Anzeige
Erschienen in:
2017 | OriginalPaper | Buchkapitel
Detecting Targeted Malicious E-Mail Using Linear Regression Algorithm with Data Mining Techniques
verfasst von : A. Sesha Rao, P. S. Avadhani, Nandita Bhanja Chaudhuri
Erschienen in: Computational Intelligence in Data Mining
Verlag: Springer Singapore
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Abstract
E-mail is the most fundamental means of communication. It is the focus of attack by the terrorists, e-mail spammers, imposters, business fraudsters, and hackers. To combat this, different data mining classifiers are used to identify the spam mails. This paper introduces a system that imports data from the e-mail accounts and performs preprocessing techniques like file conversions that are appropriate to conduct the experiments, searching for frequency of a word by Knuth–Morris–Pratt (KMP) string searching algorithm, and feature selection using principal component analysis (PCA) are applied. Next, linear regression classification is used to predict the spam mails. Then, association rule mining is performed. The mean absolute error and root mean squared error for the training data and test data are computed. The errors of the training and test data sets are negligible which indicates the classifier is well trained. Finally, the results are displayed by the visualization techniques.