Abstract
Social Engineering is an emerging concept that was initially coined in the year (1980s). Initially it was encountered, when people use to fool others by masquerading names and contact details to steal the assets of others. As the needle moves on the whole world is affected by this disease. It came across many cyber attacks like phishing, spamming, hacking etc. In all the methods the basic thing which prevails most is the presence of malicious URLs. These URLs plays an important role in making social engineering a success. In this paper we have proposed a solution that prevents this type attack by helping in detecting the malicious URLs. The model uses the Artificial Bee Colony approach to optimize and detect that the target website is genuine or not. Once we come to know that the link we are going to click is safe enough than maximum percent of the problem is solved.
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Bhardwaj, T., Sharma, T.K., Pandit, M.R. (2014). Social Engineering Prevention by Detecting Malicious URLs Using Artificial Bee Colony Algorithm. In: Pant, M., Deep, K., Nagar, A., Bansal, J. (eds) Proceedings of the Third International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 258. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1771-8_31
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DOI: https://doi.org/10.1007/978-81-322-1771-8_31
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