特征层双模态生物识别算法容侵能力评测方法

相较于单模态生物识别技术,多模态生物识别技术具有更优的适用性、安全性和可靠性,成为目前生物识别技术发展的趋势。在多模态生物识别4种融合层次中,特征层融合能够提取更多的区分性信息,消除特征的冗余,在理论〖JP2〗上可达到最佳识别效果。然而,特征层多模态生物识别算法的安全性很少被关注。目前,多模态生物识别技术的研究多集中在双模态生物识别算法上,引入入侵容忍概念,定义了容侵能力度量,提出了容侵能力评测方法,评价特征层双模态生物识别算法的容侵能力,并对典型特征层双模态生物识别算法的安全性进行了评测。

Evaluation method of intrusion tolerance capability for bimodal biometrics resognition algorithm in feature level#br#

Comparing with unimodal biometric recognition technology, multimodal biometric technology has better applicability, security and reliability, and has become the trend of biometric recognition. In the four fusion levels of multimodal biometrics, feature level fusion can extract more discriminative information, eliminate the redundancy among different features and reach the best recongnition effect in theory. However, the security of multimodal biometrics in feature level is rarely concerned. At present, the research of multimodal biometrics technology is mostly focused on bimodal biometric algorithms. This paper introduces the concept of intrusion tolerance and defines the measurement of intrusion tolerant capacity. The evaluation method of intrusion tolerant capacity is proposed to evaluate the tolerant capacity of the feature level bimodal biometric algorithms. Then the existing typical multimodal biometric algorithms are evaluated by the proposed method.