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Computer Networks
Combining elements of computer science and information technology/assurance,
ICASA's computer network research covers a wide variety of research topics.
Researchers seek new and innovative methods to better understand computer
networks by studying their behaviors, vulnerabilities, and interactions. Areas
of research include: security in distributed and grid environments, intrusion
detection, malware analysis and malicious code detection, network topology,
and software agent interaction and control.
Point of Contact: Dr.
Srinivas Mukkamala |
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Computer Networks Patents
| Title |
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Authors |
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Patent |
Internet monitoring and alerting system, New Mexico Technical Research Foundation, 2015. |
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Planck,
M.W., Colbaugh, R.D., Glass, K.L., Willard, G.N., Thiess, M.D., Ackley, D.M., Pollard, I.R., Mattax,
J.P., Barber, B.M. and Shepard, N.M. |
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U.S. Patent 9,032,518 |
Computer Networks Publications
| Title |
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Authors |
Designing Intrusion Detection
Systems: Architectures and Perspectives. Annual Review of Communications,
Vol. 57, International Engineering Consortium, 2004 |
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| Intrusion
Detection Systems using Adaptive Regression Splines. Kluwer Academic
Press, 2004 |
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S.
Mukkamala,
A. H. Sung, A. Abraham, V. Ramos |
| Knowledge Discovery in Network Audit Trails. Lecture
Notes in Computer Science, Springer, 2004, in press |
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S.
Mukkamala, A.
H. Sung |
| On the Performance of Learning Machines for Bankruptcy
Detection, 2004, Under Review |
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A. S. Vieira, B. Ribeiro,
S. Mukkamala, J. C. Neves, A.
Sung |
| An Ensemble of Network Forensic Models and Significant
Feature Analysis, Elsevier, 2004, Under Review |
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S.
Mukkamala, A.
H. Sung |
| Hybrid
Multi Agent Framework for Detection of Stealthy Probes. Applied Soft
Computing Journal, Elsevier, 2005, In Press |
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S.
Mukkamala, A.
H. Sung, A. Abraham |
| Intrusion
Detection Using an Ensemble of Intelligent Paradigms. Journal of Network
and Computer Applications, Elsevier, 2004, In Press |
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S.
Mukkamala, A.
H. Sung, A. Abraham |
| Identifying
Significant Features for Network Forensic Analysis Using Artificial Intelligence
Techniques. In International Journal on Digital Evidence, IJDE Volume
1, Issue 4, 2003 |
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S.
Mukkamala, A.
H. Sung |
| Feature
Selection for Intrusion Detection Using Neural Networks and Support Vector
Machines. Journal of the Transportation Research Board of the National
Academics, Transportation Research Record No 1822, pp. 33-39, 2003 |
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S.
Mukkamala, A.H.
Sung |
| Mining Key Features from Network Audit Trails for Intrusion
Detection Systems Using Machine Learning Techniques. Criminal Intelligence
Digest, Central Bureau of Investigation, 2002 |
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S. Mukkamala |
| “Supervised Inductive Learning with Lotka-Volterra derived models, ” in Eighth IEEE International Conference on Data Mining (ICDM2008), Pisa, December 2008. |
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K. Hovsepian, P. Anselmo, and S. Mazumdar |
| “A Modeling-based Classification Algorithm Validated with Simulated Data,” in Winter Simulation Conference (WSC 2008), Miami, 2008. (PDF) |
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K. Hovsepian, P. Anselmo, and S. Mazumdar |
| “A framework for near real-time event characterization within the internet”, in Network Science Workshop (pp. 59-66), IEEE, 2011. |
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M. Planck, K. Glass, I. Lyman, and R. Colbaugh |
| “Application of information diffusion in social networks: Verifying the use of web/blog topology entropy as an indicator for real world impact”, in 2nd International Workshop on Network Science (pp. 164-167), IEEE, 2013. |
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M. Planck, C. Brock, D. Bachman, J. Fenchel, and I.L. Pollard |
| “Initial indicators of topic success in Twitter: Using topology entropy to predict the success of Twitter hashtags”, in 2nd International Workshop on Network Science (pp. 160-163), IEEE, 2013. |
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M. Planck, I.L. Pollard, C. Brock, and A. George |
| “Audit data reduction via Multi-step decomposition Analysis: The Multi-Stage Analytic Engine--Insider Threat”, Submitted to the IEEE Symposium on Systems Security and Privacy. [Submitted] |
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I. Rose, N. Felts, A. George, and M. Planck |
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