Association for Computing Machinery
Denials of Service (DoS) attacks over-whelm online services, preventing legitimate users from accessing a service, often with impact on revenue or consumer trust. Approaches exist to filter network-level attacks, but application-level attacks are harder to detect at the firewall. Filtering at this level can be computationally expensive and difficult to scale, while still producing false positives that block legitimate users. This paper presents a model-based adaptive architecture and algorithm for detecting DoS attacks at the web application level and mitigating them.