Developing data mining algorithms for predicting cyber security risks using predictive analytics

Data mining methods used as one of successfully potential solution against cyber risks, big data and electronic thread increasing faster in the last year's, so it forms a challenge to cyber security, data prediction used as one of the fundamental tools to predict cyber risks and improving security methods.

Cyber security is one of important popular challenges in the current era where cyber-attacks and risks increasing, so fast it is very important to develop tools and techniques of cyber security, data mining techniques one of the important method used to solve cyber security problems. In this study we took support vector machine with random forest as prediction of risks tool then tested on a set of chosen data to detect attacks and risks on information and demonstrate the results, merging and make a comparison between them to gain best way for predicting of cyber security risks and determine the unusual data patterns that consider suspicious activity and improving the response to them.