Today, millions of devices produce billions of network requests to the servers. All these request packets need to be scanned for security. Hence, providing network security and privacy requires filtering and deduplication of packets. In case of filtering, Bloom Filter data structure is the best alternative. Bloom Filter is a probabilistic data structure for membership filtering and it is capable of filtering massive amounts of data using a small memory footprint. However, Bloom Filter is not popular in many applications due to its false positive and false negative issues. Currently, many network security and privacy techniques are implementing Bloom Filter. In this paper, we discuss various facts on Bloom Filter. We advocate that Bloom Filter is the first layer of defence for network security and privacy. Furthermore, we discuss how Bloom Filter provides better security against various network attacks.