Deep packet inspection using parallel bloom filters

Abstract

There is a class of packet processing applications that inspect packets deeper than the protocol headers to analyze content. For instance, network security applications must drop packets containing certain malicious Internet worms or computer viruses carried in a packet payload. Content forwarding applications look at the hypertext transport protocol headers and distribute the requests among the servers for load balancing. Packet inspection applications, when deployed at router ports, must operate at wire speeds. With networking speeds doubling every year, it is becoming increasingly difficult for software-based packet monitors to keep up with the line rates. We describe a hardware-based technique using Bloom filters, which can detect strings in streaming data without degrading network throughput. A Bloom filter is a data structure that stores a set of signatures compactly by computing multiple hash functions on each member of the set. This technique queries a database of strings to check for the membership of a particular string. The answer to this query can be false positive but never a false negative. An important property of this data structure is that the computation time involved in performing the query is independent of the number of strings in the database provided the memory used by the data structure scales linearly with the number of strings stored in it. Furthermore, the amount of storage required by the Bloom filter for each string is independent of its length.