Deep Learning Approach in Anti-Phishing Technology

Abstract

A significant rise in electronic trade, or consumer-to-consumer online transactions, has occurred recently as a result of advances in Internet and cloud technologies. Malware, phishing, ransomware, man- in-the-middle attacks and other techniques are just a few of the ways cybercriminals utilize to begin a cyber attack. Phishing is a form of social engineering or a cyber security assault in which nefarious actors send messages acting as reliable individuals. Phishing attacks use complex strategies, techniques, and technologies to obtain sensitive data, including content injection, online social networks etc. Real-time identification of phishing sites is challenging with the available anti-phishing tools. Therefore, a protected and open system is required that allows the user to directly verify the site. The long short- term memory (LSTM) algorithm and the convolutional neural network (CNN) were combined to develop a hybrid deep learning model (LCR). The goal of this research was to develop a web browser named Phishing Detection Browser (PD Browser) that can identify phishing attacks using deep learning. Keywords— Phishing, Anti-Phishing, Deep learning, Hybrid Deep Learning Model