Diabetes is a global diseases that has affected over 388 million people and cause many deaths and serious condition. This is due to the late detection and diagnosis of the disease as it causes a delay in treatment and becomes harder to prevent it from worsening. It is important to detect the disease at an early stage and start early treatment to prevent it from becoming life-threatening. The aim of this project is to produce a system that can accurately predict the disease in real-time for the user and provide online consultation by doctors and chatbots which will help prevent major illnesses in future. The project targets anyone who may want to check whether they have the disease or not. It also serves as a platform for doctors to provide online consultation to their clients. The project will follow the Knowledge Discovery in Database approach. Implementing the system will reduce time consumption, produce real-time results cost-freely & early detection of diabetes. The project is expected to produce a functional system which accurately predicts diabetes based on the data entered in real-time to minimize visits to clinics and cut the cost of the test while providing online health consultation.

Phishing is a deceptive technique to steal confidential information like user credentials and bank account details of web users. Employing technical and social engineering skills phishers make huge financial loss to web users and large organizations alike, and it has become one of the serious cybercrime today. This paper discusses different types of phishing techniques, their impacts, common indicators of phishing attacks, and analyses various anti-phishing solutions from conventional methods implementing blacklist, white list, heuristics, fuzzy logic, visual similarity, etc. to machine learning methods. The study provides gap analysis of conventional anti-phishing techniques, and points out the challenges facing machine learning based approaches including proper feature selection, diversity in data sets, imbalanced scenarios, and differences in evaluation metrics. This investigation outlines the need for serious researches in this area since there is no foolproof solution to phishing as phishers change their tactics very often to bypass anti-phishing detection systems.