• Mr Vishnu Muraleedharan
• Mr Subin Omanakuttan

The usage of internet has been increasing day by day .Internet influences our privacy a lot. We share our important data to an intended person or to someone we don’t know. We believe that our shared data will securely reach to the recipient. But it’s only our expectation. There may be a chance that some of our shared data may be corrupted. The proposed system is designed to prevent intrusion and shares data securely between client and server using RFA and SVM algorithm. The random forest algorithm is designed to classify and compare other system over the networked data. And SVM’s are used for classification and regression. The information gain method was used to improve the accuracy of RFA. To calculate the performance NSL KDD data set has been used. The NSL KDD is a data set available in many clustering algorithms. It is a data mining tool. The result of proposed system is compared with the other existing system. And we will get the result that the proposed system is far better than the previous systems.

Privacy,RFA, SVM, NSL KDD

"ENHANCED RFA : A METHOD FOR EFFICIENT INTRUSION DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.386-392, June 2019, Available :http://www.jetir.org/papers/JETIR1906P59.pdf

"ENHANCED RFA : A METHOD FOR EFFICIENT INTRUSION DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp386-392, June 2019, Available at : http://www.jetir.org/papers/JETIR1906P59.pdf