A Swarm intelligence approach for biometrics verification and identification

In this paper we investigate a swarm intelligence classification approach for both biometrics verification and identification problems. We model the problem by representing biometric templates as ants, grouped in colonies representing the clients of a biometrics authentication system. The biometric template classification process is modeled as the aggregation of ants to colonies. When test input data is captured -- a new ant in our representation -- it will be influenced by the deposited phermonones related to the population of the colonies. We experiment with the Aggregation Pheromone density based Classifier (APC), and our results show that APC outperforms ``traditional'' techniques -- like 1-nearest-neighbour and Support Vector Machines -- and we also show that performance of APC are comparable to several state of the art face verification algorithms. The results here presented let us conclude that swarm intelligence approaches represent a very promising direction for further investigations for biometrics verification and identification

Biometrics-as-a-Service: A Framework to Promote Innovative Biometric Recognition in the Cloud

Biometric recognition, or simply biometrics, is the use of biological attributes such as face, fingerprints or iris in order to recognize an individual in an automated manner. A key application of biometrics is authentication; i.e., using said biological attributes to provide access by verifying the claimed identity of an individual. This paper presents a framework for Biometrics-as-a-Service (BaaS) that performs biometric matching operations in the cloud, while relying on simple and ubiquitous consumer devices such as smartphones. Further, the framework promotes innovation by providing interfaces for a plurality of software developers to upload their matching algorithms to the cloud. When a biometric authentication request is submitted, the system uses a criteria to automatically select an appropriate matching algorithm. Every time a particular algorithm is selected, the corresponding developer is rendered a micropayment. This creates an innovative and competitive ecosystem that benefits both software developers and the consumers. As a case study, we have implemented the following: (a) an ocular recognition system using a mobile web interface providing user access to a biometric authentication service, and (b) a Linux-based virtual machine environment used by software developers for algorithm development and submission

Silhouette-based gait recognition using Procrustes shape analysis and elliptic Fourier descriptors

This paper presents a gait recognition method which combines spatio-temporal motion characteristics, statistical and physical parameters (referred to as STM-SPP) of a human subject for its classification by analysing shape of the subject's silhouette contours using Procrustes shape analysis (PSA) and elliptic Fourier descriptors (EFDs). STM-SPP uses spatio-temporal gait characteristics and physical parameters of human body to resolve similar dissimilarity scores between probe and gallery sequences obtained by PSA. A part-based shape analysis using EFDs is also introduced to achieve robustness against carrying conditions. The classification results by PSA and EFDs are combined, resolving tie in ranking using contour matching based on Hu moments. Experimental results show STM-SPP outperforms several silhouette-based gait recognition methods

Service Integration for Biometric Authentication

Unimodaalsete biomeetriliste süsteemide kasvav kasutuselevõtt era- ja riigiasutustes näitab biomeetriliste autentimissüsteemide edu. See aga ei tähenda, et biomeetrilised süsteemid pakuvad terviklikku autentimislahendust. Unimodaalsetes biomeetrilistes süsteemides ilmneb hulk piiranguid, mida on võimalik ületada kasutades multimodaalseid biomeetrilisi autentimissüsteeme. Multimodaalseid süsteeme peetakse töökindlamaks ja võimeliseks rahuldama rangeid jõudlusvajadusi. Lisaks võimaldavad multimodaalsed süsteemid arvestada mitteuniversaalsuse probleemiga ja tõhusalt tõrjuda võltsimisrünnakuid. Vaatamata suhtelistele eelistele on multimodaalsete biomeetriliste süsteemide realisatsioon ja kasutusmugavus jäänud fundamentaalseks väljakutseks tarkvaraarenduses. Multimodaalsed süsteemid on enamasti sulam unimodaalsetest süsteemidest, mis on valitud vastavalt äriprotsessi ja vaadeldava keskkonna nõuetele. Nende süsteemide mitmekesisus, lähtekoodi kättesaadavus ja juurutamisvajadused muudavad nende arenduse ja kasutuselevõtu oluliselt kulukamaks. Tarkvaraarendajatena üritame me lihtsustada arendusprotsessi ja minimeerides selleks vajamineva jõupingutuse suurust. Seetõttu keskendub see töö olemasolevate biomeetriliste süsteemide taaskasutatavaks muutmisele. Eesmärgiks on kirjeldada teenuste integratsiooni raamistik, mis automatiseerib heterogeensete biomeetriliste süsteemide sujuvat seadistamist ja paigaldust ning vähendab arenduse töömahtu ja sellega seotud kulutusi. Selle eesmärgi saavutamiseks kõrvaldame me vajaduse korduva stsenaariumipõhise ühilduvate süsteemide arenduse ja integratsiooni järgi. Biomeetriliste süsteemide arendus muudetakse ühekordseks tööks. Me esitleme ka vahendeid heterogeensetest avatud lähetekoodiga ja kommerts biomeetrilistest süsteemidest koosnevate multimodaalsete biomeetriliste süsteemide seadistamiseks ja paigaldamiseks lähtuvalt valdkonnaspetsiifilistest autentimisvajadustest. Võrreldes levinud praktikatega vähendab meie lähenemine stsenaariumi-spetsiifilise biomeetrilise autentimissüsteemi arendusele ja paigaldusele kuluvat töö hulka 46,42%.The success of biometric authentication systems is evident from the increasing rate of adoption of unimodal biometric systems in civil and governmental applications. However, this does not imply that biometric systems offer a complete authentication solution. Unimodal biometric systems exhibit a multitude of limitations which can be overcome by using multimodal biometric authentication systems. Multimodal systems are considered more reliable, and capable of meeting stringent performance needs and addressing the problem of non-universality and spoof attacks effectively. Despite the relative advantages, implementation and usability of multimodal biometric systems remain a fundamental software engineering challenge. Multimodal systems are usually an amalgamation of unimodal biometric systems chosen in accordance with the needs dictated by the business process(es) and the respective environment under consideration. The heterogeneity, availability of source code, and deployment needs for these systems incur significantly higher development and adaption costs. Being software engineers, we naturally strive to simplify the engineering process and minimize the required amount of effort. Therefore this work focuses on making the existing biometric systems reusable. The objective is to define a service integration framework which automates seamless configuration, and deployment of heterogeneous biometric systems, and minimizes the development effort and related costs. In this effort we replace the need for development and integration of scenario-specific compatible systems by repetitive scenario-specific configuration and deployment of multimodal biometric systems. The development of biometric systems is minimized to a one-time effort. We also present tools for configuration and deployment, which respectively configure and deploy multimodal biometric systems comprising of heterogeneous open source and/or commercial biometric systems required for fulfillment of domain specific authentication needs. In comparison to the prevalent practices, our approach reduces the effort required for developing and deploying reliable scenario-specific biometric authentication systems by 46.42%

Genetic Programming for Multibiometrics

Biometric systems suffer from some drawbacks: a biometric system can provide in general good performances except with some individuals as its performance depends highly on the quality of the capture. One solution to solve some of these problems is to use multibiometrics where different biometric systems are combined together (multiple captures of the same biometric modality, multiple feature extraction algorithms, multiple biometric modalities...). In this paper, we are interested in score level fusion functions application (i.e., we use a multibiometric authentication scheme which accept or deny the claimant for using an application). In the state of the art, the weighted sum of scores (which is a linear classifier) and the use of an SVM (which is a non linear classifier) provided by different biometric systems provide one of the best performances. We present a new method based on the use of genetic programming giving similar or better performances (depending on the complexity of the database). We derive a score fusion function by assembling some classical primitives functions (+, *, -, ...). We have validated the proposed method on three significant biometric benchmark datasets from the state of the art

The Horcrux Protocol: A Method for Decentralized Biometric-based Self-sovereign Identity

Most user authentication methods and identity proving systems rely on a centralized database. Such information storage presents a single point of compromise from a security perspective. If this system is compromised it poses a direct threat to users' digital identities. This paper proposes a decentralized authentication method, called the Horcrux protocol, in which there is no such single point of compromise. The protocol relies on decentralized identifiers (DIDs) under development by the W3C Verifiable Claims Community Group and the concept of self-sovereign identity. To accomplish this, we propose specification and implementation of a decentralized biometric credential storage option via blockchains using DIDs and DID documents within the IEEE 2410-2017 Biometric Open Protocol Standard (BOPS)

Bio : A Mulrimodal biometric authentication system for person identification and verification

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