AI-enabled phishing link detection and alert system
Abstract & Details
Research Area
Artificial Intelligence
Keywords
Phishing Detection
Decision Tree
Machine-learning
Abstract
Phishing attacks are an ever-present and substantial menace in the realm of cyber-security. They are cunningly designed to deceive both individuals and organizations, ultimately leading to the unauthorized ac-quisition of sensitive personal information, account credentials, credit card details, or-ganizational data, or even client passwords, all for malicious purposes. These malicious actors create phishing websites with re-markable skill, expertly mimicking legiti-mate ones, making it exceptionally chal-lenging to distinguish them from genuine sites. Consequently, phishing attacks stand as one of the most perilous and frequently encountered threats faced by both individ-uals and organizations. It is important to understand that web URLs serve as gate-ways to access information on the internet, and these very gateways are exploited by phishing attackers. Recognizing the gravity of this issue, this review paper is dedicated to raising awareness about phishing attacks, bolstering detection methods, and advocat-ing proactive measures for preventing phishing among its readership. Given the staggering volume of phishing emails and messages inundating inboxes daily, it is increasingly arduous for companies and individuals to identify and counter every instance of phishing at
tempts. Hence, it becomes paramount to develop and implement effective strategies for combating this persistent and evolving threat
License
This work is licensed under a Creative
Commons
Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | BHALARUBENI V S | BANNARI AMMAN INSTITUTE OF TECHNOLOGY |
| 2 | SUSILKUMAR K | BANNARI AMMAN INSTITUTE OF TECHNOLOGY |
| 3 | HARISH KUMAR K | BANNARI AMMAN INSTITUTE OF TECHNOLOGY |
| 4 | Dr LAKSHMANAPRAKASH S | BANNARI AMMAN INSTITUTE OF TECHNOLOGY |
How to Cite
Use the following formats to cite this article in your research.
APA Style
S, BHALARUBENI V, K, SUSILKUMAR, K, HARISH KUMAR, & S, Dr LAKSHMANAPRAKASH (2023). AI-enabled phishing link detection and alert system. International Journal of Advance Research and Innovative Ideas In Education, 9(5), 1385-1389.
MLA Style
S, BHALARUBENI V, et al. "AI-enabled phishing link detection and alert system." International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 5, 2023, pp. 1385-1389.
IEEE Style
BHALARUBENI V S, SUSILKUMAR K, HARISH KUMAR K, and Dr LAKSHMANAPRAKASH S, "AI-enabled phishing link detection and alert system," International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 5, pp. 1385-1389, 2023.
Vancouver Style
S BHALARUBENI V, K SUSILKUMAR, K HARISH KUMAR, S Dr LAKSHMANAPRAKASH. AI-enabled phishing link detection and alert system. International Journal of Advance Research and Innovative Ideas In Education. 2023;9(5):1385-1389.
Harvard Style
S, BHALARUBENI V, K, SUSILKUMAR, K, HARISH KUMAR, & S, Dr LAKSHMANAPRAKASH (2023) 'AI-enabled phishing link detection and alert system', International Journal of Advance Research and Innovative Ideas In Education, 9(5), pp. 1385-1389.
Chicago Style
S, BHALARUBENI V, et al. "AI-enabled phishing link detection and alert system." International Journal of Advance Research and Innovative Ideas In Education 9, no. 5 (2023): 1385-1389.
Turabian Style
S, BHALARUBENI V, et al. "AI-enabled phishing link detection and alert system." International Journal of Advance Research and Innovative Ideas In Education 9, no. 5 (2023): 1385-1389.
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