Abstract
Paste sites are largely used for innocent text sharing but they have grown in popularity as venues for criminal operations such as data leaks and publication. This research examines numerous types of sensitive information and the extent to which each can cause damage if compromised. Our proposal intends to develop an efficient scoring scheme for determining the sensitivity of information included within a paste’s body. We designed a scraper to monitor two surface web and two dark web paste sites and extract and score various aspects from the obtained data. The findings indicated that surface web paste sites featured a greater amount of sensitive material than dark web paste sites.
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Singh, R., Amritha, P.P., Sethumadhavan, M. (2022). Scoring Scheme to Determine the Sensitive Information Level in Surface Web and Dark Web. In: Singh, M., Tyagi, V., Gupta, P.K., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2022. Communications in Computer and Information Science, vol 1613. Springer, Cham. https://doi.org/10.1007/978-3-031-12638-3_14
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DOI: https://doi.org/10.1007/978-3-031-12638-3_14
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