An Advanced Approach for Detection of Distributed Denial of Service (DDoS) Attacks Using Machine Learning Techniques

One of the most hazardous attacks in network security is the Distributed Denial of Service (DDoS) attack. DDoS is endangering the internet because it halts the functionality of vital services of online applications. When a system is under a DDoS attack, it is unable to provide services to its customers as the system is busy with false requests coming from the attackers. Which can cause a serious problem if banking, healthcare, or government service went under such an attack. DDoS attacks are rapidly increasing and are getting more sophisticated, so it has become difficult to detect these attacks and at the same time protect online services from them. This research study suggests an advanced approach for the detection of such attacks by integrating machine learning techniques.