{"title":"DPFEE: A High Performance Scalable Pre-Processor for Network Security Systems","authors":"Vinayaka Jyothi;Sateesh K. Addepalli;Ramesh Karri","doi":"10.1109/TMSCS.2017.2765324","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":100643,"journal":{"name":"IEEE Transactions on Multi-Scale Computing Systems","volume":"4 1","pages":"55-68"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TMSCS.2017.2765324","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Multi-Scale Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/8078262/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
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.