Abstract
Social networking sites have made its impact in converting a passive reader into content contributor. This has turned online social networks into a commercial sphere. The site demands creation of public profiles. The main goal of online social networks is to share content with maximum users. This enormous sharing of information can lead to malicious users leverage the privacy of an individual. An attempt has been made in this paper to improve privacy preservation by calculating the reliability of a user, can entrust on his/her peer using the content sharing, Machine Learning and tone analysis. The recorded metrics and transaction details are stored in IPFS.
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Neethu, M.R., Harini, N., Abirami, K. (2021). Investigating Peers in Social Networks: Reliable or Unreilable. In: Tripathy, A., Sarkar, M., Sahoo, J., Li, KC., Chinara, S. (eds) Advances in Distributed Computing and Machine Learning. Lecture Notes in Networks and Systems, vol 127. Springer, Singapore. https://doi.org/10.1007/978-981-15-4218-3_18
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DOI: https://doi.org/10.1007/978-981-15-4218-3_18
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