Inside the Slammer Worm

By David Moore, Vern Paxson, Stefan Savage, Colleen Shannon, Stuart Staniford-Chen, Nicholas C. Weaver. IEEE Security and Privacy, 2003

1,097 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/82d5304042597f7e15ba0d1b77264f5efd0e7895

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

1. Wenke Lee
2. Dawn Song
3. Guofei Gu
4. Miguel Oom Temudo de Castro
5. James Newsome
6. David Dagon
7. Dan Boneh
8. Helen J. Wang

In Information Systems

1. Dawn Song
2. Wenke Lee
3. James Newsome
4. Yuanyuan Zhou
5. Dan Boneh
6. Thorsten Holz
7. Martín Casado
8. Manuel Costa

In Signal Processing

1. Wenke Lee
2. Dawn Song
3. Guofei Gu
4. James Newsome
5. Thorsten Holz
6. David Dagon
7. Niels Provos
8. Moritz Steiner

Citations in the corpus

• Secure or insure?: a game-theoretic analysis of information security games (2008, background): “The " I Love You " virus [27], Code Red [29] and Slammer worms [28], to cite the most famous cases, have infected hundreds of thousands of machines and caused, all together, billions of dollars in damages.”
• A survey of coordinated attacks and collaborative intrusion detection (2010, methodology): “For example, in 2003 the SQL-Slammer worm infected 75,000 hosts in 10 min, which caused significant disruption to financial, transportation, and government institutions (Moore et al., 2003).”
• Understanding the Mirai Botnet (2017, background): “5 megabytes/second, about 6000 times faster [68], and the Witty worm scanned even faster at 3 megabytes/second [81].”
• A Survey of Game Theory as Applied to Network Security (2010, neutral): “[20], [29], which study network attacks.”
• Security for Industrial Communication Systems (2005, background): “Worm infections are untargeted and usually create availability problems for the affected systems or even the Internet as a whole [ 11 ].”
• Cyber-physical systems security: Limitations, issues and future trends (2020, neutral): “…the Stuxnet (1 & 2) [99], [100], [101] and Duqu malware (1.0, 1.5 & 2.0) attack types [102], [103], [104], Gauss malware [105], [106], [102], and RED October malware [107], [108], as well as Shamoon Malware (1, 2 & 3) [109], [110], [111], Mahdi malware [112], [113], [114], and Slammer Worm [115].”
• LIFT: A Low-Overhead Practical Information Flow Tracking System for Detecting Security Attacks (2006, background): “It brought down tens of thousands of machines within several minutes and cost hundreds of millions of dollars loss [30].”
• A Virtual Honeypot Framework (2004, background): “Blaster [5], Code Red [13], Nimda [4], Slammer [ 14 ], etc.”
• An Inside Look at Botnets (2007, background): “characterized the Code Red I/II worm outbreaks in [29] and the Sapphire/Slammer worm outbreak [27] providing key details on propagation methods and infection rates.”
• An Overview of IP Flow-Based Intrusion Detection (2010, background): “An example is the DoS effect related to the scanning phase of the Sapphire/Slammer worm [40]: while spreading, the worm provokes the crash of Microsoft SQL Server hosted on the target machine.”