Ke Wang's Candidate Exam Paper List
(04/18/04)
Topic: Anomaly Detection in Network Security
AD in Network Security
(currently 21):
- A Stateful
Intrusion Detection System for World-Wide Web Servers
G. Vigna, W. Robertson,
V. Kher, and R.A. Kemmerer, Proceedings of
ACSAC 2003.
- Bro:
A System for Detecting Network Intruders in Real-Time, V. Paxson, Computer
Networks, 31(23-24), pp. 2435-2463, 14 Dec. 1999
- Enhancing
Byte-Level Network Intrusion Detection Signatures with Context,
R. Sommer and V. Paxson, ACM CCS 2003
- Specification
Based Anomaly Detection: A New Approach for Detecting Network Intrusions,
R. Sekar, A. Gupta, J. Frullo, T. Shanbhag, A. Tiwari, H. Yang & S.
Zhou, ACM CCS, 2002.
- Anomaly Detection
of Web-based Attacks. C. Kruegel
and G. Vigna. 10th ACM
Conference on Computer and Communication Security (CCS '03)
- Service
Specific Anomaly Detection for Network Intrusion Detection,
C. Krugel, T. Toth & E. Kirda, ACM Symposium on Applied Computing,
2002
- A
comparative study of anomaly detection schemes in network intrusion
detection, A. Lazarevic, L. Ertoz, A. Ozgur, J. Srivastava & V.
Kumar. Proc. SIAM Conf. Data Mining, 2003
- Detecting
Anomalous Network Traffic with Self-Organizing Maps, M. Ramadas, S.
Ostermann & B. Tjaden, RAID, 2003
- Learning
Nonstationary Models of Normal Network Traffic for Detecting Novel Attacks,
M. Mahoney and P. Chan, KDD '02
- Detecting
Malicious Software by Monitoring Anomalous Windows Registry Accesses. S.
Stolfo, F Apap, E. Eskin, K. Heller, S. Hershkop, A. Honig, and K. Svore. CU
Tech Report Feb. 23, 2004.
- DCAP:
Detecting Misbehaving Flows via Collaborative Aggregate Policing. C-N.
Chuah, L. Subramanian and R. H. Katz,ACM SIGCOMM Computer Communication
Review, 2003
- A
Signal Analysis of Network Traffic Anomalies,
Paul Barford, Jeffery Kline, David Plonka and Amos Ron, IMW '02
- Sketch-based
Change Detection: Methods, Evaluation, and Applications, Balachander
Krishnamurthy, Subhabrata Sen, Yin Zhang and Yan Chen, 1st ACM/USENIX
Internet Measurement Conference (IMC '03)
- Stateful Intrusion Detection for High-Speed
Networks.
C. Kruegel, F. Valeur, G. Vigna,
and R.A. Kemmerer, IEEE
Symposium on Research on Security and Privacy (S&P '02)
- Information-Theoretic
Measures for Anomaly Detection, W. Lee and D. Xiang, S&P '01.
- Why
6? Defining the Operational Limits of stide,an Anomaly-Based Intrusion
Detector. K. Tan and R. Maxion, S&P '02
- Surveillance
detection in high bandwidth environments, S. Robertson, E. Siegel, M.
Miller & S. Stolfo, Proc. DISCEX, 2003
- Fast
Portscan Detection Using Sequential Hypothesis Testing, Jaeyeon Jung,
Vern Paxson, Arthur W. Berger, Hari Balakrishnan. S&P '04
- Internet
Quarantine: Requirements for Containing Self-Propagating Code. D. Moore,
C. Shannon, G. Voelker, S. Savage. INFOCOM 2003
- How
to 0wn the Internet in Your Spare Time. S. Stanifold, V. Paxson, N.
Weaver. USENIX Security 2002.
- Network
Intrusion Detection: Evasion, Traffic Normalization, and End-to-End Protocol
Semantics M. Handley,
C. Kreibich and V. Paxson, USENIX Security Symposium 2001.
Machine Learning and Data
Mining Related (currently 7):
- Estimating
the Support of a High-Dimensional Distribution, B. Schölkopf, J.
Platt, J. Shawe-Taylor, A. Smola, R. Williamson. Report 99-87, Microsoft
Research, 1999.
- Efficient
Bayesian Parameter Estimation in Large Discrete Domains. Nir Friedman
and Yoram Singer, NIPS'98
- A
Geometric Framework for Unsupervised Anomaly Detection: Detecting Intrusions
in Unlabeled Data. E. Eskin, A. Arnold, M. Prerau, L. Portnoy and S.
Stolfo. Data Mining for Security Applications. Kluwer 2002
- Anomaly
Detection over Noisy Data using Learned Probability Distributions, E.
Eskin ICML'00
- LOF:
Identifying Density-Based Local Outliers. M. Breunig, H. Kriegel, R. Ng,
J. Sander, SIGMOD 2000
- Outlier
detection for high dimensional data, C. Aggarwal, P. Yu, SIGMOD '01
- On-line
Unsupervised Outlier Detection Using Finite Mixtures with Discounting
Learning Algorithms, K. Yamanishi, J. Takeuchi & G. Williams. KDD
'00
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