Defending against distributed denial-of-service attacks with max-min fair server-centric router throttles

By David K. Y. Yau, John C.S. Lui, Feng Liang, Y. Yam. IEEE/ACM Transactions on Networking, 2005

339 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/7fa202d3486a7d6de583aff64ba3f45b0702439c

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

1. Vijay Janappa Reddi
2. Ruby B. Lee
3. Kang G. Shin
4. Aikaterini Mitrokotsa
5. Christos Douligeris
6. Cheng Jin
7. Thanh Thi Nguyen
8. Haining Wang

In Computer Networks and Communications

1. Ruby B. Lee
2. Kang G. Shin
3. Aikaterini Mitrokotsa
4. Christos Douligeris
5. Vijay Janappa Reddi
6. Cheng Jin
7. Thanh Thi Nguyen
8. Haining Wang

Citations in the corpus

• DDoS attacks and defense mechanisms: classification and state-of-the-art (2004, background): “Throttling [91] is a mitigation approach against DDoS attacks, which prevents servers (web servers in particular) from going down.”
• Deep Reinforcement Learning for Cyber Security (2019, background): “[106] to evaluate throttling approaches.”
• Defense Against Spoofed IP Traffic Using Hop-Count Filtering (2007, methodology): “Through analysis using network measure­ment data, we show that HCF can identify close to 90% of spoofed IP packets, and then discard them with little collateral damage.”
• Distributed Denial of Service: Taxonomies of Attacks, Tools, and Countermeasures (2004, positive): “The Max-min Fair server-centric router throttle method[21] sets up routers that access a server with logic to adjust (throttle) incoming traffic to levels that will be safe for the server to process.”