Prevention of Phishing attacks using AI Algorithm

A particularly successful type of cybercrime that allows criminals to trick people and steal crucial data is phishing. Phishing is currently one of the most common online scams. Phishing assaults may result in significant losses for sensitive information, identity theft, businesses, and the government are just some of their victims. Phishing websites are widespread entrance points for social engineering attacks carried out online, including countless website frauds. When such attacks occur, by copying the acts of reputable websites, the attacker(s) create website pages and send the URL(s) to the targeted recipients via social networking, texting, or spam messaging. However, the number of victims is rising exponentially as a result of inadequate security technologies. Studies have categorized phishing attacks by basic phishing methods and defenses, ignoring the significance of the end-to-end phishing lifecycle. This article offers a fresh, in-depth model of phishing that takes into account attack stages, different types of attackers, threats, targets, attack channels, and attack tactics. The proposed anatomy will also make it easier for readers to understand how long a phishing effort lasts, increasing knowledge of these attacks and the techniques used as well as aiding in the creation of a comprehensive anti-phishing system. Due to the anonymity and lack of regulations on the Internet, phishing attacks are more likely to be successful. The effectiveness of the phishing detection system is limited, according to existing research. To protect consumers from cyberattacks, a clever strategy is needed. A detection method used in this work is based on artificial intelligence-based LSTM which has produced satisfactory performance and accuracy.