Supervised learning‐based DDoS attacks detection: Tuning hyperparameters

Evading DDoS detection with mimicry attacks

Distributed Denial of Service (DDoS) attacks are security attacks that prevent normal use of communication facilities. More and more DDoS attacks are occurring each day. Conventional DDoS attacks are typically based on flooding the server. Currently, other types of DDoS attacks have been observed, such as the mimicry DDoS attack. The mimicry attack is characterized by (1) gradual increase in th...

DDoS Attacks Detection Model and its Application

With the proliferation of Internet applications and network-centric services, network and system security issues are more important than before. In the past few years, cyber attacks, including distributed denial-of-service (DDoS) attacks, have a significant increase on the Internet, resulting in degraded confidence and trusts in the use of Internet. However, the present DDoS attack detection te...

Throttling DDoS Attacks

Distributed Denial of Service poses a significant threat to the Internet today. In these attacks, an attacker runs a malicious process in compromised systems under his control and generates enormous number of requests, which in turn can easily exhaust the computing resources of a victim web server within a short period of time. Many mechanisms have been proposed till date to combat this attack....

surviving DDoS attacks

ka n d u l a @ M IT. E D U C O N S I D E R T H E F O L L O W I N G S C E N A R I O : Alyssa Hacker subverts tens of thousands of machines by using a worm and then uses these zombies to mount a distributed denial of service attack on a Web server. Alyssa’s zombies do not launch a SYN flood or issue dummy packets that will only congest the Web server’s access link. Instead, the zombies fetch file...

Intrusion Forecast, Detection and Traceback against DDoS attacks