Monitoring and early warning for internet worms
By Cliff Changchun Zou, Lixin Gao, W. Gong, D. Towsley. Conference on Computer and Communications Security, 2003
379 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Information Systems, Signal Processing
View Paper: https://www.semanticscholar.org/paper/2aff48719398c5e0a5ade9cc2e0555c55efa3155
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Wenke Lee
- David Dagon
- Kishor S. Trivedi
- William H. Sanders
- David M. Nicol
- Cliff Changchun Zou
- Christopher P. Lee
- Guofei Gu
In Information Systems
In Signal Processing
- Cliff Changchun Zou
- Wenke Lee
- David Dagon
- Christopher P. Lee
- Guofei Gu
- Pavel Laskov
- Charu C. Aggarwal
Citations in the corpus
- Modeling Botnet Propagation Using Time Zones (2006, methodology): “For this reason, we study a Code Red-like worm that has the total vulnerable population N1 + N2 + N3 = 360; 000, and = 358/min [ ZGGT03 ].”
- Model-based evaluation: from dependability to security (2004, methodology): “equations have been used [158], [159], [160], [161], [162].”
- The monitoring and early detection of Internet worms (2005, neutral): “They provide the similar estimation results [45].”
- An Advanced Hybrid Peer-to-Peer Botnet (2007, methodology): “The peer-list updating procedure happens around time t=110 (each bot is assumed to send out 358 scans per unit time to the entire IPv4 space, similar to what Code Red worm did [37]).”
- A Taxonomy of Botnet Structures (2007, background): “Further, the considerable body of literature on worm detection has identified detection techniques that can be adapted to botnet detection [9, 21, 26, 44, 58, 61–63].”