Resource-sensitive intrusion detection models for network traffic

Network security is an important subject in today's extensively interconnected computer world. The industry, academic institutions, small and large businesses and even residences are now greatly at risk from the increasing onslaught of computer attacks. Such malicious efforts cause damage ranging from mere violation of confidentiality and issues of privacy up to actual financial loss if business operations are compromised, or even further, loss of human lives in the case of mission-critical networked computer applications. Intrusion Detection Systems (IDS) have been used along with the help of data mining modeling efforts to detect intruders, yet with the limitation of organizational resources it is unreasonable to inspect every network alarm raised by the IDS. Modified Expected Cost of Misclassification ( MECM) is a model selection measure that is resource-aware and cost-sensitive at the same time, and has proven to be effective for the identification of the best resource-based intrusion detection model.