As Security is becoming more and more useful in the field of computing, users would like to be sure of how secure their files are on a system, as security is one of the most crucial fields in networking and file storage. Dependable file storage and access establish several security issues in a cloud computing. This research designed and implemented virtual secure file storage system on cloud using hybrid cryptography. The cryptography method used for file encryption and decryption is AES and SHA-2 hash function. It is implemented using Cloud APIs with REST calls or client libraries in PHP. The system interfaces were developed using HTML, CSS and JAVASCRIPT. Back end development was done using PHP, MYSQL and GCP Cloud Storage Library then the file encryption and decryption was achieved through PHP classes which includes open_ssl_file_encryption and decryption (AES) and also MCRYPT function. The proposed virtual system is also compared with some latest related works.

This study was intended to analyse data mining techniques on the customer engagements with telecommunication companies in Nigeria. This study was guided by the following objectives; to provide an overview, on how prediction is being made in a telecommunication company using data mining. MTN Nigeria was chosen as a case study to identify fraud telecommunication companies in Nigeria; to identify the challenges of data mining faced by telecommunication companies in Nigeria. The study employed the descriptive and explanatory design; primary means were applied in order to collect data. Primary data sources were used and data was analyzed using orange data mining software. The study findings revealed that data mining significantly impacts on the performance of telecommunication industries. In this paper, we made an attempt in to the analysis of telecommunication company data to assess the impact of customer engagements.

Diabetes or Diabetes Mellitus (DM) is noxious diseases in the world. Diabetes is caused by obesity or high blood glucose level, lack of exercise and so forth. It can be manage if it’s detected at early state. Machine learning is the construction of computer system or program that can adapt and learn from their experience. PIMA dataset is used in this research works. The dataset contains some 9 attributes of 768 patients. There are different kinds of machine learning algorithms but in this research works we choose three algorithms which are under supervised learning. The algorithms are Logistic regression, Decision tree and Random forest. Each of these algorithms model were trained and tested. We later use some measure to compare and analyze the performance of the machine learning algorithms. The performance measures used are Accuracy, F-measure, Recall and Precision. Logistic Regression has the highest accuracy score which is 77%, also have the highest precision score 0.77 and have the highest f-measure 0.64. Decision Tree has the highest recall score 0.58

This research has taken a Quantitative, interpretive and cross-sectional designs in the form of a self-administered questionnaire through survey. The aim is to investigate the adoption of Cloud Computing by IT based small and medium scales enterprises in Northwestern Nigeria. About one hundred and fifty (150) questionnaires were distributed among seven states in the North-Western Nigeria and average of one hundred and nine (109) was responded. The result of the survey shown that most of the IT professional in these SMEs are cloud provider’s end users, continue to use cloud provider in the future, is part of their strategic effort, recommended Cloud provider to others and they are very satisfied with the cloud providers. Challenges that are preventing them from getting the maximum value out of cloud providers are lack of encouragement, poor training, application is missing and lack of executive sponsorship.