BLINC
University of California, Riverside · Intel (United States)
Abstract
We present a fundamentally different approach to classifying traffic flows according to the applications that generate them. In contrast to previous methods, our approach is based on observing and identifying patterns of host behavior at the transport layer. We analyze these patterns at three levels of increasing detail (i) the social, (ii) the functional and (iii) the application level. This multilevel approach of looking at traffic flow is probably the most important contribution of this paper. Furthermore, our approach has two important features. First, it operates in the dark, having (a) no access to packet payload, (b) no knowledge of port numbers and (c) no additional information other than what current…
Citation impact
- FWCI
- 87.76
- Percentile
- 100%
- References
- 24
Authors
3Topics & keywords
- Computer science
- Payload (computing)
- Network packet
- Data mining
- Port (circuit theory)
- Transport layer
- Contrast (vision)
- Host (biology)