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Privacy Preserving Datamining Techniques with Data Security in Data Transformation

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Computer Communication, Networking and IoT

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 459))

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Abstract

Data mining is the process of pattern recovery in multiple database fields. Big data is the great volume of data that is being processed in the environment of data mining. It is therefore impossible to use hand-held database management tools or typical data processing programme to collect data sets, so that data mining techniques have been deployed. An effective data transformation is a vital prerequisite for facilitating an efficient process for discovering information on a wider scale. I would want to mention that in present PPDM research, certain fundamental problems are not addressed. First of all, Privacy Preserving Data Mining (PPDM) does not have a standard terminology. Second, for the centralised database, most algorithms are developed. However, data are commonly stored in several sites in today’s global digital world. Third, many algorithms are focused on safeguarding the privacy of personal information, but do not focus on data mining results. There is no single approach to obtain data and to hide limitations. Fourth, each algorithm is specialised on data mining tasks primarily. No single strategy can work for any type of data clustering algorithm. Part of data privacy also is a crucial role in transforming data after data storage. These can be used as a guide to future PPDM research. Present research explores the privacy of data mining with various ways to approach the scope of new development approach.

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Authors and Affiliations

  1. Department of Computer Science, Gitam (Deemed to be University), Visakhapatnam, 530045, India

    Bonagiri Jyothi & V. Naga Lakshmi

Authors
  1. Bonagiri Jyothi
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  2. V. Naga Lakshmi
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Correspondence to Bonagiri Jyothi .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, India

    Suresh Chandra Satapathy

  2. Western Norway University of Applied Sciences, Bergen, Norway

    Jerry Chun-Wei Lin

  3. University of Malaya, Kuala Lumpur, Malaysia

    Lai Khin Wee

  4. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial College of Engineering and Management (SRMCEM), Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  5. Dept of Computer Science and Engineering, Dayananda Sagar University, Bengaluru, India

    T. M. Rajesh

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Jyothi, B., Lakshmi, V.N. (2023). Privacy Preserving Datamining Techniques with Data Security in Data Transformation. In: Satapathy, S.C., Lin, J.CW., Wee, L.K., Bhateja, V., Rajesh, T.M. (eds) Computer Communication, Networking and IoT. Lecture Notes in Networks and Systems, vol 459. Springer, Singapore. https://doi.org/10.1007/978-981-19-1976-3_34

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  • DOI: https://doi.org/10.1007/978-981-19-1976-3_34

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-1975-6

  • Online ISBN: 978-981-19-1976-3

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