  Fraud and terrorism have a close connect in terms of the processes that
enables and promote them. In the era of Internet, its various services that
include Web, e-mail, social networks, blogs, instant messaging, chats, etc. are
used in terrorism not only for communication but also for i) creation of
ideology, ii) resource gathering, iii) recruitment, indoctrination and
training, iv) creation of terror network, and v) information gathering. A major
challenge for law enforcement and intelligence agencies is efficient and
accurate gathering of relevant and growing volume of crime data. This paper
reports on use of established Na\"ive Bayesian filter for classification of
threat e-mails. Efficiency in filtering threat e-mail by use of three different
Na\"ive Bayesian filter approaches i.e. single keywords, weighted multiple
keywords and weighted multiple keywords with keyword context matching are
evaluated on a threat e-mail corpus created by extracting data from sources
that are very close to terrorism.
