Skip to main content

Abstract

Statistical methods and computational capabilities have grown tremendously in the past few decades. Along with the growing interest in Artificial Intelligence and Machine Learning, there is also significant development in the field of Cloud Computing and Big data. Nowadays, we use a wide range of tools that have given us the power to stripe this data, process them, and analyze or even predict outcomes using this data.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Crane, C. (2021, March 12). What is homomorphic encryption? Retrieved April 07, 2021, from https://www.thesslstore.com/blog/what-is-homomorphic-encryption/

    Google Scholar 

  2. What is homomorphic encryption? (2021, January 13). Retrieved April 07, 2021, from https://www.experfy.com/blog/bigdata-cloud/what-is-homomorphic-encryption/

  3. Gentry, Craig. “Fully homomorphic encryption using ideal lattices.” In Proceedings of the forty-first annual ACM symposium on Theory of computing, pp. 169–178. 2009.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Sniatala, P., Iyengar, S., Ramani, S.K. (2021). Homomorphic Encryption. In: Evolution of Smart Sensing Ecosystems with Tamper Evident Security. Springer, Cham. https://doi.org/10.1007/978-3-030-77764-7_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-77764-7_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-77763-0

  • Online ISBN: 978-3-030-77764-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics