A. Aldo Tenis^*, R. Santhosh

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2625-2641, 2023, DOI:10.32604/csse.2023.036626

Abstract The social engineering cyber-attack is where culprits mislead the users by getting the login details which provides the information to the evil server called phishing. The deep learning approaches and the machine learning are compared in the proposed system for presenting the methodology that can detect phishing websites via Uniform Resource Locator (URLs) analysis. The legal class is composed of the home pages with no inclusion of login forms in most of the present modern solutions, which deals with the detection of phishing. Contrarily, the URLs in both classes from the login page due, considering the representation of a real… More >

Diana T. Mosa^1,2, Mahmoud Y. Shams^3,*, Amr A. Abohany², El-Sayed M. El-kenawy⁴, M. Thabet⁵

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1271-1290, 2023, DOI:10.32604/cmc.2023.036422

Abstract Cyber Attacks are critical and destructive to all industry sectors. They affect social engineering by allowing unapproved access to a Personal Computer (PC) that breaks the corrupted system and threatens humans. The defense of security requires understanding the nature of Cyber Attacks, so prevention becomes easy and accurate by acquiring sufficient knowledge about various features of Cyber Attacks. Cyber-Security proposes appropriate actions that can handle and block attacks. A phishing attack is one of the cybercrimes in which users follow a link to illegal websites that will persuade them to divulge their private information. One of the online security challenges… More >

Saeed M. Alshahrani¹, Nayyar Ahmed Khan^1,*, Jameel Almalki², Waleed Al Shehri²

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5625-5640, 2022, DOI:10.32604/cmc.2022.030982

Abstract The continuous destruction and frauds prevailing due to phishing URLs make it an indispensable area for research. Various techniques are adopted in the detection process, including neural networks, machine learning, or hybrid techniques. A novel detection model is proposed that uses data mining with the Particle Swarm Optimization technique (PSO) to increase and empower the method of detecting phishing URLs. Feature selection based on various techniques to identify the phishing candidates from the URL is conducted. In this approach, the features mined from the URL are extracted using data mining rules. The features are selected on the basis of URL… More >