Multi-biometric systems have been widely accepted in various applications due to its capability to solve the limitations of unimodal systems. Directly storing the biometric templates into a centralised server leads to privacy concerns. In the past few years, many biometric authentication systems based on homomorphic encryption have been introduced to provide security for the templates. Most of the existing solutions rely on an implication of the assumption that the server is ‘honest-but-curious’. Therefore, the compromise of server results into the entire system vulnerability and fails to provide the integrity. To address this, we propose a novel multi-instance iris authentication system, BMIAE to deal with malicious attacks over the transmission channel and at the untrusted server. BMIAE encrypt the iris templates using ElGamal encryption to guarantee confidentiality and Smart contract running on a Blockchain helps to achieve the integrity of templates and matching result. BMIAE also addresses the limitations of using Blockchain for biometrics like privacy and expensive storage. To check the effectiveness and robustness, BMIAE has experimented on CASIA-V3-Interval, IITD and SDUMLA-HMT iris databases. Experimental results show that BMIAE provides improved accuracy, and eliminates the need to trust the centralised server when compared to the state-of-the-art approaches.

中文翻译：

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BMIAE：使用加性ElGamal同态加密的基于区块链的多实例虹膜身份验证

多生物系统因其解决单峰系统局限性的能力而被广泛接受。将生物特征模板直接存储到中央服务器会导致隐私问题。在过去的几年中，已经引入了许多基于同态加密的生物特征认证系统来为模板提供安全性。现有的大多数解决方案都依赖于服务器“诚实但好奇”的假设。因此，服务器的危害会导致整个系统漏洞，并且无法提供完整性。为了解决这个问题，我们提出了一种新颖的多实例虹膜身份验证系统，美国医学会在传输通道和不受信任的服务器上处理恶意攻击。BMIAE使用ElGamal加密对虹膜模板进行加密以确保机密性，并且在区块链上运行的智能合约有助于实现模板的完整性和匹配结果。美国医学会还解决了将区块链用于生物识别的局限性，例如隐私和昂贵的存储。要检查有效性和鲁棒性，美国医学会在CASIA-V3-Interval，IITD和SDUMLA-HMT虹膜数据库上进行了实验。实验结果表明美国医学会 与最新技术相比，它提供了更高的准确性，并且消除了对集中式服务器信任的需要。