Automatic firewall rules generator for anomaly detection systems with
  Apriori algorithm
  Network intrusion detection systems have become a crucial issue for computer
systems security infrastructures. Different methods and algorithms are
developed and proposed in recent years to improve intrusion detection systems.
The most important issue in current systems is that they are poor at detecting
novel anomaly attacks. These kinds of attacks refer to any action that
significantly deviates from the normal behaviour which is considered intrusion.
This paper proposed a model to improve this problem based on data mining
techniques. Apriori algorithm is used to predict novel attacks and generate
real-time rules for firewall. Apriori algorithm extracts interesting
correlation relationships among large set of data items. This paper illustrates
how to use Apriori algorithm in intrusion detection systems to cerate a
automatic firewall rules generator to detect novel anomaly attack. Apriori is
the best-known algorithm to mine association rules. This is an innovative way
to find association rules on large scale.
