Spam Detection with Complex-Valued Neural Network Using Behavior-Based Characteristics

The paper proposes the use of the complex-valued neural network to detect spam. The main contributions of this work are two-fold. First, we present a new model based on the CVNN for classifying personal E-mails. We changed the input of the email into 2-dimensional vector. The complex-valued neural network is superior for handling 2-dimensional vector data stream, because the input of the complex-valued neural network has real part and imaginary part. Second, the behavior-based characteristics are extracted as most important features of the E-mail. The results reveal that the proposed technology is reliable, efficient and scalable.