چکیده (انگلیسی):

information that appears to be a realistic. It is mandatory to trace the origin of the email and the
authors/systems responsible for generating such emails. Representative signatures of email are to be
generated using lexical and syntactic based methods. The signature of each email has huge dimensions and
is called a vector/pattern. In order to make it convenient for subsequent processing, the huge dimension of
the signature is converted into 2-dimensional pattern using Fisher’s Linear Discriminant Function (FLD).
The 2-dimensional patterns of the signatures of emails under consideration are used as training data for the
Radial Basis Function (RBF) network which can learn non-linear data. The classification of email is very
well achieved due to transformation by FLD and training by RBF. The proposed method helps in building
signature database for accurate categorization in email forensics. The proposed combination of algorithms
helps in clustering the different emails generated by an author or by a system.