计算机科学
加速
网络数据包
可扩展性
现场可编程门阵列
数据包处理
网络处理器
应用层
入侵检测系统
嵌入式系统
计算机网络
并行计算
操作系统
人工智能
软件
作者
V. Jyothi,Sateesh Addepalli,Ramesh Karri
出处
期刊:IEEE transactions on multi-scale computing systems
[Institute of Electrical and Electronics Engineers]
日期:2018-01-01
卷期号:4 (1): 55-68
被引量:10
标识
DOI:10.1109/tmscs.2017.2765324
摘要
Network Intrusion Detection Systems (NIDS) and Anti-Denial-of-Service (DoS) employ Deep Packet Inspection (DPI) which provides visibility to the content of payload to detect network attacks. All DPI engines assume a pre-processing step that extracts the various protocol-specific fields. However, application layer (L7) field extraction is computationally expensive. We propose a novel Deep Packet Field Extraction Engine (DPFEE) for application layer field extraction to hardware. DPFEE is a content-aware, grammar-based, Layer 7 programmable field extraction engine for text-based protocols. Our prototype DPFEE implementation for the Session Initiation Protocol (SIP) and HTTP protocol on a single FPGA, achieves a bandwidth of 408.5 Gbps and this can be scaled beyond 500 Gbps. Single DPFEE exhibits a speedup of 24X-89X against widely used preprocessors. Even against 12 multi-instances of a preprocessor, single DPFEE demonstrated a speedup of 4.7-7.4X. Single DPFEE achieved 3.14X higher bandwidth, 1020X lower latency, and 106X lower power consumption, when compared with 200 parallel streams of GPU accelerated preprocessor.
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