Evaluation of Bernoulli Naive Bayes model for detection of distributed denial of service attacks

Distributed denial of service is a form cyber-attack that involves sending several network traffic to target system such as DHCP, domain name server (DNS), and HTTP server. The attack aims exhaust computing resources memory the processor by blocking legitimate users from getting access provided Network intrusion prevention ensures security protects attacks. Thus, this paper presents predicitive model identifies distributed attacks (DDSA) using Bernoulli-Naive Bayes. developed evaluated on publicly available Kaggle dataset. method tested with confusion matrix, receiver operating characteristics (ROC) curve, accuracy measure its performance. experimental results show an 85.99% in detecting DDSA proposed method. Hence, Bayes-based was found be effective significant for protection servers malicious