Information Technology Reference
In-Depth Information
3. Babcock, B., Babu, S., Datar, M., Motwani, R., and Widom, J.: Models and
issues in data stream systems. In
Symposium on Principles of Database Systems
,
Madison, Wisconsin, USA, ACM SIGMOD (June 2002)
4. Babcock, B., Datar, M., and Motwani, R.: Sampling from a moving window over
streaming data. In
Proceedings of 13th Annual ACM-SIAM Symposium on Discrete
Algorithms
(2002)
5. Babu, S., Subramanian, L., and Widom, J.: A data stream management system for
network trac management. In
Workshop on Network-Related Data Management
(2001)
6. Bellovin, S.M., Leech, M., and Taylor, T.: ICMP traceback messages. In
Internet
Draft draft-ietf-itrace-01.txt (Work in progress)
. IETF (Oct 2001)
7. Bhattacharyya, M., Hershkop, S., Eskin, E., and Stolfo, S.J.: Met: An experimental
system for malicious email tracking. In
Proceedings of the 2002 New Security
Paradigms Workshop (NSPW-2002)
, Virginia Beach, VA (Sep 2002)
8. Bloom, B.: Space/time tradeoffs in in hash coding with allowable errors. In
CACM
(1970) 422-426
9. Broder, A. and Mitzenmatcher, M.: Network applications of bloom filters: A sur-
vey. In
Annual Allerton Conference on Communication, Control, and Computing
,
Urbana-Champaign, Illinois, USA (October 2002)
10. Burch, H. and Cheswick, B.: Tracing anonymous packets to their approximate
source. In
Proc. USENIX LISA
(Dec 2000)
11. Datar, M., Gionis, A., Indyk, P., and Motwani, R.: Maintaining stream statistics
over sliding windows. In
ACM Symposium on Discrete Algorithms
(2001) 635-644
12. Dean, D., Franklin, M., and Stubblefield, A.: An algebraic approach to IP trace-
back. In
Proceedings of NDSS
(Feb 2001)
13. Debar, H., Dacier, M., and Wepsi, A.: A revised taxonomy for intrusion-detection
systems. IBM Research Report (1999)
14. Domingos, P. and Hulten, G.: Mining high-speed data streams. In
Proc. SIGKDD
Int. Conf. Knowledge Discovery and Data Mining
(2000)
15. Sanstorm Enterprises. Netintercept.
http://www.sandstorm.com/products/netintercept/ (Feb 2003)
16. Frank, J.: Artificial intelligence and intrusion detection: Current and future direc-
tions. In Proceedings of the 17th National Computer Security Conference (1994)
17. Gibbons, P. and Matias, Y.: Synopsis data structures for massive data sets. In
DI-
MACS: Series in Discrete Mathematics and Theoretical Computer Science: Special
Issue on External Memory Algorithms and Visualization
(1999)
18. Gilbert, K., Kotidis, Y., Muthukrishnan, S., and Strauss, M.: Surfing wavelets on
streams: one pass summaries for approximate aggregate queries. In
Proc. ACM
Conf. Very Large Databases
. VLDB (2001)
19. Guha, S., Koudas, N., and Shim, K.: Data streams and histograms. In
Proc. ACM
Symp. Theory Comput.
STOC (2001)
20. Hulten, G., Spencer, L., and Domingos, P.: Mining time-changing data streams.
In
Proc. SIGKDD Int. Conf. Knowledge Discovery and Data Mining
(2001)
21. Ilgun, K., Kemmerer, R.A., and Porras, P.A.: State transition analysis: A rule-
based intrusion detection approach. IEEE Transactions on Software Engineering
(March 1995)
22. Javitz, H.S. and Valdes, A.: The sri ides statistical anomaly detector. In Proceed-
ings of the IEEE Symposium on Research in Security and Privacy (1991)
23. Kumar, S. and Spafford, E.H.: An application of pattern matching in intrusion
detection. Purdue University Technical Report CSD-TR-94-013 (1994)
