ICNP '02 Proceedings of the 10th IEEE International Conference on Network Protocols
Computing Iceberg Queries Efficiently
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Frequency Estimation of Internet Packet Streams with Limited Space
ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
What's hot and what's not: tracking most frequent items dynamically
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Identifying frequent items in sliding windows over on-line packet streams
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
Dynamically maintaining frequent items over a data stream
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Approximate frequency counts over data streams
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
On effective sampling techniques in host-based intrusion detection in tactical MANET
International Journal of Security and Networks
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Network security is an important issue in maintaining the Internet as an important social infrastructure. Especially, finding excessive consumption of network bandwidth caused by P2P mass flow, finding internet viruses, and finding DDoS attacks are important security issues. Although stream mining techniques seem to be promising techniques for network security, extensive network flow prevents the simple application of such techniques. Since conventional methods require non-realistic memory resources, a mining technique which works well using limited memory is required. This paper proposes a sampling-based mining method to achieve network security. By analyzing the characteristics of the proposed method with real Internet backbone flow data, we show the advantages of the proposed method, i.e. less memory consumption.