2 Questions each on in separate document

Running head: TOKENIZATION 1

TOKENIZATION 6

Tokenization

Tokenization refers to the practice of protecting sensitive data by replacing it with an algorithmically developed number. This number is called tokenization, and the process is used to prevent credit card fraud. Tokenization helps to secure information transmitted on the internet, which helps in meeting the data policies. In electronic payment, data tokenization is used to secure the end-to-end process. The token number serves as a reference to the original data, and no algorithm can be used to derive the initial data. In recent times, there have been increasing use of tokens in telephone numbers, social security numbers, and email addresses.

“Tokenization uses a database that stores relationship between the sensitive value and the token.” (Guo, 2017)

The world of block-chain has witnessed a significant transformation due to the introduction of tokenization. This technological concept has replaced real money, which has replaced sensitive data with non-sensitive data. Tokenization was first introduced in 2001 by Trust Commerce as a way of securing credit card information (Donald, 2018). Before this invention, merchants stored credit data on their servers. This rendered data insecurity as anyone could access the system and vies sensitive data. Tokenization improved the cardholder security and eliminated all intercepts hackers can use in decrypting data.

Tokenization is a data security intervention that provides adequate protection and storage of sensitive information. The system used in tokenization provides data processing applications. This system offers interfaces and authorities that detokenize back to sensitive data and request tokens. The security benefit of tokenization is segmented and logically isolated from data processing systems that stored confidential data replaced by tokens. The system is useful because it requests tokens, detokenize, and redeems them back to sensitive data. In organization systems replacing live data with tokens minimizes the exposure of sensitive data to stores, processes applications, and people reducing the chances of unauthorized access.

The tokenization system does not use live data, except a few trusted applications that are permitted. A system that undergoes tokenization operates within secure and isolated data centers. The security of a token predominantly lies in the infeasibility of determining the surrogate value. Moreover, using tokenization as a security technique depends on interpretation, regulatory requirements, and assessment entities.

“The isolation tactic of the system enhance the security mechanism as well as compliance with global standards.” (Raymond, 2011)

In the digital world were cyber-attacks have become a threat as society is becoming more technological literate tokenization is a significant factor to consider. The use of token renders it more difficult for attackers to gain access to confidential data. This is possible because of the encryption factor that requires an appropriate key to be decrypted. The system also incorporates off-site data vaulting, which blocks any user trying to access sensitive information. However, tokenization cannot fully guarantee the prevention of breach. Its property of desensitizing data makes the data useless to attackers.

“The good thing about tokenization is that if breach occurs there is no data to steal.”(Donald, 2018)

Most companies in the 21st century have adopted tokenization in their payment services model. Some companies have complex payment needs that involve several gateways, for instance, making payments from multiple regions using different currencies. Tokenization has been a significant breakthrough due to its ability to simplify integration code. The amount is also secured from unauthorized services, which is a protection policy. Online payments are vulnerable to attackers, and tokenization is a significant element in ensuring financial standards.

References

Donald, P. C. (2018). Data security standard. Requirements and Security Assessment version, 3. doi:10.1107/fcomm.2018.006

Guo, J. (2017). Critical tokenization and its properties. Computational Linguistics, 23(4), 569-596. doi.10.1016/jcbspro.2017.10.026

Raymond, K., (2011). Information extraction from web services: a comparison of Tokenization algorithms. doi.10/1105/2011.05634

References