A taxonomy of computer worms

By Nicholas C. Weaver, Vern Paxson, Stuart Staniford-Chen, R. Cunningham. Worm, 2003

530 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Signal Processing

View Paper: https://www.semanticscholar.org/paper/b8177692445768996889d19353bb9284771f057e

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Citations in the corpus

Fast Detection of Scanning Worm Infections (2004, background): “Local addresses are often preferentially selected [27] as communication between neighboring hosts will likely encounter fewer defenses.”
Very Fast Containment of Scanning Worms (2004, unknown): “Currently, such containment mechanisms only work against scanning worms [27] because they leverage the anomaly of a local host attempting to connect to multiple other hosts as the means of detecting an infectee.”
A Survey of IoT-Enabled Cyberattacks: Assessing Attack Paths to Critical Infrastructures and Services (2018, background): “The malware was a computer worm [212] and the hospital’s IT stuff had no knowledge of its existence.”
Modeling Botnet Propagation Using Time Zones (2006, result): “Improvements belonging to the rst category can be found in more recent analysis such as [SM04], which traced signicant worm outbreaks, and [ZTGC05, WPSC03 ,WSP04], which examined a specic type of routed worm, and [ZTG04], which examines specic types of propagation (e.g., e-mail).”
An Overview of IP Flow-Based Intrusion Detection (2010, background): “These classications usually distinguish between the following basic categories [38], [39]:”
Polymorphic Worm Detection Using Structural Information of Executables (2005, background): “In recent years, Internet worms have proliferated because of hardware and software mono-cultures, which make it possible to exploit a single vulnerability to compromise a large number of hosts [25].”
A Survey of Attacks and Countermeasures in Mobile Ad Hoc Networks (2007, background): “The Code Red worm [50] is one of the scanning worms.”
A Survey of Malware Detection Techniques (2007, unknown): “[53] describe zero-day exploits.”
Polonium: Tera-Scale Graph Mining and Inference for Malware Detection (2011, background): “Polonium has served 120 million people and helped answer more than one trillion queries for file reputation.”
Characterization of network-wide anomalies in traffic flows (2004, background): “Researchers have characterized Internet intrusion activity [24], failure events in IP networks [17], and also constructed taxonomies for Internet worms [23], denial of service attacks [9] and defenses [18].”
A Taxonomy of Botnet Structures (2007, methodology): “Similar to how previous work detailed key aspects of individual classes of worms [57], this paper provides a taxonomy of botnet organization, and their utility for various malicious activity.”
The Internet Motion Sensor - A Distributed Blackhole Monitoring System (2005, background): “Internet worms represent a class of security threats that seek to execute code on a target machine by exploiting vulnerabilities in the operating system or application software [15, 33].”
A survey of coordinated attacks and collaborative intrusion detection (2010, background): “Note that we do not attempt to provide a comprehensive survey of these attacks, which can be found in (Staniford, 2002; Weaver et al., 2003; Goldi and Hiestand, 2005; Peng et al., 2006; Mirkovic and Reiher, 2004; Igure and Williams, 2008).”