In today's information technology world, cloud computing plays a major role. Cloud computing is dynamically flexible as well as sizable and cost-efficient including important virtual tools. Data security is the main concern in cloud computing. Different encryption techniques have been introduced to secure cloud computing, but the data is constantly under threat due to security exploits. This paper presents a hybrid Crypto method using updated RSA and TWOFISH algorithms to protect data integrity and security in cloud computing. The proposed technique is robust, fast and demonstrates better performance results. This research also highlights many security risks and solutions in cloud computing.
The rail transportation system is crucial to the growth of any developing nation. Thus, there is a need to optimize the processes surrounding rail transportation, such as purchasing train tickets. The process of purchasing tickets manually at Nigerian railway stations is prone to ticket racketeering. Online ticketing systems have proven to be effective in other transportation systems such as the air transportation system. Therefore, implementing a web-based system for the ticketing process of rail transportation in Nigeria will solve the problem of ticket racketeering. The system is implemented using HTML, PHP, CSS, JQuery, JavaScript and Bootstrap with Quick Response (QR) codes for the process of ticket verification. Evidently, the system is reliable and recommended for use in ticket booking and reservation for rail transportation in Nigeria as it will contribute immensely to the economic growth of the country.
This work focuses on the design and implementation of a fingerprint biometric identification system for charging and discharging library materials. Charging of library materials denotes lending or borrowing of library materials, however discharging is done when the patron or borrower return the borrowed library material. The crux of charging and discharging library materials is the means to identify the borrower and the book borrowed amidst great number of library patrons and huge collection in the library. Many methods of charging and discharging have been developed over the years. Most of these methods use a borrower's & book's card as means of identification, until the advent of the automated system. This work is aimed at using fingerprint identification as a veritable method for patron's identification during charging of library materials. It covers the conceptual analysis and practical design of a fingerprint identification system using Digitalpersona-SDK and is implemented for charging and discharging materials in the library. The fingerprint biometric identification system is designed using Java programming language and MySQL database at the backend for storing patrons' information including fingerprint images. Usability evaluation of the system revealed that the fingerprint approach to charging and discharging of library materials is faster, more effective and efficient than the manual system.
A communication system is a system model that describes a communication exchange between two stations, transmitter and receiver. The application of cryptography is treated as the most effective solution to ensure the secure transmission of data. Cryptographic drawbacks cause such systems to cryptanalysis by malicious individuals, resulting in most data breaches. As an alternative, this system proposes a framework that provides solution to communication system by integrating biometrics with cryptography. The system developed makes use of the combination of public key RSA system with fingerprint, which is the most popularly used biometric. This research work ensures the security of messages communicated between the two users and the maintenance of a secure authentication mechanism. The developed system is based on privacy-preserving architecture. It could be used as an access control system as well as an internal communication mechanism for many organizations.
Cancer is one of the deadliest diseases in human beings. Breast cancer is considered to be the second most exposed cancer in the world and is now the most common disease in women. The women of ages 45-59 has the highest number of chances to be affected by breast cancer. Early prediction and diagnosis of breast cancer can prevent its spread and may help with effective treatment or medication. Predicting breast cancer is a very arduous task as the data can be highly Non-linear and may require high level computation modeling. However, many machine learning algorithms like KNN, K-Means, Decision Trees, Neural Networks etc., have proved to be effective in predicting breast cancer. This study shows the use of k-Nearest Neighbors (kNN) algorithm to predict whether a person is having breast cancer or not, using a machine learning model trained with different features. Thus, we inferred that we could predict the Breast Cancer with reasonable accuracy. From the results, it can be concluded that breast cancer cells can be accurately detected using machine learning techniques such as KNN.
