Abstract
Everyone's social life was intertwined with internet social networks during the show's run. These objectives have resulted in a significant shift in how we seek fulfillment in our social lives. Making new friends and staying in touch with them, as well as keeping up with their progress, has become less difficult. However, due to their rapid growth, issues such as sybil (false) profiles and online impersonation have arisen. According to a subsequent analysis, the number of accounts that appear within social media is significantly lower than the number of people who use it. This implies that sybil profiles have been increased in the long run. Recognizing these sybil profiles poses a challenge for online social media providers. There is no feasible course of action available to address these issues. In this paper, we developed a machine learning method for revealing sybil profiles that is feasible and competent. In this section, we will use business classification techniques based on Notable Neural Organize calculation to classify the professionals.
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Verma, P., Nigam, A., Tiwari, G., Mallesham, G. (2022). Sybil Account Detection in Social Network Using Deep Neural Network. In: Sharma, H., Vyas, V.K., Pandey, R.K., Prasad, M. (eds) Proceedings of the International Conference on Intelligent Vision and Computing (ICIVC 2021). ICIVC 2021. Proceedings in Adaptation, Learning and Optimization, vol 15. Springer, Cham. https://doi.org/10.1007/978-3-030-97196-0_11
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