Title :
Develop a composite risk score to detect anomaly intrusion
Author :
Wang, Yun ; Cannady, James
Abstract :
This study developed a composite risk score for anomaly intrusion detection based on the KDD-cup 1999 data, which demonstrated a high sensitivity, specificity and a low misclassification in detecting network attacks (0.90, 0.94, and 0.08, respectively). This score provides a statistically sound basis for developing a real time intrusion detection system, and it can be constructed via common computer languages without interfacing with any typical software and statistical tool.
Keywords :
Internet; computer network management; data mining; real-time systems; risk analysis; telecommunication security; KDD-cup 1999 data; anomaly intrusion detection; composite risk score; network attacks; real time intrusion detection; Computer languages; Computer networks; Data mining; Databases; Intrusion detection; Probability; Real time systems; Software tools; Testing; Training data;
Conference_Titel :
SoutheastCon, 2005. Proceedings. IEEE
Print_ISBN :
0-7803-8865-8
DOI :
10.1109/SECON.2005.1423285
