Engineering Graphical Captcha and AES Crypto Hash Functions for Secure Online Authentication

Password alone is currently not trusted for user online authentication and security as threats from hackers continue to grow, requiring highly efficient defense safeguard protection against unauthorized users. Therefore, CAPTCHA techniques came into the picture as an automated assistance to distinguish between humans and robots. The CAPTCHA has several applications in the online security domain requiring to be merged with encrypted hash function benefitting from the facility of the graphical password schemes. This paper proposes engineering an authentication technique using graphical CAPTCHA with an AES encrypted hash password to maintain applicable security accessing systems. We propose three layered security system that joins highly efficient security mechanisms to avoid users’ stress of entering password many times or different other hectic routines in order to save account accessing.

An automation API for authentication and security for file uploads in the cloud storage environment

Cloud Computing is widespread to support industrial and academy related applications worldwide. The archival data process in the cloud is one of the challenging tasks. To handle this issue, the authors addressed the model, which allows authenticating the cloud storage using the JOSS (Java Library for Open stack storage) through the authentication URL. To achieve the authentication of the heterogeneous data while uploading into the cloud storage, a proposed model developed using the JOSS. To address this research question and demonstrate our approach, we have created the API for the archival solution in order to authenticate the cloud storage using the JOSS authentication model, providing the authentication URL. It consists of the user id and password for the verification of the user while transmitting the data into the cloud storage. The API is becoming dynamic and complex, and one of the major challenges faced by the developer in order to develop appropriate standalone applicataion interface. The extensible mechanism for authentication requires a URL in order to connect to the cloud storage system. The objective of this paper is to enhance/optimize the rate of transmission to upload the data in the cloud storage using the rclone.

Using Deep Learning to Recognize People by Face and Voice

There are many ways to build a person identification system and those systems can be used for authentication and security. The latest phones for example, bring fingerprint readers to enhance the user experience. From our perspective on Neural Networkswe determine that Machine Learning is enough to guarantee someone’s identity without the need of any specific sensors other than a camera and a microphone. It is achievable with pictures of their face, sounds of their voice and Deep Learning. This work presents a study to build an application to allow biometric authentication using only multimedia and Deep Learning.

Web based fingerprint roll call attendance management system

Managing people and keeping adequate record of the attendance for most of the tertiary institutions are difficult task. Moreover, the manual taking of attendance adds to the difficulty of this task because it is strenuous, time intensive and can easily be falsified. Meanwhile, With the advent of new technology, a new world of authentication and security has been created via biometrics. This work aims at improving Covenant Universities paper-based attendance by using biometrics, specifically fingerprint technology. It is a web application that works with a fingerprint reader from which the features of the student’s fingerprint are extracted during enrolment. This is also needed during the authentication phase which occurs during the roll call attendance in the halls of residence. It is implemented using PHP and MySQL.

Biometric Authentication and Identification using Behavioral Biometrics Technique of Signature Verification

Authentication using biometrics is on the rise due to various security concerns and especially in India with the advent of Digital India concept promoting the wide use of aadhar as an authentication mechanism. The authentication using a login and a password are fading away due to the various malpractices and fraudulent methods that have been developed which pose a threat to this kind of authentication and security mechanism. Signature verification is one of the important aspects of biometric authentication which is slowly finding its use in certain niche organizations. The present study uses an ensemble approach, stacking to authenticate or validate a user by his signature and proposes a hybrid model using three algorithms namely, Random Tree, Logistic Regression & Multi-Layer Perceptron for achieving better accuracy.