Analysis Against DDOS Flooding Attacks in Healthcare System using Artificial Neural Network
Ravi Pratap Singh Tomar · International Journal of Advanced Trends in Computer Science and Engineering · 2019
The research on cyber security has gained more attention and interest outside the availability of computer security experts.Cyber security is not a single issue, but a series of highly different issues involving multiple threats.The data accommodation in health care system is growing continuously, which demanded a highly efficient and intelligent system to deal with the health records.The increase in the data increases the probability of affecting data by the cyber attacker.Therefore, it becomes essential to deal with cyber-attacks.This research focused on the utilization of cyber security for healthcare organization using machine learning approach.Our aim is to detect Distributed Denial of Service (DDoS) attack, which is one of the most commonly present cyber-attacks.This type of attack is designed to prevent genuine user from the required network resources.By using the concept of Artificial Neural Network (ANN), the system is trained based on the database related to the clinical record, financial record, individual record etc.During the data communication process, cross-validation is performed using ANN approach, which matched the data with the database and at last check the performance parameters.The experiment results indicate that there is an increase in the True Positive Rate (TPR) and False Positive Rate (FPR) of 0.27 % and 8.79 % respectively has been observed.