Biometric Security System Research Articles

A SIGNATURE IDENTIFICATION SYSTEM WITH PRINCIPAL COMPONENT ANALYSIS AND STENTIFORD THINNING ALGORITHMS

Several biometric security systems have been implemented. Biometric is the use of a person’s physiological or behavioural characteristics to identify the individual. An example of behavioural method of biometric is signature identification. Signature identification is the use of handwritten signature to identify a person. This paper attempt design and implement an algorithm for handwritten signature identification. The signature identification system consists of signature acquisition, preprocessing, features extraction and matching stages. Signature acquisition can be either online or offline (both were considered in this research work). Online signatures are obtained by signing on digital tablets while offline signatures are scanned (or snapped) into the system. Preprocessing stage of the system include turning the image to greyscale. The grey image is further converted to binary (black and white). The image is then thinned, using Stentiford thinning algorithm. Stentiford thinning algorithm in an iterative thinning method with a good thinned imaged output. The image is finally cropped to rid the image of unnecessary white spaces. For features extraction, principal component analysis is used. Principal Component Analysis is a good statistical tool for identifying pattern in data. Features extracted from each signature are stored as a template. After features extraction, the distance between signature templates are computed using Manhattan distance. If the distance exceeds a certain threshold, the test signature is rejected (otherwise it is accepted). The design system has a FAR of 4% and an FRR of 6% for offline signatures. A FAR of 2% and an FRR of 3% were obtained for online signatures

Security System in ATM using MultimodalBiometric System and SteganographicTechnique

The paper proposes to implement the biometric security system based on combination of iris and palm print with Steganographic technique for authentication purpose. Here the data hiding approach involves to conceal secret personal informatics within their biometric for still enhance the privacy protection. A Biometric system is essentially a pattern recognition system that makes use of biometric traits to recognize individuals. The most unique phenotypic feature visible in a person's face is the detailed texture of each eye's iris. Palm is the inner surface of a hand between the wrist and the fingers. Palm print is referred to principal lines, wrinkles and ridges on the palm. This system proposes a multi-resolution approach based on Wavelet Packet Transform (WPT) for texture analysis of iris and Weber’s local descriptors based texture analysis of palm print will be proposed here. Weber local descriptor is used to represents the changes of illumination in an image and it determines the features such as differential excitation and gradient orientation. The development of this approach is motivated by the observation that dominant frequencies of iris texture are located in the low and middle frequency channels. The hand palm print image is aligned and cropped according to the key points. The palm print image is enhanced and resized. The features of palm print and iris are fused then compared with database image feature vectors and its recognized using Euclidean or Hamming distance. If this module is completed successfully then person information which contains person authentication number with four digits key will be matched with extracted data from already hidden image for second level security. Crime which is happening in ATM became a serious issue that affects not only customers but also bank operators. The main solution to this problem is Multimodal biometrics. Finally the multimodal system along with Steganographic approach shows the better performance accuracy for this automatic identification and authentication in ATM system.

Entropy Measurement for Biometric Verification Systems.

Biometric verification systems are designed to accept multiple similar biometric measurements per user due to inherent intrauser variations in the biometric data. This is important to preserve reasonable acceptance rate of genuine queries and the overall feasibility of the recognition system. However, such acceptance of multiple similar measurements decreases the imposter's difficulty of obtaining a system-acceptable measurement, thus resulting in a degraded security level. This deteriorated security needs to be measurable to provide truthful security assurance to the users. Entropy is a standard measure of security. However, the entropy formula is applicable only when there is a single acceptable possibility. In this paper, we develop an entropy-measuring model for biometric systems that accepts multiple similar measurements per user. Based on the idea of guessing entropy, the proposed model quantifies biometric system security in terms of adversarial guessing effort for two practical attacks. Excellent agreement between analytic and experimental simulation-based measurement results on a synthetic and a benchmark face dataset justify the correctness of our model and thus the feasibility of the proposed entropy-measuring approach.

Biometric security system over finite field for mobile applications

Recently, number of mobile users and mobile banking applications are increased dramatically. The current mobile banking system unable to provide face-to-face transaction, that is, anyone can perform transaction by using proper secret code. This study proposes a new triangular based indexing method to authenticate the original account holder in mobile banking environment. A Delaunay triangulation indexing scheme has been designed for protecting biometric template and Voronoi vertex is calculated for verifying the authorised person. A novel algorithm has been developed for mutual authentication. To reduce key size, elliptic curve cryptography technique is adapted. Biometric key is generated for secure communication and also discusses the security aspects of the proposed method.

Security of Biometric Systems

There are many ways how to identify people and to provide their authorization of access to a specific area. This article describes the reliability of biometric systems that are commonly used to identify of people. The article aims to highlight the ways in which to disturb the security of biometric systems. There are describes techniques that can impair the reliability of equipment for fingerprinting. To test the reliability of the fingerprint was made series of measurements; the results are presented in the article.

Biometric Security System for Watchlist Surveillance

We propose a biometric security system to identify miscreants (Watchlist person) whose information is already provided in the database. With huge volumes of information being brought forth from these surveillance cameras, methods are needed to automatically analyze these surveillance videos. In our approach we combined Principal Component Analysis (PCA) with Nearest Neighbor replacing threshold value by confidence value. The proposed approach works with only one image per person. We are able to reduce recognition time and an alarm needs to be generated as soon as a Watchlist person is caught in the video.

Palm and hand vein-based fuzzy vault generation scheme for multibiometric cryptosystem

Template security of biometric systems is a vital issue and needs critical focus. The importance lies in the fact that unlike passwords, stolen biometric templates cannot be revoked. Hence, the biometric templates cannot be stored in plain format and needs strong protection against any forgery. In this paper, we present a technique to generate face and palm vein-based fuzzy vault for multi-biometric cryptosystem. Here, initially the input images are pre-processed using various processes to make images fit for further processing. In our proposed method, the features are extracted from the processed hand and palm vein images by finding out unique common points. The chaff points are added to the already extracted points to obtain the combined feature vector. The secret key points which are generated based on the user key input (by using proposed method) are added to the combined feature vector to have the fuzzy vault. For decoding, the multi-modal biometric template from palm vein and hand vein image is constructed and is combined with the stored fuzzy vault to generate the final key. Finally, the experimentation is conducted using the palm vein and hand vein database. The evaluation metrics employed are FMR (False Match Ratio) and GMR (Genuine Match Ratio). From the metric values obtained for the proposed system, we can infer that the system has performed well. The results are also compared to our earlier technique and the results shows that the proposed technique has achieved better results having GAR of 94% without noise and 88% with noise.

Cellular Automata based Encrypted ECG-hash Code Generation: An Application in Inter human Biometric Authentication System

Abstract —In this modern era, biometrics incorporate various mechanisms to recognize inimitable features of human beings by utilizing their biological and evident features. This paper proposes a novel technique for constructing a resilient and secure biometric recognition system. In this paper, an ECG-hash code of two distinct individuals has been formed by taking dot product of electrocardiogram (ECG) feature matrices of two persons located at two different sites at respective databases. The validity of the system increases as samples from both persons, between whom the transmission takes place, are essential. Besides, electrocardiogram is such a unique feature of an individual that could not be compromised at any circumstance as contradictory to other features like fingerprints, face recognition etc. Moreover, the ECG-hash code is encrypted using rule vector of cellular automata that gives better security in terms of randomness of generated cipher text.

Affect-insensitive speaker recognition systems via emotional speech clustering using prosodic features

Voice-based biometric security systems involving only neutral speech have achieved promising performance. However, the speakers are very likely to fail the recognition when the test data exhibit multiple emotions. This paper aimed to address the mismatch of the emotional states between training and testing speech. We discuss different modeling strategies that incorporate the emotions (affects) of speakers into the training stage of a Mandarin-based speaker recognition system and propose an alternative approach, which could optimize the utilization of the limited affective speech. The training speeches are partitioned and clustered by the trends of the prosodic variations. Multiple models are built based on the clustered speech for a given speaker. The prosodic differences are characterized by a combination of features that describe the changes of the fundamental frequencies and energy contours. The experiments were carried out based on the Mandarin Affective Speech Corpus. The result shows 73.37 % improvement in recognition rate over that of the traditional speaker verification tasks relatively and also achieves 63.53 % higher in performance over the structural training-based systems relatively.

Biometric tech meets further resistance in the US education sector

Biometric technology continues to meet resistance in the US education sector, following Florida's ban on the collection of biometric data from school children. The University of Georgia (UGA)'s news publication Red and Black reports that biometric building security systems, which had been operated by hand scan since the 1970s, have been replaced on hygiene grounds.

Iris Biometric Authentication used for Security Systems

Pupil detection and iris localisation using scanning method and feature extraction is performed with five level decomposition techniques, with these two proposed algorithm we could achieve efficient and fast person authentication in biometric security systems. Statistical performance evaluation is also performed using parameters False acceptance rate (FAR), False rejection rate (FRR), Correct recognition rate (CRR), Equal error rate (EER), Match ratio etc, using CASIA database.

UNCONSTRAINED IRIS AUTHENTICATION THROUGH FUSION OF RGB CHANNEL INFORMATION

The unique iris pattern of each human eye is complex, but easily be scanned or captured by a camera. However, the high cost infrared iris scanners used for acquisition causes inconvenience to users by distance related constraints. This restricts its widespread use in real-time applications such as airports and banks. The images captured by cameras under visible wavelength are obstructed by the presence of reflections and shadows which requires additional attention. The main objective of this paper is to propose a secure biometric iris authentication system by fusion of RGB channel information from the real-time data captured under visible wavelength and varying light conditions. The proposed system is adapted to a real-time noisy iris dataset. The effectiveness of this proposed system was tested on two different color iris datasets, namely, a public database UBIRISv1 and a newly created database SSNDS which contains images captured with any digital/mobile camera of minimum 5MP under unconstrained environments. This system supports the cross sensor acquisition and successful iris segmentation from these unconstrained inputs. The features from each channel are extracted using log Gabor filter and a matching is performed using hamming distance based on two thresholds (inter and intra class variations). The performance quality of the proposed biometric system leads to the feasibility of a new cost-effective approach for any real-time application, which requires authentication to ensure quality service, enhance security, eliminate fraud, and maximize effectiveness.

Technique to generate face and palm vein-based fuzzy vault for multi-biometric cryptosystem

Template security of biometric systems is a vital issue and needs critical focus. The importance lies in the fact that unlike passwords, stolen biometric templates cannot be revoked. Hence, the biometric templates cannot be stored in plain format and needs strong protection against any forgery. In this paper, we present a technique to generate face and palm vein-based fuzzy vault for multi-biometric cryptosystem. Here, initially the input images are pre-processed using various processes to make images fit for further processing. In our proposed method, the features are extracted from the processed face and palm vein images by finding out unique common points. The chaff points are added to the already extracted points to obtain the combined feature vector. The secret key points which are generated based on the user key input (by using proposed method) are added to the combined feature vector to have the fuzzy vault. For decoding, the multi-modal biometric template from palm vein and face image is constructed and is combined with the stored fuzzy vault to generate the final key. Finally, the experimentation is conducted using the palm vein and face database available in the CASIA and JAFFE database. The evaluation metrics employed are FMR (False Match Ratio) and GMR (Genuine Match Ratio). From the metric values obtained for the proposed system, we can infer that the system has performed well.

Distributed Face Recognition in Wireless Sensor Networks

As one of the most successful applications of image analysis and understanding, face recognition has recently received significant attention, especially during the past few years. In order to construct an autonomous and robust biometric security system, this paper explores the application of face recognition technique in wireless sensor networks. Given the limited technological resources of sensor nodes, new challenges remain to be met. In this work, a facial component-based recognition mechanism is firstly applied to ensure the recognition accuracy. Secondly, in order to address the problem of resource constraints, a distributed scheme based on K-d trees is deployed for both the face image transmission and retrieval. According to the simulation results, the proposed method is capable of achieving considerable energy efficiency, while assuring the recognition accuracy.

Mobile Multimodal Biometric System for Security

Among our huge life requirements, the most important requirement which has a vital role in our daily life is the security. Recently using biometrics in the security systems has a wide range of research interests since they provide systems have more efficient, reliable, and secure than the others. In the present time researches for mobile biometric devices are provided with a fingerprint only which isn’t sufficient for the areas where lawlessness and anarchy cases are existed recently due to the current political situation in some developing countries in Africa and Middle East where the rate of crime increased significantly involving a large number of people getting into the crime scene. Police departments are unable to identify robbers and criminals due to the presence of newly unrecorded ones with the lack of presence of a fixed database holding records of widely known criminals. So in this paper we propose a mobile biometric authentication system (MOBAS) based on Zigbee technology and a multimodal biometric authentication system in which the primary biometric modalities adopted are the fingerprint and the face recognition. The proposed system aims to provide a mobile, light, user friendly, reliable and secure biometric authentication system to the police departments, and that will help the officers anywhere to identify the criminals by taking a fingerprint or capturing an image or both for different scenarios, sending them wirelessly to the server at the appropriate police station and then waiting for a response concerning the person’s criminal record sent wirelessly from the police station and displayed on a mobile biometric authentication device (MOBA). According to the sent criminal record, the police officers will take a suitable action towards this person.

Impact of Changing Parameters when Preprocessing Dorsal Hand Vein Pattern

Dorsal hand vein biometric has been the driving force for many researchers lately. The latters have adopted several approaches for preprocessing the vein pattern, extracting its features and matching. Preprocessing steps play an important role in a biometric security system since it allows obtaining the features required for later stages.In line with this, the preprocessing steps of the dorsal hand vein pattern are being scrutinized in a view of procuringideal vein features. Recently more attention is being given to processing and matching stages of a biometric security system. It is therefore mandatory to investigate on the preprocessing factors that affect the performance of a biometric system. Thus, in this work, different preprocessing techniques are being investigated.A database of 500 images is considered for which same number of images and instances are used. Through experimentation, it is found that different techniques give different results which have an impact on the later stages. The result proves that a well-defined extracted vein pattern gives better performance and leads to a more secure biometric authentication system.

Analysing Factors Affecting Hand Biometrics during Image Capture

As more people are connected digitally, a highly automatic personal identification system is crucial. Dorsal hand vein biometric is an emerging biometric characteristic which is explored at its full swing. Although, researchers have deployed many hand biometrics using interesting techniques, it has not yet been accepted in many applications. Images capture is an important phase where the images obtained determine the performance of the biometric security system. Environmental factors and behavior of the subjects have an effect on image capture. In these work, different variables, that is, distance between camera and hand, the angle of deviation and the environmental temperature are controlled to capture images. The results are analysed and the effect of the variables have been depicted. It is deduced that image capture phase in biometric applications deserve more attention.

BSC: A Novel Scheme for Providing Security using Biometric Smart Card

Technology advances day by day and the new things are being developed. There are many new technologies being introduced and developed in any discipline. Data Security plays a vital role and Biometric security systems is one of the new trends to be developed, which has its advantages for controlling access, protecting sensitive data, tracking on-line systems, etc.,. Biometric technologies such as fingerprint, face and iris recognition have seen an increasing interest throughout the past decades to increase the security, convenience, accountability. Such interest has been intensified with various large-scale initiatives from governments that seek to incorporate biometric technologies for the purposes of identification, verification and for fraud detection and deterrence. Being purely ad hoc technological implementations, biometric devices are now seen as being of strategic value and consequently of strategic importance. With the perception of better efficiency and effectiveness, governments are beginning to embrace biometric technologies. Industry is also geared up to sell the products, and all over the world businesses are looking to incorporate biometrics for many different uses ranging from accesscontrol to e-commerce and entertainment. Biometrics and smart cards are two of the most powerful security solutions available today. This paper introduces a new mechanism to provide better security and services with Biometric Smart Card technology including hybrid biometric security, i.e., with the combination of security for fingerprint pattern and for the smart card. General Terms BSC, NFC, PIN, X.509, Authentication, Security Mechanism, RSA Algorithm, Cyber Forensics.

Cancelable Fusion of Face and Ear for Secure Multi-Biometric Template

Biometric fusion to achieve multimodality has emerged as a highly successful new approach to combat problems of unimodal biometric system such as intraclass variability, interclass similarity, data quality, non-universality, and sensitivity to noise. The authors have proposed new type of biometric fusion called cancelable fusion. The idea behind the cancelable biometric or cancelability is to transform a biometric data or feature into a new one so that the stored biometric template can be easily changed in a biometric security system. Cancelable fusion does the fusion of multiple biometric trait in addition it preserve the properties of cancelability. In this paper, the authors present a novel architecture for template generation within the context of the cancelable multibiometric fusion. The authors develop a novel cancelable biometric template generation algorithm using cancelable fusion, random projection and transformation-based feature extraction and selection. The authors further validate the performance of the proposed algorithm on a virtual multimodal face and ear database.

Integrating Cancellable Biometrics with Geographical Location for Effective Unattended Authentication of Users of Mobile Devices

Over the past decade, security and privacy concerns about the growing deployment of biometrics as a proof of identity have motivated researchers to investigate solutions such as cancellable biometrics to enhance the security of biometric systems. However, the open nature of newly emerged mobile authentication scenarios has made these solutions impractical and necessitated the need for new innovative solutions. This paper proposes an effective authentication scheme for remote users on mobile-handsets. The proposal incorporates cancellable biometrics with actual mobile-handset location to produce a one-time authentication token. For added security, the location is obtained and verified via two independent sources, and the authentication token is robustly stamped by the transaction time to guarantee the liveliness. This makes the proposed scheme immune against replay and other remote fraudulent attacks. Trials and simulations based on using biometric datasets and real GPS/Cellular measurements show the viability of our scheme for unattended and mobile authentication. 