Decentralized multi-dimensional alert correlation for collaborative intrusion detection

Abstract

The growth in coordinated network attacks such as scans, worms and distributed denial-of-service (DDoS) attacks is a profound threat to the security of the Internet. Collaborative intrusion detection systems (CIDSs) have the potential to detect these attacks, by enabling all the participating intrusion detection systems (IDSs) to share suspicious intelligence with each other to form a global view of the current security threats. Current correlation algorithms in CIDSs are either too simple to capture the important characteristics of attacks, or too computationally expensive to detect attacks in a timely manner. We propose a decentralized, multi-dimensional alert correlation algorithm for CID..