The filtering of XML data is the basis of many complex applications. Lots of algorithms have been proposed to solve this problem [2, 3, 5, 6, 7, 8, 9, 11, 12, 13, 18]. One important challenge is that the number of path queries is huge. It is necessary to take an efficient data structure representing path queries. Another challenge is that these path queries usually vary with time. The maintenance of path queries determines the flexibility and capacity of a filtering system.

In this paper, we introduce a novel approximate method for XML data filtering, which uses Bloom filters representing path queries. In this method, millions of path queries can be stored efficiently. At the same time, it is easy to deal with the change of these path queries. To improve the filtering performance, we introduce a new data structure, Prefix Filters, to decrease the number of candidate paths. Experiments show that our Bloom filter-based method takes less time to build routing table than automaton-based method. And our method has a good performance with acceptable false positive when filtering XML packets of relatively small depth with millions of path queries.