An Evaluation of Score Level Fusion Approaches for Fingerprint and Finger-vein Biometrics

Biometric systems have to address many requirements, such as large population coverage, demographic diversity, varied deployment environment, as well as practical aspects like performance and spoofing attacks. Traditional unimodal biometric systems do not fully meet the aforementioned requirements making them vulnerable and susceptible to different types of attacks. In response to that, modern biometric systems combine multiple biometric modalities at different fusion levels. The fused score is decisive to classify an unknown user as a genuine or impostor. In this paper, we evaluate combinations of score normalization and fusion techniques using two modalities (fingerprint and finger-vein) with the goal of identifying which one achieves better improvement rate over traditional unimodal biometric systems. The individual scores obtained from finger-veins and fingerprints are combined at score level using three score normalization techniques (min-max, z-score, hyperbolic tangent) and four score fusion approaches (minimum score, maximum score, simple sum, user weighting). The experimental results proved that the combination of hyperbolic tangent score normalization technique with the simple sum fusion approach achieve the best improvement rate of 99.98%.Comment: 10 pages, 5 figures, 3 tables, conference, NISK 201

Multi-biometric templates using fingerprint and voice

As biometrics gains popularity, there is an increasing concern about privacy and misuse of biometric data held in central repositories. Furthermore, biometric verification systems face challenges arising from noise and intra-class variations. To tackle both problems, a multimodal biometric verification system combining fingerprint and voice modalities is proposed. The system combines the two modalities at the template level, using multibiometric templates. The fusion of fingerprint and voice data successfully diminishes privacy concerns by hiding the minutiae points from the fingerprint, among the artificial points generated by the features obtained from the spoken utterance of the speaker. Equal error rates are observed to be under 2% for the system where 600 utterances from 30 people have been processed and fused with a database of 400 fingerprints from 200 individuals. Accuracy is increased compared to the previous results for voice verification over the same speaker database

Using biometrics authentication via fingerprint recognition in e-Exams in e-Learning environment

E-learning is a great opportunity for modern life. Notably, however, the tool needs to be coupled with efficient and reliable security mechanisms to ensure the medium can be established as a dependable one. Authentication of e-exam takers is of prime importance so that exams are given by fair means. A new approach shall be proposed so as to ensure that no unauthorised individuals are permitted to give the exams

Intensifying the Security of Multiomodal Biometric Authentication System using Watermarking

In Multimodal biometrics system two or more biometric attributes are combined which makes it far more secure than unimodal system as it nullifies all the vulnerabilities of it. But with the prompt ontogenesis of information technology, even the biometric data is not secure. There is one such technique that is implemented to secure the biometric data from inadvertent or deliberate attacks is known as Digital watermarking. This paper postulate an approach that is devise in both the directions of enlarging the security through watermarking technique and improving the efficiency of biometric identification system by going multimodal. Three biometric traits are consider in this paper two of them are physical traits i.e. ; face, fingerprint and one is behavioral trait (signature).The biometric traits are initially metamorphose using Discrete Wavelet and Discrete Cosine Transformation and then watermarked using Singular Value Decomposition. Scheme depiction and presented results rationalize the effectiveness of the scheme

Biometric Template Spoofing Detection Using Sparse Watermarking Scheme

No Abstrac

Biometric Privacy Protection based on Combination of Hiding and Chaotic Encryption

 نتيجة لاستخدام أنظمة القياسات الحيوية بكثرة، أصبحت سلامة ميزة القياسات الحيوية ذات أهمية كبيرة. عندما يتم نقل الصور البيومترية عبر قنوات غير آمنة أو تخزينها كبيانات أولية ، فإنها تصبح عرضة لخطر السرقة والتزوير والهجوم. يعد إخفاء البيانات أحد الأساليب الرئيسية لحماية الخصوصية. الهدف من إخفاء البيانات البيومترية هو تضمين البيانات الشخصية ززفي غلاف القياسات الحيوية والحفاظ على أداء التعرف. تقدم الفكرة الورقية مستويين من الأمان يعتمدان على الإخفاء والتشفير. يتم تجزأت صورة العين إلى جزئيين او منطقتين هما  (ROI)  (NROI) وبقصد بهما منطقة مهمة ومنطقة غير مهمة .يتم تضمين بيانات الخصوصية مع NROI ثم إعادة تجميع الصورة باستخدام ROI  للقزحية للحصول على صورة مدمجة. ثم يتم تطبيق التشفير العشوائي على الصورة المضمنة للحصول على مستوى عالٍ من الأمان. تم اختبار النتائج التجريبية باستخدام مجموعة بيانات CASIA1.تم استخدام مقياسيين هما PSNR و NC. أظهرت نتائج الاختبار قيمة عالية لل  PSNR مما يعني احتفاظ صورة الغلاف بجودتها وقيمة NC هي (1) مما يعني استرجاع مثالي للبيانات السرية. كما وتم اختبار طريقة التشفير باستخدام قياسات مثل الرسم البياني والارتباط والنتروبيا وجميع النتائج كانت جيدة.With the expanded use of biometric systems, the safety of the biometric feature has become increasingly important. When biometric images are transferred through unsafe channels or stored as raw data, they become at risk of theft, forgery and attack. Data hiding is one of the main techniques of Privacy Protection. The goal of biometric data hiding is for adequate personal data is to be included in the cover of Biometrics and to maintain recognition performance. The paper idea introduces two levels of security based on hiding and encryption. The eye image is segmented into two regions Region of Interest (ROI) and Non-Region of Interest (NROI), The iris segmentation method depends on the Circular Hough Transform (CHT). The privacy data is embedded with NROI and then reassemble the image with ROI (iris) to get the embedding image. Then chaotic encryption is applied on the embedded image to get a high level of security. The experimental results are tested using the CASIA1 data set. The tests of hiding level are done using measurements such as PSNR and NC. The results show that the suggested method gives a higher value of PSNR which means not destroy the cover image and the value of NC is (1) which means a perfect reconstruction of secret data. The tests on encryption levels show good results using measurements such as histogram, correlation, and entropy

Conceivable security risks and authentication techniques for smart devices

With the rapidly escalating use of smart devices and fraudulent transaction of users’ data from their devices, efficient and reliable techniques for authentication of the smart devices have become an obligatory issue. This paper reviews the security risks for mobile devices and studies several authentication techniques available for smart devices. The results from field studies enable a comparative evaluation of user-preferred authentication mechanisms and their opinions about reliability, biometric authentication and visual authentication techniques