Code red worm propagation modeling and analysis
By Cliff Changchun Zou, W. Gong, D. Towsley. Conference on Computer and Communications Security, 2002
855 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Networks and Communications
View Paper: https://www.semanticscholar.org/paper/8a112ce78b0852ab71c630ebc514d0634ec8aa35
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Angelos Dennis Keromytis
- Wenke Lee
- David Dagon
- Guofei Gu
- David M. Nicol
- William H. Sanders
- Kishor S. Trivedi
- Cliff Changchun Zou
In Computer Networks and Communications
- Andreas Haeberlen
- Alan Mislove
- Wenke Lee
- David Dagon
- Cliff Changchun Zou
- Kishor S. Trivedi
- William H. Sanders
- David M. Nicol
Citations in the corpus
- Incentive-based modeling and inference of attacker intent, objectives, and strategies (2003, background): “However, with a focus on attack characteristics [17] and attack effects [2, 33], existing AIOS inference techniques are”
- Countering code-injection attacks with instruction-set randomization (2003, background): “Because such attacks can be launched over a network, they are regularly used to break into hosts or as an infection vector for computer worms [55, 4, 9, 10, 46, 64].”
- Internet attack knowledge discovery via clusters and cliques of attack traces (2006, background): “Code Red II, for instance, implements such a strategy [18].”
- An Overview of IP Flow-Based Intrusion Detection (2010, background): “Code Red [73] and Sapphire/Slammer [40] are examples of this mechanism.”
- Glacier: highly durable, decentralized storage despite massive correlated failures (2005, background): “The course, scope and impact of these attacks has been studied in great detail [29, 30, 38, 39, 47].”
- Modeling the spread of active worms (2003, background): “Zou extended the Epidemiological model to the two-factor worm model, which takes consideration of the human countermeasure and the worm’s impact on Internet traffic and infrastructure [12].”
- 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].”
- Modeling Botnet Propagation Using Time Zones (2006, methodology): “Models have also been proposed for a few famous worms, including CodeRed [ ZGT02 , Moo02a, Sta01] and Slammer [MPS+03].”
- 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): “In Section VIII, we discuss limitations and possible future work.”