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Data Breach in Social Networks Using Machine Learning

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Advanced Computing (IACC 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1528))

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Abstract

There is a huge concern over privacy of data and security breaches in the upcoming area pertinent to digital services. There is a phenomenal increase in social media sites so as the increase in the volume of data. Therefore, from the linguistic perspective, to understand and analyze the data has become a complex procedure. In this paper, the investigation is done on the information characteristics which are attributed to data breach messages, first we create a questionnaire to know the basic information about the purpose of using social media applications by various users and their awareness regarding the data breach through these applications and secondly, we tried to find out some meaningful insight out of the data collected to reach to some logical conclusion. A quite different pattern is followed by breach information diffusion in contrast to the conventional news channels where the related posts are subjected to wide attention on social media. The widely shared messages among the tech-savvy groups and the personnel involved in the studies related to security are the key factors. Researchers can mine down the grounded insights to the research questions by analyzing the messages in the field of linguistic and visual perspective over social media. This primary research has been done to analyze people’s perception towards digitalization and how the risk of data breach has affected them in using some of the most widely used social media application.

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References

  1. Joshi, U.D., Vanshika, A.P. Singh, T.R. Pahuja, S. Naval, G.S.: Fake Social Media Profile Detection. Machine Learning: Algorithms and Applications by Wiley Publishers (2020)

    Google Scholar 

  2. Gupta, S., Singal, G., Garg, D.: Deep reinforcement learning techniques in diversified domains: a survey. Arch. Computat. Methods Eng. 28(7), 4715–4754 (2021). https://doi.org/10.1007/s11831-021-09552-3

    Article  Google Scholar 

  3. Sprinklr. Why managing social media is crucial in the event of a data breach. Weblog. https://blog.sprinklr.com/wpcontent/uploads/securepdfs/2016/03/20151113_WP_EN_Why_Managing_Social_Media_is_Crucial_in_the_Event_of_Data_Breach_V01.pdf

  4. Frouws, B., Phillips, M., Hassan, A., Twigt, M.: Getting to Europe the whatsapp way: the use of ict in contemporary mixed migration flows to Europe (June 2016). In: Regional Mixed Migration Secretariat Briefing Paper (2016), https://doi.org/10.2139/ssrn.2862592

  5. Evangelos, K., Pedro, T., Ruben, G.: Need fulfillment and experiences on social media: a case on Facebook and WhatsApp. Comput. Human Behav. 55 (Part B), 888–897 (2016). ISSN 0747–5632. https://doi.org/10.1016/j.chb.2015.10.015

  6. O’Sullivan, D., O’O’Sullivan, E., O’Connor, M., Declan, L., John M.: Whatsapp doc. BMJ Innov. 3(4) 238–239 (2017)

    Google Scholar 

  7. Naga, V., Glenn, D.: A Social Network Analysis (SNA) study on data breach concerns over social media. In: 52nd Hawaii International Conference on System Sciences (2019) https://core.ac.uk/download/pdf/211327978.pdf

  8. Abdin, L.: Bots and Fake News: The Role of WhatsApp in the 2018 Brazilian Presidential Election (2019)

    Google Scholar 

  9. SELFKEY: All Data Breaches in 2019 – 2021 – An Alarming Timeline. Weblog. https://selfkey.org/data-breaches-in-2019/

  10. Juma’h, A.H., Alnsour, Y.: The effect of data breaches on company performance. Int. J. Account. Inf. Manag. 28(2), 275–301 (2020). https://doi.org/10.1108/IJAIM-01-2019-0006

    Article  Google Scholar 

  11. livemint: Data, AI can add $400–500bn to India’s GDP by 2025. Weblog. https://www.livemint.com/news/india/data-ai-can-add-450-500-bn-to-india-s-gdp-by-025-nasscom-11597755748693.html

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Mahapatra, M., Gupta, N., Kushwaha, R., Singal, G. (2022). Data Breach in Social Networks Using Machine Learning. In: Garg, D., Jagannathan, S., Gupta, A., Garg, L., Gupta, S. (eds) Advanced Computing. IACC 2021. Communications in Computer and Information Science, vol 1528. Springer, Cham. https://doi.org/10.1007/978-3-030-95502-1_50

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  • DOI: https://doi.org/10.1007/978-3-030-95502-1_50

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-95501-4

  • Online ISBN: 978-3-030-95502-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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