Efficient string matching: an aid to bibliographic search
Communications of the ACM
Programming Techniques: Regular expression search algorithm
Communications of the ACM
Fast and memory-efficient regular expression matching for deep packet inspection
Proceedings of the 2006 ACM/IEEE symposium on Architecture for networking and communications systems
An improved algorithm to accelerate regular expression evaluation
Proceedings of the 3rd ACM/IEEE Symposium on Architecture for networking and communications systems
XFA: Faster Signature Matching with Extended Automata
SP '08 Proceedings of the 2008 IEEE Symposium on Security and Privacy
Regular Expression Matching on Graphics Hardware for Intrusion Detection
RAID '09 Proceedings of the 12th International Symposium on Recent Advances in Intrusion Detection
Multi-byte Regular Expression Matching with Speculation
RAID '09 Proceedings of the 12th International Symposium on Recent Advances in Intrusion Detection
Slimming down Deep packet inspection systems
INFOCOM'09 Proceedings of the 28th IEEE international conference on Computer Communications Workshops
IP routing processing with graphic processors
Proceedings of the Conference on Design, Automation and Test in Europe
iNFAnt: NFA pattern matching on GPGPU devices
ACM SIGCOMM Computer Communication Review
Gregex: GPU Based High Speed Regular Expression Matching Engine
IMIS '11 Proceedings of the 2011 Fifth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing
GPU-based NFA implementation for memory efficient high speed regular expression matching
Proceedings of the 17th ACM SIGPLAN symposium on Principles and Practice of Parallel Programming
Issues and future directions in traffic classification
IEEE Network: The Magazine of Global Internetworking
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Traffic Identification is a crucial task performed by ISP administrators to evaluate and improve network service quality. Deep Packet Inspection (DPI) is a well-known technique used to identify networked traffic. DPI relies mostly on Regular Expressions (REs) evaluated by Finite Automata. Many previous studies have investigated the impacts on the classification accuracy of such systems when inspecting only a portion of the traffic. However, none have discussed the real impacts on the overall system throughput. This work presents a novel technique to perform DPI on Graphics Processing Units (GPU) called Flow-Based Traffic Identification (FBTI) and a proof-of-concept prototype analysis. Basically we want to increase DPI systems? performance on commodity platforms as well as their capacity to identify networked traffic on high speed links. By combining Deterministic Finite Automaton (DFA) for evaluating REs and flow-level packet sampling we achieve a raw performance of over 60 Gbps on GPUs. Our prototype solution could reach a real throughput of over 12 Gbps, measured as the identified volume of flows.