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Change-point detection method on 100Gb/s Ethernet interface

This paper deals with hardware acceleration of statistical methods for detection of anomalies on 100Gb/s Ethernet. The approach is demonstrated by implementing a sequential Non-Parametric Cumulative Sum (NP-CUSUM) procedure. We use high-level synthesis in combination with emerging software defined monitoring (SDM) methodology for rapid development of FPGA-based hardware-accelerated network monitoring applications. The implemented method offloads detection of network attacks and anomalies directly into an FPGA chip. The parallel nature of FPGA allows for simultaneous detection of various kinds of anomalies. Our results show that hardware acceleration of statistical methods using the SDM concept with high-level synthesis from C/C++ is possible and very promising for traffic analysis and anomaly detection in high-speed 100Gb/s networks.