(untitled) (JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences, 2019)
The growth and development of the Internet has led to the rapid expansion of Local network systems and World Wide Web, has reflected a very large increase in Internet users. Data and computer hardware are becoming more relevant to the global network, making it more vulnerable to attackers. so there is an urgent need to further protect the Devices and data users of attacks or unauthorized access. Including the detection and classification of data transmitted over the World Wide Web, especially that connect users’ devices to prevent illegal access. In this sense, the research was based on the use of one of the smart algorithms of meta heuristic algorithm (Tabu) to find the most efficient rules in the detection process and use the best ways to neglect the repeated rules, which helps to reduce the storage space and reduce the time addition. Algorithm was hybridized with the artificial intelligence (Fuzzy Logic) Which in turn can reduce the rules required to hybridize in order to obtain new rules. Experiments were conducted on dataset (KDD99 10%) for detection and determination through algorithm if dataset is normal or attacks, Thus, this algorithm gave the results of a Detection Rate of 87.7%, a Detection accuracy of 96.36%, and the time taken for the results obtained was 13 minutes and 26 seconds.