Abstract
A NEW DEFENSE MECHANISM AGAINST SMISHING ATTACKS USING GRAY WOLF OPTIMIZER
*Marwan H. Alsammarraie and Mohamad A. Alfayomi
ABSTRACT
Recently, the phishing attack is one of the critical threats against the Organizations, Internet users, service provider, cloud computing and many other fields in daily life. In the phishing attack, the intruder attempts to defraud the users and leak or steal the credential information, including personal information such as bank account, passwords etc., by sending a fooled email or SMS to redirect the user to an untrusted website. Various methods have been proposed in terms of filtering and detect different types of phishing attacks, however, the researchers and security information experts still studying to find a solution to assure the internet security from phishing and other attacks. Viewing SMS phishing messages are mostly short text and become a relatively low number associated with legitimate messages, new features for quick writing and oversampling technique for imbalanced data utilized to SMS phishing detection. In this research, a novel framework of the SMS phishing detection presented. The proposed method combines feature extraction, oversampling, optimization algorithm for feature selection and classification. The general framework for SMS phishing detection is consists of Data input, Data preprocessing, Feature extraction, Oversampling. Then, Feature optimization using binary Gray Wolf Optimizer Algorithm, Classification using support vector machine (SVM), and results and output.
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