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© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM20280

TokEncryption: Enhanced Hashing of Text using Tokenization

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM20280

Volume:

6 |

5 |

May 2022

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM20280

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

PV

Praneeth Vadlapati

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Abstract

In the current digital space, the security of sensitive information, such as passwords and private data, is of high importance. Traditional hashing methods might not adequately address data privacy concerns or vulnerabilities created due to weak passwords. Tokenization methods are utilized in natural language processing (NLP). This paper introduces a method called “TokEncryption” to utilize tokens for one-way encryption of text called hashing. A tokenizer is used to generate tokens for an input text, which are utilized to encrypt the text to create secure encrypted text. Different characters of the text are encrypted using distinct tokens to ensure a variation in encryption patterns throughout the resultant text. The process enhances data security and privacy using an unconventional approach that makes it secure from attackers attempting to reconstruct the text. The system can be used in addition to the existing encryption approaches. The results show a successful encryption of text. Weak passwords are successfully encrypted to create strong passwords with multiple types of characters, including alphabets, numbers, and special characters. The code is available at github.com/Pro-GenAI/TokEncryption.

KEYWORDS

data privacy data security data encryption natural language processing (NLP) tokenization cryptography information security

Cite This Article

Praneeth Vadlapati, "TokEncryption: Enhanced Hashing of Text using Tokenization," International Journal of Scientific Research in Engineering and Management, vol. 6, no. 5, May 2022. https://doi.org/10.55041/IJSREM20280

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Publication Date

7/11/2024

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Double-Blind Peer Review

Review Rounds: 2

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5

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The authors declare no conflict of interest related to this research work.

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