Abstract
This paper presents a solution to mitigate real-world phishing attacks. By synergizing data structures, search algorithms, and open-source datasets, the solution precisely detects inputs resembling previous phishing attempts, enabling informed user decisions. Through rigorous testing, the solution attains high accuracy, outperforming existing technologies. Its real-time nature, facilitating dataset updates, curtails phishing success rates, fortifying digital security. This fosters a safer online milieu and underscores the need for proactive cyber defense against evolving threats.
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Acknowledgements
The authors deeply acknowledge the Professors from Singapore Institute of Technology (SIT) for their help and support for this project research. The authors would also like to declare that there is no conflict of interest.
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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Ng, J.K., Loo, B.J.L., Lan, E.Y., Leong, S.M., Teo, C.J., Guo, H. (2023). Solution for Detecting Phishing Attacks. In: Lu, J., et al. Proceedings of the 9th IRC Conference on Science, Engineering, and Technology. IRC-SET 2023. Springer, Singapore. https://doi.org/10.1007/978-981-99-8369-8_50
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DOI: https://doi.org/10.1007/978-981-99-8369-8_50
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