Abstract
High performance signature matching against a large dictionary is of great importance in network security applications. The many-core SIMD GPU is a competitive choice for signature matching. In this paper, a hybrid parallel signature matching model (HPSMM) using SIMD GPU is proposed, which uses pattern set partition and input text partition together. Then the problem of load balancing for multiprocessors in the GPU is discussed carefully, and a balanced pattern set partition method (BPSPM) employed in HPSMM is introduced. Experiments demonstrate that using pattern set partition and input text partition together can help achieve a better performance, and the proposed BPSPM-Length works well in load balancing.
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References
Antonatos, S., Anagnostakis, K.G., Markatos, E.P.: Generating realistic workloads for network intrusion detection systems. In: ACM SIGSOFT Software Engineering Notes, vol. 29, pp. 207–215 (2004)
Tuck, N., Sherwood, T., Calder, B., Varghese, G.: Deterministic memory-efficient string matching algorithms for intrusion detection. In: Proc. of INFOCOM, vol. 4, pp. 2628–2639 (2004)
Clark, C.R., Schimmel, D.E.: Scalable Pattern Matching for High Speed Networks. In: Proceedings of the 12th Annual IEEE Symposium on Field-Programmable Custom Computing Machines, pp. 249–257. IEEE Computer Society, Washington (2004)
Tan, L., Sherwood, T.: A High Throughput String Matching Architecture for Intrusion Detection and Prevention. In: Proceedings of the 32nd annual international symposium on Computer Architecture, vol. 4, pp. 112–122 (2005)
Dharmapurikar, S., Lockwood, J.W.: Fast and scalable pattern matching for network intrusion detection systems. IEEE Journal on Selected Areas in Communications 24, 1781–1791 (2006)
Yu, F., Katz, R.H., Lakshman, T.V.: Gigabit rate packet pattern-matching using TCAM. In: Proceedings of the 12th IEEE International Conference on Network Protocols, 2004, pp. 174–183 (2004)
Alicherry, M., Muthuprasanna, M., Kumar, V.: High speed pattern matching for network IDS/IPS, pp. 187–196. IEEE Computer Society, Los Alamitos (2006)
Lei, S., Yue, Z., Jianming, Y., Bo, X., Bin, L., Jun, L.: On the Extreme Parallelism Inside Next-Generation Network Processors. In: Proceedings of INFOCOM, pp. 1379–1387 (2007)
Ni, J., Lin, C., Chen, Z., Ungsunan, P.: A Fast Multi-pattern Matching Algorithm for Deep Packet Inspection on a Network Processor. In: International Conference on Parallel Processing (2007)
Nvidia G80 Specs, http://www.nvidian.com/page/8800_features.html
Nvidia CUDA Programming Guide 2.1., http://developer.download.nvidia.com/compute/cuda/2_1/NVIDIA_CUDA_Programming_Guide_2.1.pdf
Marziale, L., Richard, G.G., Roussev, V.: Massive threading: Using GPUs to increase the performance of digital forensics tools. Digital Investigation 4, 73–81 (2007)
Vasiliadis, G., Antonatos, S., Polychronakis, M., Markatos, E.P., Ioannidis, S.: Gnort: High performance network intrusion detection using graphics processors. In: Lippmann, R., Kirda, E., Trachtenberg, A. (eds.) RAID 2008. LNCS, vol. 5230, pp. 116–134. Springer, Heidelberg (2008)
Aho, A.V., Corasick, M.J.: Efficient String Matching: An Aid to Bibliographic Search. Communications of the ACM 18, 333–340 (1975)
Goyal, N., Ormont, J., Smith, R., Sankaralingam, K., Estan, C.: Signature Matching in Network Processing using SIMD/GPU Architectures. UW CS technical report 1628 (January 2008)
Smith, R., Estan, C., Jha, S., Kong, S.: Deflating the big bang: fast and scalable deep packet inspection with extended finite automata. In: Proceedings of the ACM SIGCOMM 2008 conference on Data communication, pp. 207–218. ACM, New York (2008)
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Wu, C., Yin, J., Cai, Z., Zhu, E., Chen, J. (2009). A Hybrid Parallel Signature Matching Model for Network Security Applications Using SIMD GPU. In: Dou, Y., Gruber, R., Joller, J.M. (eds) Advanced Parallel Processing Technologies. APPT 2009. Lecture Notes in Computer Science, vol 5737. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03644-6_15
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DOI: https://doi.org/10.1007/978-3-642-03644-6_15
Publisher Name: Springer, Berlin, Heidelberg
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