Detecting SYN flooding attacks

By Haining Wang, Danlu Zhang, Kang G. Shin. Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies, 2002

707 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/2d891f28f644fb9d84a2515c699361274950d471

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. Marina K. Thottan
2. Vasilios A. Siris
3. Chuanyi Ji
4. Fotini Papagalou
5. Kang G. Shin
6. Alexandre Termier
7. Pierre-Alain Fouque
8. Cheng Jin

In Computer Networks and Communications

1. Vasilios A. Siris
2. Marina K. Thottan
3. Chuanyi Ji
4. Fotini Papagalou
5. Alexander G. Tartakovsky
6. Rudolf B. Blazek
7. Hongjoon Kim
8. Boris L. Rozovskii

Citations in the corpus

• Defense Against Spoofed IP Traffic Using Hop-Count Filtering (2007, background): “Several efficient mechanisms [17], [19], [35], [52] are avai lable to detect DDoS attacks.”
• Asymptotic Optimality of Change-Point Detection Schemes in General Continuous-Time Models (2006, background): “To detect denial of service attacks, one can monitor the number of packets (TCP, ICMP, UDP) (see Blažek et al., 2001; Tartakovsky et al., 2006; Tartakovsky and Veeravalli, 2004; Wang et al., 2002).”
• Hop-count filtering: an effective defense against spoofed DDoS traffic (2003, background): “Besides the IP2HC inspect ion, several efficient mechanisms [17, 20, 30, 43] are available t o de ect DDoS attacks.”
• A novel approach to detection of intrusions in computer networks via adaptive sequential and batch-sequential change-point detection methods (2006, background): “In fact, DOS flooding attacks remain the subject of intensive research, as can be seen in [11], [13], [19], [20], [22], and [37].”
• Anomaly detection in IP networks (2003, methodology): “Statistical analysis has been used to detect both anomalies corresponding t network failures [5], as well as network intrusions [6].”
• Application of anomaly detection algorithms for detecting SYN flooding attacks (2004, methodology): “Observe that the CUSUM algorithm discussed in this paper has better performance than the algorithm in [12].”
• Anomaly Detection in Streams with Extreme Value Theory (2017, background): “For example, in intrusion detection, some network attack techniques rely on intensive scans of the network, which are characterized by an unusually high number of SYN packets [32].”