Automatic protocol field inference for deeper protocol understanding

2015 IFIP Networking Conference (IFIP Networking)(2015)

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摘要
Security tools have evolved dramatically in the recent years to combat the increasingly complex nature of attacks, but to be effective these tools need to be configured by experts that understand network protocols thoroughly. In this paper we present FieldHunter, which automatically extracts fields and infers their types; providing this much needed information to the security experts for keeping pace with the increasing rate of new network applications and their underlying protocols. FieldHunter relies on collecting application messages from multiple sessions and then applying statistical correlations is able to infer the types of the fields. These statistical correlations can be between different messages or other associations with meta-data such as message length, client or server IPs. Our system is designed to extract and infer fields from both binary and textual protocols. We evaluated FieldHunter on real network traffic collected in ISP networks from three different continents. FieldHunter was able to extract security relevant fields and infer their nature for well documented network protocols (such as DNS and MSNP) as well as protocols for which the specifications are not publicly available (such as SopCast) and from malware such as (Ramnit).
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关键词
automatic protocol field inference,protocol understanding,security tool,network protocol,FieldHunter,field extraction,statistical correlation,metadata,message length,client IP,server IP,textual protocol,binary protocol,network traffic,ISP network,DNS,MSNP,SopCast,malware,Ramnit,Internet service provider,domain name system,Internet protocol,Microsoft notification protocol
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