Year: 2024
Type: article
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
DOI: 10.55041/ijsrem20280
Author: Praneeth Vadlapati
Institution: VIT-AP University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4405609053