关键词: 入侵检测;拒绝服务攻击;特征匹配
A DoS Attack Detection Technology Based on Signature Matching
Abstract
DoS attacks prevent legitimate user of network from using normal network services. In recent years, DoS attacks emerge in endlessly. They break off the services of some famous sites and network servers; interrupt the normal network behavior, result in great financial loss.
Currently, Statistic based DoS attack detection approaches are not adopted for the real-time detection. Misuse based Intrusion Detection Systems such as Snort are designed without considering the characteristic of DoS attack, thus they can not achieve the best performances.
This paper develops a DoS attack detection technology based on signature matching. By analyzing different kinds of DoS attacks such as Smurf and SYN Flooding, and various DoS attack tools such as Tribal Flood Network and Trin00, we extract the attack signatures of DoS. Then these signatures are expressed according to the forms compatible with Snort. We analyze two pattern matching algorithms: Boyer-Moore algorithm and Aho-Corasick algorithm. Then, combining with the characteristics of DoS attacks, we propose an improved algorithm on AC algorithm, named Reversed AC algorithm. Our experimental results show that the Reversed AC algorithm has better performance and consumes a bit more memories.
We design and implement our system prototype and conduct some experiments with DARPA 2000 intrusion evaluation dataset. Our experimental results show that our prototype has detection rate with 98% and false alarm rate with 20%. Our future work is to extract more complete DoS attack signatures to decrease the false alarm rate of our prototype.
Key Words: Intrusion Detection; Denial of Service; Signature Matching
Contents
1 Introduction 1
1.1 Background 1
1.2 Related Work 1
1.3 Research Content and Scope 2
1.4 Paper Structure 3
2 DoS Attacks Overview 4
2.1 Typical DoS Attacks 4
2.1.1 ICMP Flooding 4
2.1.2 TCP Flooding 4
2.1.3 UDP Flooding 5
2.1.4 Summary 5
2.2 Popular DoS Attacks Tools 5
2.2.1 Tribal Flood Network 6
2.2.2 Trin00 6
2.2.3 TFN2K 6
2.2.4 Stacheldraht 6
2.3 DoS Attack Signature Extracting 6
2.3.1 Signature Construction 6
2.3.2 Signature Extracting 8
2.3.3 Signatures Expression 9
3 Pattern Matching Algorithms 10
3.1 Boyer-Moore Algorithm 10
3.2 Aho-Corasick Algorithm 11
3.3 Improvement of Aho-Corasick Algorithm 12
3.4 Performance Analysis 15
4 System Prototype Design and Implementation 17
4.1 System Architecture 17
4.2 System Prototype Design and Implementation 18
4.2.1 Packet Capture 18
4.2.2 Packet Decode 19
4.2.3 Signature Engine 20
4.2.4 Detection Engine 22
4.2.5 Visual Alert 23
5 Experimental Evaluation 26
5.1 Detection Rate 26
5.2 False Alarm Rate 27
5.3 Performance 28
5.4 Summary 28
6 Conclusion 30
Acknowledgements 31
References 32