Proceedings ArticleDOI
Cloud-Based Framework for Cancelable Biometric System
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TLDR
This paper explores the possibility of executing cancelable biometric services offloaded to the cloud environment to provide privacy and protection to the biometrics stored in cloud.Abstract:
Biometric databases are normally stored in a trusted server which may not be able to offer adequate processing power and storage capacity for large databases. Cloud computing has various capabilities to store and process data in large-scale quickly. This paper explores the possibility of executing cancelable biometric services offloaded to the cloud environment. The major aim is to provide privacy and protection to the biometrics stored in cloud. It presents an elaborate note on the key components in building the system. A case study of cancelable iris recognition has been performed in cloud and its performance has been studied.read more
Citations
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Journal ArticleDOI
Cancelable Biometrics: a comprehensive survey
Manisha,Nitin Kumar +1 more
TL;DR: A comprehensive survey of more than 120 techniques suggested by various researchers from time to time for Cancelable Biometrics is presented and a novel taxonomy for the same is developed.
Journal ArticleDOI
Cancelable Biometrics Using Deep Learning as a Cloud Service
TL;DR: It is established that cloud is a good solution for biometric systems where intensive computation, quick response times, and high accuracy is required and a first cancelable biometric framework based on deep learning on the cloud is proposed.
Book ChapterDOI
A Robust Image Security System for Cloud-Based Smart Campus Using LBP and PCA
TL;DR: In this article, a method for personal identification using biometric system in cloud environment is proposed in which first biometric images are encrypted using either block encryption technique or pixel encryption technique.
Journal ArticleDOI
Improving Data Security, Privacy, and Interoperability for the IEEE Biometric Open Protocol Standard
TL;DR: A probabilistic scheme to encrypt biometric database indexes and a novel approach to interoperability among systems interchanging biometric characteristics, thus enhancing the IEEE Biometric Open Protocol Standard (BOPS).
References
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Proceedings ArticleDOI
Privacy-Preserving Public Auditing for Data Storage Security in Cloud Computing
TL;DR: This paper utilize and uniquely combine the public key based homomorphic authenticator with random masking to achieve the privacy-preserving public cloud data auditing system, which meets all above requirements.
Journal ArticleDOI
Generating Cancelable Fingerprint Templates
TL;DR: This paper demonstrates several methods to generate multiple cancelable identifiers from fingerprint images to overcome privacy concerns and concludes that feature-level cancelable biometric construction is practicable in large biometric deployments.
Journal ArticleDOI
CloudID: Trustworthy cloud-based and cross-enterprise biometric identification
TL;DR: The proposed approach is the first cloud-based biometric identification system with a proven zero data disclosure possibility, which allows different enterprises to perform biometrics identification on a single database without revealing any sensitive information.
Proceedings ArticleDOI
Efficient privacy-preserving biometric identification in cloud computing
Jiawei Yuan,Shucheng Yu +1 more
TL;DR: Thorough analysis shows that the proposed scheme is secure and offers a higher level of privacy protection than related solutions such as kNN search in encrypted databases and computational/communication costs at the owner side are several magnitudes lower than the existing biometric identification schemes.
Journal ArticleDOI
Cancellable iris template generation based on Indexing-First-One hashing
Yen-Lung Lai,Zhe Jin,Andrew Beng Jin Teoh,Bok-Min Goi,Wun-She Yap,Tong-Yuen Chai,Christian Rathgeb +6 more
TL;DR: A new cancellable iris scheme, coined as "Indexing-First-One" (IFO) hashing, inspired from the Min-hashing that primarily used in text retrieval domain and strengthened by two novel mechanisms, namely P-order Hadamard product and modulo threshold function is introduced.
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