一种基于数据融合的身份识别方法

针对单一生物特征身份识别由于传感器噪音及特征破损等缺陷导致识别率低的问题,从信息融合角度出发,提出一种基于语音和人脸的多生物特征身份识别方法.分别提取语音特征和人脸特征作为识别的依据,并用神经网络在特征层上进行融合识别.实验证明,该方法相对单一生物特征身份识别,在同等条件下具有更高的识别率.     

基于指纹和声纹的身份认证技术研究

基于生物特征识别的身份认证技术已经应用于多个领域,然而单一的生物特征有各自的优缺点,为了提高身份认证的安全性和鲁棒性,对多生物特征进行融合便成为了身份认证技术新的研究方向。将指纹识别和声纹识别通过加权融合的方法在匹配层进行融合,实验结果表明,融合系统的等错误率(EER)比指纹识别和声纹识别提高了0.3%~0.4%,证明了融合系统识别率有所提高。     

基于神经网络融合的语音人脸身份识别方法

传统的身份识别系统利用单一的生物特征作为依据,在复杂背景下,系统性能往往会大幅下降。基于数据融合的多生物特征身份识别技术可以提高生物识别系统的准确率等性能。该文利用特征脸和矢量量化方法建立人脸识别和语音识别两个子系统,在决策层用神经网络融合子系统的输出来进行身份识别。实验证明该方法比单个子系统识别率高,在噪音环境下,优势明显。     

基于三角范数的多模态手指生物特征的分数层融合方法

多模态的生物特征融合已成为目前生物识别研究领域的主要发展趋势,从防伪性角度出发,满足普适性和易采集、易接受性的应用需求,提出了基于手指静脉,并结合指纹、指关节纹和指形的分数层融合来实现多模态生物特征的身份认证方案。实验结果表明,本文提出基于Sugeno-Weber三角范数的分数层融合方法,能够增大类内与类间匹配分数分布间的距离,提高了多模态生物特征的身份认证性能。     

基于改进ENN算法的多生物特征融合的身份验证

基于多生物特征的身份鉴别技术已受到越来越多的重视.单个生物特征有其固有的局 限性,通过融合不同的生物特征可以提高身份鉴别系统的验证性能和鲁棒性.该文融合了声纹 和指纹特征,提出了一种改进的ENN方法,并与K-NN、传统ENN方法进行了比较.改进的 ENN将认证率提高了大约2％.同时,又在不同的数据集上比较了改进的ENN方法和基于 Bayes理论的融合系统,分析并评价了两种方法的适用范围和优缺点.实验结果证明了此方法的 有效性.     

融合多生物特征的RFID智能身份识别系统设计

RFID技术和生物特征识别得到了快速发展,为进一步提高身份识别的精度和效率,该文介绍了一种融合RFID和多生物特征的身份认证系统模型。该系统模型可以应用在很多领域如公共场所的安全检测、工作区域的出入口等,具有非常重要的实际应用价值。     

融合多生物特征的RFID智能身份识别系统设计

RFID技术和生物特征识别得到了快速发展,为进一步提高身份识别的精度和效率,该文介绍了一种融合RFID和多生物特征的身份认证系统模型。该系统模型可以应用在很多领域如公共场所的安全检测、工作区域的出入口等,具有非常重要的实际应用价值。     

生物特征识别综述*

对传统的身份鉴别手段和现代生物特征识别技术产生背景进行了综述,介绍目前典型的生物特征识别技术的原理和发展趋势,分析了实际应用中存在的优缺点,并探讨了基于个人生物特征融合的多生物特征识别技术和生物特征信息保护问题,强调了生物识别技术在身份认证领域的重要性。     

基于两枚不同指纹融合模糊金库的身份认证算法

基于单一生物特征模糊金库证易于受到相关攻击而导致生物特征模板泄露的安全性问题,提出一种基于两枚不同手指指纹的特征融合模糊金库的身份认证方案。这种身份认证方案采用了分别来自两枚不同手指指纹的细节点与方向场进行融合的方法,基于Diffie-Hellman密钥交换协议思想。实验结果表明该身份认证方案在指纹特征模板的安全性保护上比基于单一指纹特征模板有显著提高。     

基于匹配分数的多生物特征识别融合综述

受数据噪音和识别系统本身的限制,基于单一生物特征的身份认证系统所能达到的准确率是有限的。通过多生物特征识别来提高识别的准确率成为当前生物特征识别领域的研究热点之一。首先介绍了多生物特征识别的必要性、多生物特征识别的分类,然后重点介绍了基于匹配分数的多生物特征识别融合的研究现状,最后总结了多生物特征识别研究中的问题和未来的研究方向。     

Person authentication using brainwaves (EEG) and maximum a posteriori model adaptation

In this paper, we investigate the use of brain activity for person authentication. It has been shown in previous studies that the brainwave pattern of every individual is unique and that the electroencephalogram (EEG) can be used for biometric identification. EEG-based biometry is an emerging research topic and we believe that it may open new research directions and applications in the future. However, very little work has been done in this area and was focusing mainly on person identification but not on person authentication. Person authentication aims to accept or to reject a person claiming an identity, i.e., comparing a biometric data to one template, while the goal of person identification is to match the biometric data against all the records in a database. We propose the use of a statistical framework based on Gaussian mixture models and maximum a posteriori model adaptation, successfully applied to speaker and face authentication, which can deal with only one training session. We perform intensive experimental simulations using several strict train/test protocols to show the potential of our method. We also show that there are some mental tasks that are more appropriate for person authentication than others     

FPGA implementation of fast & secure fingerprint authentication using trsg (true random and timestamp generator)

In the digital authentication system, the emerging technology is fingerprint authentication, which have been concentrated more attraction towards security and control. Existing authentication systems such as Biometric cryptosystems, Cancellable templates, and Bio-hashing provide a solution for addressing these vulnerabilities. To implement the fingerprint authentication with more accuracy, a novel FPGA based authentication system has proposed in this paper and the performance has evaluated with the help of the previous scheme. First, finger code template (FCT) is generated by applying transformation function on finger code and biometric key created from the randomization process. While in the second phase, 40-bit binary string (ofc), 40-bit binary time stamp, random numbers 0 and 40 (r1, r2, r3, and r4) are generated from TRSG (True Random and Time Stamp Generator) which is converted into 80-bit efc. Based on the obtained efc, the person details are compared with primary data stored in the database. The simulation result shows that the proposed method reduces the LUT utilization to 0.17% and complexity as 14%. Hence, FPGA based fingerprint authentication shows its excellence with the lowest complexity value and thereby enhance the presentation of the biometric authentication system.     

A text-independent Persian writer identification based on feature relation graph (FRG)

The style of people's handwriting is a biometric feature that is used in person authentication. In this paper, we have proposed a text independent method for Persian writer identification. In the proposed method, pattern based features are extracted from data using Gabor and XGabor filter. The extracted features are represented for each person by using a graph that is called FRG (feature relation graph). This graph is constructed using relations between extracted features by employing a fuzzy method. The fuzzy method determines the similarity between features extracted from different handwritten instances of each person. In the identification phase, a graph similarity approach is employed to determine the similarity of the FRG generated from the test data and the FRGs generated by training data. The experimental results were satisfactory and the proposed method got about 100% accuracy on a dataset with 100 writers when enough training data was used. However, this method has been applied on Persian handwritings but we believe it can be extended on other languages especially in data representation and classification parts.     

基于可逆信息隐藏技术的认证方案的攻击与改进

可逆信息隐藏技术一方面能够对图像的原始性和完整性进行认证和保护,同时还能够确保无失真地恢复原始图像,近年来在公安、司法等领域受到越来越多的关注。基于可逆信息隐藏的认证方案需要同时满足可逆和认证两个方面的要求,在实际中具有较大挑战性,目前成功案例较少。在文献[1]中,Hong等人提出了一种新的基于可逆信息隐藏技术的认证方法,该方法借助IPVO(Improved pixel-value-ordering)和LSB(Least significant bit)替换等技术,可以有效地对图像进行认证。本文我们对Hong等人的方法进行了深入研究,指出在该方法中仅有部分像素参与认证码的生成且攻击方能够很容易地获知这部分像素,因此在安全性上还存在不足。针对该方法存在的安全漏洞,我们提出了一种针对性的攻击方案,即攻击方可选择对图像中未参与认证码生成和嵌入的像素进行修改。该攻击方案可以在不影响所嵌入认证码提取的同时,实现有意义篡改。为了提高认证算法的安全性,本文还针对Hong等人算法的缺陷提出了相应的改进方案,即将更多像素引入认证码的生成过程中并在嵌入前对图像块进行置乱。理论分析和实验结果验证了本文提出的...     

Scalable watermark extraction for real-time authentication of JPEG 2000 images

This paper proposes a novel scalable authentication scheme that utilizes the progressive enhancement functionality in JPEG 2000 scalable image coding. The proposed method first models the wavelet-based quality scalable coding to identify the effect of the quantization and de-quantization on wavelet coefficient magnitudes and the data embedded within such coefficients as a watermark. A relationship is then established between the watermark extraction rule and the embedding rule, using the magnitudes of the reconstructed and original coefficients. It ranks the wavelet coefficients according to their ability to retain the embedded watermark data intact under various quantization levels corresponding to quality enhancements. Then watermark data is embedded into wavelet coefficients according to their rank followed by JPEG 2000 embedded coding. At the decoder as more and more quality and resolution layers are decoded the authentication metric is improved, thus resulting in gradually increasing complexity of the authentication process according to the number of quality and resolution enhancements. The low complexity authentication is available at low quality low resolution decoding, enabling real-time authentication for resource constrained applications without affecting the authentication metric. Compared to the existing methods, the proposed method results in highly robust scalable authentication of JPEG 2000 coded images.     

基于遗传算法和灰色关联分析的击键特征识别算法

基于用户击键特征的身份认证比传统的基于口令的身份认证方法有更高的安全性，现有研究方法中基于神经网络、数据挖掘等算法计算复杂度高，而基于特征向量、贝叶斯统计模型等算法识别精度较低。为了在提高识别精度的同时有效降低计算复杂度，在研究现有算法的基础上提出了一种基于遗传算法与灰色关联分析的击键特征识别算法。该算法利用遗传算法根据用户训练样本确定表征用户击键特征的标准特征序列，通过对当前用户击键特征序列与标准特征序列进行灰色关联分析实现用户身份认证。实验结果表明，该算法识别精度达到神经网络、支持向量机等算法的较高水平，错误拒绝率与错误接受率分别为0%与1.5%。且计算复杂度低，与基于特征向量的算法相近。     

Area bound dynamic time warping based fast and accurate person authentication using a biometric pen

The paper presents a modified dynamic time warping (DTW) technique for person authentication based on time series matching obtained from handwriting. The online data has been acquired by a biometric smart pen device. The proposed method allows fast and accurate classification of human individuals based on handwritten PIN words or signature samples. Although classic DTW provides robust distance measurements essential for accurate classification of sequences, it is computationally expensive. To speed up computations we introduce area bound dynamic time warping (AB_DTW) that divides time series into several areas bounded by segments of consecutive zero crossings including local peaks and valleys. Unlike classic DTW which compares whole signals, the proposed AB_DTW warps areas bounded by the local regions. Two kinds of data abstraction formats of area bound—1 dimensional and 2 dimensional—are evaluated. Experimental results show that because of a higher-level data abstraction, the proposed approach is several times faster than classic DTW. Moreover, AB_DTW does not offer substantial loss of accuracy which is required for authentication performance using handwritten PIN words and signatures sampled by biometric pen device.     

体域网中基于CSI指纹的身份认证算法研究

无线体域网是实现智慧健康的重要基础,但其采集的生理状态等敏感信息在开放的无线信道传输,攻击者容易伪装成合法用户获取用户隐私数据,因而身份认证成为挑战。对此,提出了一种将无线信道特征CSI与递归神经网络（RNN）相结合的身份认证方法,实现体域网中节点的有效身份认证。利用无线体域网中无线信道的物理层特征CSI作为合法节点认证的指纹特征。为了加快认证速度与效率,通过取特定环境下CSI的数据包,将数据包中子载波的特性作为RNN的输入量,训练出RNN模型来快速识别合法节点。通过实验将所提出的身份认证方法与利用RSS作为指纹特征的认证方法进行比较,结果表明所提方法的认证速度更快、准确率更高。     

基于OTP和RSA的身份认证系统研究

该文应用RSA密码机制既可对数据加密又可对私钥拥有者进行身份认证的原理,对挑战/应答方式的动态口令身份认证系统进行了改进。改进后的系统通过对在网络上传输的认证数据进行加密确保了数据在传输过程中的安全性,同时实现了用户和服务器间的双向认证。另外,改进方案利用软件来产生随机挑战大大节省了开销成本。     

Graph-Based Replication and Two Factor Authentication in Cloud Computing

Many cutting-edge methods are now possible in real-time commercial settings and are growing in popularity on cloud platforms. By incorporating new, cutting-edge technologies to a larger extent without using more infrastructures, the information technology platform is anticipating a completely new level of development. The following concepts are proposed in this research paper: 1) A reliable authentication method Data replication that is optimised; graph-based data encryption and packing colouring in Redundant Array of Independent Disks (RAID) storage. At the data centre, data is encrypted using crypto keys called Key Streams. These keys are produced using the packing colouring method in the web graph’s jump graph. In order to achieve space efficiency, the replication is carried out on optimised many servers employing packing colours. It would be thought that more connections would provide better authentication. This study provides an innovative architecture with robust security, enhanced authentication, and low cost.