The Role of Fuzzy Logic in Improving Accuracy of Phishing Detection System
Neelam Badi1, Mayank Patel2, Amit Sinhal3
1Neelam Badi, student of Geetanjali Institute of Technical Studies, Udaipur, (Rajasthan), India.
2Dr. Mayank Patel, Associate Professor in the Department of Computer Science and Engineering at Geetanjali Institute of Technical Studies, Udaipur, (Rajasthan), India.
3Dr Amit Sinhal, Department of Computer Science and Engineering at Geetanjali Institute of Technical Studies, Udaipur, (Rajasthan), India.
Manuscript received on 02 June 2019 | Revised Manuscript received on 10 June 2019 | Manuscript published on 30 June 2019 | PP: 3162-3164 | Volume-8 Issue-8, June 2019 | Retrieval Number: H7317068819/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Considering the ease of implementation, the wide vector of targets it addresses and the flexibility to adapt and breach sophisticated technologies, phishing attacks are becoming widely popular among cyber attackers to gain sensitive user data and credentials. Despite the humongous mass of this form of cyber-attack, McAfee Labs Threats Report 2018  suggests that 97% of the total number of email users were not able to identify sophisticated phishing content (URL, email, links, etc). Hence, a number of anti-phishing and phishing detection tools based on various techniques such as the blacklist, heuristic, visual, data mining, machine learning, etc are available.However, the subjective ambiguity and the vastness in methodologies used for phishing attacks makes real-time detection and identification of such malicious URLs to be a very complicated and dynamic process, that even machine learning cannot address. Considering the vagueness of phishy URLs, the human cognition-like natural approach of fuzzy logic makes it a suitable choice for tackling the quality factors of the findings rather than just numerical values. In this paper, we will show how usage of fuzzy logic can improve the accuracy of machine learning based phishing detection systems and provide a resilient and smart model for better cyber security.
Keyword: Anti-Phishing, Cyber Security, Fuzzy Logic, Hacking, Machine Learning, Phishing Attack, Phishing Detection.
Scope of the Article: System Integration.