Statistical Opportunities, Roles, and Challenges in Network Security

[1]  Y. Vardi,et al.  Network Tomography: Estimating Source-Destination Traffic Intensities from Link Data , 1996 .

[2]  V. Rao Vemuri,et al.  Use of K-Nearest Neighbor classifier for intrusion detection , 2002, Comput. Secur..

[3]  Robert K. Cunningham,et al.  Improving Intrusion Detection Performance using Keyword Selection and Neural Networks , 2000, Recent Advances in Intrusion Detection.

[4]  Anupam Joshi,et al.  Low-complexity fuzzy relational clustering algorithms for Web mining , 2001, IEEE Trans. Fuzzy Syst..

[5]  Yun Wang,et al.  A multinomial logistic regression modeling approach for anomaly intrusion detection , 2005, Comput. Secur..

[6]  Qiang Chen,et al.  Multivariate Statistical Analysis of Audit Trails for Host-Based Intrusion Detection , 2002, IEEE Trans. Computers.

[7]  Ajantha Herath,et al.  Intrusion detection using the chi-square goodness-of-fit test for information assurance, network, forensics and software security , 2007 .

[8]  Jonathan A C Sterne,et al.  Sifting the evidence—what's wrong with significance tests? , 2001, BMJ : British Medical Journal.

[9]  Jung-Min Park,et al.  An overview of anomaly detection techniques: Existing solutions and latest technological trends , 2007, Comput. Networks.

[10]  Richard Lippmann,et al.  The 1999 DARPA off-line intrusion detection evaluation , 2000, Comput. Networks.

[11]  John McHugh,et al.  Intrusion and intrusion detection , 2001, International Journal of Information Security.

[12]  Álvaro Herrero,et al.  Intrusion Detection at Packet Level by Unsupervised Architectures , 2007, IDEAL.

[13]  Wenke Lee,et al.  Intrusion Detection Techniques for Mobile Wireless Networks , 2003, Wirel. Networks.

[14]  Sung-Bae Cho,et al.  Efficient anomaly detection by modeling privilege flows using hidden Markov model , 2003, Comput. Secur..

[15]  John McHugh,et al.  Testing Intrusion detection systems: a critique of the 1998 and 1999 DARPA intrusion detection system evaluations as performed by Lincoln Laboratory , 2000, TSEC.

[16]  David J. Hand,et al.  Statistical fraud detection: A review , 2002 .

[17]  RICHAFID BASKERVILLE,et al.  Information systems security design methods: implications for information systems development , 1993, CSUR.

[18]  Yun Wang,et al.  Determining the Minimum Sample Size of Audit Data Required to Profile User Behavior and Detect Anomaly Intrusion , 2006, Int. J. Bus. Data Commun. Netw..

[19]  Ali A. Ghorbani,et al.  Approximate autoregressive modeling for network attack detection , 2008 .

[20]  A. Karr,et al.  Computer Intrusion: Detecting Masquerades , 2001 .

[21]  Iwao Sasase,et al.  Anomaly Detection on Mobile Phone Based Operational Behavior , 2008 .

[22]  S. Goodman Toward Evidence-Based Medical Statistics. 1: The P Value Fallacy , 1999, Annals of Internal Medicine.

[23]  Yun Wang,et al.  Risk Factors to Retrieve Anomaly Intrusion Information and Profile User Behavior , 2006, Int. J. Bus. Data Commun. Netw..

[24]  Yun Wang,et al.  Develop a composite risk score to detect anomaly intrusion , 2005, Proceedings. IEEE SoutheastCon, 2005..

[25]  Charles Elkan,et al.  Results of the KDD'99 classifier learning , 2000, SKDD.

[26]  David A. Cieslak,et al.  RIPPS: Rogue Identifying Packet Payload Slicer Detecting Unauthorized Wireless Hosts Through Network Traffic Conditioning , 2008, TSEC.

[27]  Dorothy E. Denning,et al.  An Intrusion-Detection Model , 1987, IEEE Transactions on Software Engineering.

[28]  Steven L. Scott,et al.  A Bayesian paradigm for designing intrusion detection systems , 2004, Computational Statistics & Data Analysis.