Face similarity linkage: A novel biometric approach to sexually motivated serial killer victims

Some sexually motivated serial killers target victims on the basis of appearance. Therefore, multiple victims of a single serial killer are likely to have some facial features and geometries that are similar. The current research was undertaken to propose a technique, termed face similarity linkage, to evaluate whether victims of a serial killer have statistically more similar facial measurements than a randomly chosen person of the same gender. To test this, three of Ted Bundy's victims were randomly selected and anatomical landmarks were located and measured to produce proportionality indices of their faces. A random subject from an online database was used as a comparison. The results showed there were no statistically significant differences between the three of Bundy's victims, however there was significant difference between 11 of the 17 facial measurements of Bundy's victims when compared to a random person. This research serves as a proof of concept that, with more advanced means of data collection, may be a useful tool for law enforcement for linking serial homicides. The current method is relatively novel, and in need of expert systems interfaces to improve speed and application, which is outlined in the current study.     

基于区块链的生物特征和口令双因子跨域认证与密钥协商方案

针对用户跨域访问数据资源的数据共享场景, 为了保证用户的身份合法性以及安全通信, 提出了一种基于区块链的生物特征和口令双因子跨域认证与密钥协商方案. 用户生物特征通过模糊提取技术转换为生物密钥和生物公开信息参与认证, 避免生物特征被泄露. 包含生物密钥和生物公开信息的用户身份信息存储在区块链账本中,保证身份信息一致以及...     

Gait recognition: highly unique dynamic plantar pressure patterns among 104 individuals

Everyone''s walking style is unique, and it has been shown that both humans and computers are very good at recognizing known gait patterns. It is therefore unsurprising that dynamic foot pressure patterns, which indirectly reflect the accelerations of all body parts, are also unique, and that previous studies have achieved moderate-to-high classification rates (CRs) using foot pressure variables. However, these studies are limited by small sample sizes (n < 30), moderate CRs (CR ≃ 90%), or both. Here we show, using relatively simple image processing and feature extraction, that dynamic foot pressures can be used to identify n = 104 subjects with a CR of 99.6 per cent. Our key innovation was improved and automated spatial alignment which, by itself, improved CR to over 98 per cent, a finding that pointedly emphasizes inter-subject pressure pattern uniqueness. We also found that automated dimensionality reduction invariably improved CRs. As dynamic pressure data are immediately usable, with little or no pre-processing required, and as they may be collected discreetly during uninterrupted gait using in-floor systems, foot pressure-based identification appears to have wide potential for both the security and health industries.     

基于ARM门禁系统的设计与实现

以嵌入式处理器（ARM）作为核心处理芯片,以指纹作为载体,通过控制器局域网（CAN）总线来实现上位机与门禁节点控制器的通信,完成了门禁系统的基本功能。该系统弥补了以往门禁系统中依赖单片机作为主要控制芯片的存储空间不足及扩展能力有限的弊端,并将人体生物特征应用到门禁系统中,利用人体生物特征的唯一性大大提高了门禁系统的安全性,促进了门禁系统的向前发展。     

Iris Recognition Technique

1 Introduction We are living in the age, in which the demand on security is increasing greatly. Consequently, biometric recognition, which is a safe, reliable and convenient technology for personal recognition, appears. This technology makes use of physiological or behavioural characteristics to identify individuals[1]. A biometric system is a pattern recognition system including acquiring the biometric feature from individual, extracting the feature vector from the raw data and comparing this…     

基于指纹特征数字水印算法的身份认证技术研究

本文利用指纹特征信息生成数字水印信号,并隐藏在身份证件之中.以身份证件作为指纹信息的载体,取代了传统指纹识别系统中的指纹特征参考信息数据库,提高整个自动指纹识别系统(AFIS)的安全性.同时,嵌入指纹特征信息的身份证件与用户存在本质联系,防止证件被盗用,实现对证件的保护.实验证明,使用含水印的证件在保证指纹识别系统正常工作的前提下,提高了验证的安全性,并且水印算法具有一定的鲁棒性.     

指静脉认证技术及应用

本文详细阐述了手指静脉特征识别技术的原理与特点,并与其他生物识别技术进行比较,最后介绍了日立制作所手指静脉相关产品及未来的应用领域。     

An anonymous biometric‐based remote user‐authenticated key agreement scheme for multimedia systems

We analyze the security of the Li et al . authentication scheme and show its vulnerability to off‐line password‐guessing and replay attacks. We design a new anonymous authentication scheme. The proposed scheme not only removes the drawback of the scheme of the Li et al . scheme but also protects user's anonymity. Moreover, we show validity of our proposed scheme using Burrows, Abadi, and Needham logic. Our scheme is comparable in terms of the communication and computational overhead with related schemes. Copyright © 2015 John Wiley & Sons, Ltd.     

Face Attribute Convolutional Neural Network System for Data Security with Improved Crypto Biometrics

Due to the enormous usage of the internet for transmission of data over a network, security and authenticity become major risks. Major challenges encountered in biometric system are the misuse of enrolled biometric templates stored in database server. To describe these issues various algorithms are implemented to deliver better protection to biometric traits such as physical (Face, fingerprint, Ear etc.) and behavioural (Gesture, Voice, tying etc.) by means of matching and verification process. In this work, biometric security system with fuzzy extractor and convolutional neural networks using face attribute is proposed which provides different choices for supporting cryptographic processes to the confidential data. The proposed system not only offers security but also enhances the system execution by discrepancy conservation of binary templates. Here Face Attribute Convolutional Neural Network (FACNN) is used to generate binary codes from nodal points which act as a key to encrypt and decrypt the entire data for further processing. Implementing Artificial Intelligence (AI) into the proposed system, automatically upgrades and replaces the previously stored biometric template after certain time period to reduce the risk of ageing difference while processing. Binary codes generated from face templates are used not only for cryptographic approach is also used for biometric process of enrolment and verification. Three main face data sets are taken into the evaluation to attain system performance by improving the efficiency of matching performance to verify authenticity. This system enhances the system performance by 8% matching and verification and minimizes the False Acceptance Rate (FAR), False Rejection Rate (FRR) and Equal Error Rate (EER) by 6 times and increases the data privacy through the biometric cryptosystem by 98.2% while compared to other work.