Abstract
Technology in our current era has become very important, as it has facilitated many services for us and has become faster and easier than before, as we can complete many things simultaneously and as quickly as possible. One of the most important services affected by technology is the electronic banking services, where the services provided by banks to their customers can be dealt with at maximum speed and does not require much effort and time, and with the progress and development of these services there are problems that have emerged and among the most important of these problems facing electronic banking services that affect their security It is a phishing problem. The problem of phishing is one of the biggest and most important problems, and it means that there is an attack and sabotage on sensitive data by people trying to steal and destroy information by creating fake sites similar to the original sites of the bank aimed at manipulating customers and stealing important information and the most important of this information is the IBAN number of the account owner in The bank or password. In this project, we work to limit and reduce the attack by identifying legitimate and fake sites using one of the data mining algorithms, which is c4.5 algorithm As this algorithm works on classification, so it can classify fake and legitimate sites where used this algorithm in WEKA is a tool for analyzing data and categorizing fake websites and reducing phishing in electronic banking services. After applying the algorithm to a dataset containing 32 attributes, the accuracy rate was 98.11%, which is considered a good percentage for classification, while the instance rate was only incorrect 1.89%.