Hardware based virus protection systems are required for identifying the malicious content and further removing it from network streams. Network Intrusion Detection System(NIDS) is needed to protect the end user machines from threats. An effective NIDS is therefore a network security system capable of protecting the end user machines well before a threat affects.NIDS requires a space efficient data base for detection of threats in high speed conditions. Bloom Filters are one of the security filters that consume significant power to detect and then filter out malicious content. A Bloom filter is a space efficient randomized data structure for representing a set in order to support membership queries. The aim of this paper is to compare the different architectures of Bloom filter like Standard Bloom filter, pipelined bloom filter, counting Bloom filter and parallel processing architecture of bloom filter in terms of their merits and demerits by using algorithmic & architectural techniques.