Impact Of Web (URL) Phishing and Its Detection

Web phishing, machine learning, real time URL analysis detection techniques

Authors

  • Kunle Oloyede Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA, United States
  • Chinenye Obunadike Anambra State University Uli, Anambra State , Nigeria
  • Simo Yufenyuy Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA, United States
  • Emmanuel Elom Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA, United States
  • Abdul-Waliyyu Bello Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA, United States
  • Somtobe Olisah Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA, United States
  • Callistus Obunadike Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA, United States
  • Oluwadamilola Ogunleye George Washington University, Washington DC, USA, United States
  • Sulaimon Adeniji University of Lagos, Lagos State, Nigeria
Vol. 12 No. 04 (2024)
Mathematics and Statistics
April 13, 2024

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Abstract: Web phishing is a persuasive and evolving cyber threat that poses significant risks to individuals, businesses, and organizations in the modern digital age. This paper aims to provide an overview of web phishing, focusing on its methods, detection techniques, and prevention. Phishing attacks occur when malicious actors use deceptive practices to trick people into divulging sensitive or classified information such as passwords, credit card details, or personal data. These attacks primarily manifest through emails, websites, or social engineering tactics. Phishing emails often impersonate trusted entities and lure recipients into clicking on malicious links or downloading harmful attachments. Web phishing involves using fraudulent websites that mimic legitimate ones to steal user information or deliver malware. Detecting web phishing attacks is an ongoing challenge due to the sophistication of attackers. Several detection techniques have been developed, including heuristic analysis, machine learning algorithms, and real-time URL analysis. These methods analyze various attributes of websites and emails to identify suspicious patterns or behaviors. Detecting web phishing is equally essential. Effective prevention strategies include user education and awareness programs, using two-factor authentication, regular software updates, and deploying advanced email filtering and anti-phishing tools. User training is crucial in helping individuals recognize phishing attempts and avoid falling victim to them.