  The last years of the 20 th century and the beginning of the 21 th mark the
facilitation trend of our real life due to the big development and progress of
the computers and other intelligent devices. Algorithms based on artificial
intelligence are basically a part of the software. The transmitted information
by Internet or LAN arises continuously and it is expected that the protection
of the data has been ensured. The aim of the present paper is to reveal false
names of users' accounts as a result of hackers' attacks. The probability a
given account to be either false or actual is calculated using a novel approach
combining machine learning analysis (especially clusters' analysis) with chaos
theory. The suspected account will be used as a pattern and by classification
techniques clusters will be formed with a respective probability this name to
be false. This investigation puts two main purposes: First, to determine if
there exists a trend of appearance of the similar usernames, which arises
during the creation of new accounts. Second, to detect the false usernames and
to discriminate those from the real ones, independently of that if two types of
accounts are generated with the same speed. These security systems are applied
in different areas, where the security of the data in users' accounts is
strictly required. For example, they can be used in on-line voting for
balloting, in studying the social opinion by inquiries, in protection of the
information in different user accounts of given system etc.
