-disciplinary effort on privacy enhancing technology, combining innovative developments in cryptography and fingerprint recognition. The objective of this project is to provide a breakthrough in electronic authentication for various applications in the physical world and on the Internet. On the one hand it will provide secure identity verification thanks to fingerprint recognition. On the other hand it will reliably protect the biometric data through advanced cryptography technology. In concrete terms, it will provide the assurance that (i) the data used for the authentication, generated from the fingerprint, cannot be used to restore the original fingerprint sample, (ii) the individual will be able to create different "pseudo-identities" for different applications with the same fingerprint, whilst ensuring that these different identities (and hence the related personal data) cannot be linked to each other, and (iii) the individual is enabled to revoke an biometric identifier (pseudo-identity) for a given application in case it should not be used anymore

    Hand-based multimodal identification system with secure biometric template storage

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    WOS:000304107200001This study proposes a biometric system for personal identification based on three biometric characteristics from the hand, namely: the palmprint, finger surfaces and hand geometry. A protection scheme is applied to the biometric template data to guarantee its revocability, security and diversity among different biometric systems. An error-correcting code (ECC), a cryptographic hash function (CHF) and a binarisation module are the core of the template protection scheme. Since the ECC and CHF operate on binary data, an additional feature binarisation step is required. This study proposes: (i) a novel identification architecture that uses hand geometry as a soft biometric to accelerate the identification process and ensure the system's scalability; and (ii) a new feature binarisation technique that guarantees that the Hamming distance between transformed binary features is proportional to the difference between their real values. The proposed system achieves promising recognition and speed performances on two publicly available hand image databases.info:eu-repo/semantics/acceptedVersio

    Biometric Keys for the Encryption of Multimodal Signatures

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    Electricity, electromagnetism & magnetis

    Anonymous subject identification and privacy information management in video surveillance

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    The widespread deployment of surveillance cameras has raised serious privacy concerns, and many privacy-enhancing schemes have been recently proposed to automatically redact images of selected individuals in the surveillance video for protection. Of equal importance are the privacy and efficiency of techniques to first, identify those individuals for privacy protection and second, provide access to original surveillance video contents for security analysis. In this paper, we propose an anonymous subject identification and privacy data management system to be used in privacy-aware video surveillance. The anonymous subject identification system uses iris patterns to identify individuals for privacy protection. Anonymity of the iris-matching process is guaranteed through the use of a garbled-circuit (GC)-based iris matching protocol. A novel GC complexity reduction scheme is proposed by simplifying the iris masking process in the protocol. A user-centric privacy information management system is also proposed that allows subjects to anonymously access their privacy information via their iris patterns. The system is composed of two encrypted-domain protocols: The privacy information encryption protocol encrypts the original video records using the iris pattern acquired during the subject identification phase; the privacy information retrieval protocol allows the video records to be anonymously retrieved through a GC-based iris pattern matching process. Experimental results on a public iris biometric database demonstrate the validity of our framework

    Accelerometer-Based Key Generation and Distribution Method for Wearable IoT Devices

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    Voice Recognition Systems for The Disabled Electorate: Critical Review on Architectures and Authentication Strategies

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    An inevitable factor that makes the concept of electronic voting irresistible is the fact that it offers the possibility of exceeding the manual voting process in terms of convenience, widespread participation, and consideration for People Living with Disabilities. The underlying voting technology and ballot design can determine the credibility of election results, influence how voters felt about their ability to exercise their right to vote, and their willingness to accept the legitimacy of electoral results. However, the adoption of e-voting systems has unveiled a new set of problems such as security threats, trust, and reliability of voting systems and the electoral process itself. This paper presents a critical literature review on concepts, architectures, and existing authentication strategies in voice recognition systems for the e-voting system for the disabled electorate. Consequently, in this paper, an intelligent yet secure scheme for electronic voting systems specifically for people living with disabilities is presented

    Comparative Analysis of Iris Segmentation and Iris Feature Extraction Techniques

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    Iris recognition is identification and verification of an individual based on their respective unique iris patterns. This system is preferred because it is stable: Iris of an individual does not change by the passing of time; Unique: Each person has a different Iris pattern; Flexible: it can easily be incorporated into security systems; Reliable: No theft because people can�t create an iris of another person;In our survey project the processes of Iris segmentation and Feature Extraction have been studied in depth.In this survey paper the various techniques that are used in Iris segmentation and Feature extraction processes are compared and analysed and a conclusion is drawn from them
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