A Novel Multimodal Biometric Authentication System Using Machine Learning and Blockchain

Secure user authentication has become an important issue in modern society as in many consumer applications, especially financial transactions, it is extremely important to prove the identity of the user. In this context, biometric authentication methods that rely on physical and behavioural characteristics have been proposed as an alternative for convolutional systems that rely on simple passwords, Personal Identification Number or tokens. However, in real-world applications, authentication systems that involve a single biometric faced many issues, especially lack accuracy and noisy data, which boost the research community to create multibiometric systems that involve a variety of biometrics. Those systems provide better performance and higher accuracy compared to other authentication methods. However, most of them are inconvenient and requires complex interactions from the user. Thus, in this paper, we present a multimodal authentication system that relies on machine learning and blockchain, intending to provide a more reliable, transparent, and convenient authentication mechanism. The proposed system combines tow important biometrics: fingerprint and face with age, and gender features. The supervised learning algorithm Decision Tree has been used to combine the results of the biometrics verification process and produce a confidence level related to the user. The initial experimental results show the efficiency and robustness of the proposed systems

Biometric Authentication Using Fused Multimodal Biometric

AbstractBiometrics are basically based on the expansion of pattern recognition systems. At present, electronic or optical sensors like cameras and scanning devices are used to capture images, recordings or measurements of a person's ‘unique’ characteristics. These technologies are being utilized across a range of applications like security, prevention of cyber crime and border control, public aid/social benefits, customs, immigration, passport and healthcare identity verification, as well as commercial enterprises use. Most biometric systems that are typically use a single biometric trait to establish identity have some challenges like Noise in sensed data which increases False Acceptance Rate (FAR) of the system, Non-universality which reduces Genuine Acceptance Rate (GAR). Hence the security afforded by the biometric system mitigates its benefits. In this paper, we propose a Fused Multimodal systems which also have several advantages over unibiometric systems such as, enhanced verification accuracy, larger feature space to accommodate more subjects and higher security against spoofing. The proposed enhanced multimodal authentication system is based on feature extraction(using fingerprint, retina and fingervein) and key generation (using RSA). The experimental evaluation implemented using MATLAB 2014, illustrates the significance improvement in the performance of multimodal biometrics with RSA have GAR of 95.3% and FAR of 0.01%

Wireless power charging and identification of theft electric vehicle using Block chain technology

Abstract Vehicles have become an indispensable part of every human’s life. Almost, every work depends on vehicle for transportation. Without the vehicle our work would be crucial. Though a vehicle have many benefits, it also creates a major threat for the environment by its pollution. Additionally, the existing system fails to charge the Electric Vehicle (EV) system as there is no separate charging system. This can be implemented by our proposed system wireless power charging technology using inductive coupling method. Consequently, existing system also fails to identify the theft EV in an efficient manner. This issues can be solved by using a mobile application with vehicle information. The application maintains the blockchain server which continuously monitors theft Electric Vehicle by sending, vehicle information to all rechargeable stations. In case, the theft Electric Vehicle enters the charging station the information is passed to the authorized person of the Electric Vehicle. As a result the proposed system integrates Wireless charging and anti-theft vehicle in an efficient way when compared with the existing system.</jats:p