Currently, as data has become increasingly important like currency, adequate security is needed and tokenization is a process to do this. In this procedure, the data is converted into a token that works as a separate identifier, preserving the integral information without any exposure. This article explores the concept of data tokenization, its comparison to encryption, its benefits and limitations.
Data tokenization: an introduction
To understand the concept of data tokenization, you need to know about tokens. A token works as a non-mineable digital unit that exists as a registry entry within a blockchain. There are different forms and usage scenarios of tokens. For example, they can be used for data encryption or as currency. Generally, tokens use blockchains such as Ethereum for their issuance. The prominent token standards take into account ERC-20, BEP-20, ERC-1155 and ERC-721.
Tokens work as transferable units of value issued by a blockchain. However, they are different from the crypto coins such as Bitcoin or Ether that are native to their blockchains. Various tokens can be exchanged to act as off-chain assets, including property and gold. These tokens fall within the category of tokenization of real-world assets.
The data tokenization procedure involves converting sensitive data into tokens. This enables the transfer, storage and processing of the data in question without making it public. Such tokens are normally exclusive and immutable. Their verification can be done on the blockchain for improved data security, compliance and privacy. Data tokenization can also be used for social media accounts. Consumers can symbolize its online presence to simultaneously switch peerlessly between social media platforms to maintain ownership of the data.
Difference between tokenization and encryption
Some people confuse tokenization with encryption, but they are different concepts despite their common goal of protecting data. Encryption refers to the procedure of scanning plain text data into a format that is unreadable and requires a secret key to decrypt it. A mathematical procedure is taken into account to encrypt the data. Some use cases of encryption include regulatory compliance, digital signatures, authentication, data storage, and secure communications.
On the other hand, tokenization involves a procedure of replacing sensitive data with unique and non-sensitive identifiers known as tokens. This process does not require a secret key for data protection. For example, a person’s personal information can be exchanged with a token that is unrelated to the original number. Tokenization is often used for regulatory compliance and data security. The known use cases of tokenization include payment processing and management of personally identifiable information.
Benefits of data tokenization
Some well-known benefits of data tokenization include improved data security, protected data sharing, and regulatory compliance.
Enhanced data security
Because data tokenization replaces sensitive data with certain tokens, it minimizes the dangers of data breach, fraud, identity theft, and so on. Tokens have a connection to the actual data based on a secure mapping system. This way, the original data remains safe, despite the tokens being leaked or stolen.
Secure data exchange
Tokenization allows users to enable secure data sharing between suppliers, departments, and so on. Since the parties receiving the tokens do not have access to the original data, this procedure can be effectively scaled to meet the increasing demands of the platforms. In this regard, tokenization saves the cost of significant data security measures.
Regulatory compliance
Several markets face strict data protection regulations. In such industries, tokenization can enable companies to meet such requirements. Moreover, the tokenization procedure can also reduce complications related to security audits. It also streamlines data management to a great extent.
Limits of data tokenization
Regardless of the above-mentioned benefits, data tokenization still has some limitations. They include data management, data interoperability, data recovery and data quality.
Data management
The process of data tokenization can raise ethical and legal questions about the ownership, control, use and sharing of the data. Tokenization of a consumer’s personal data can change the way he or she consents to data collection and use. In some cases, this could suppress users’ rights to intellectual property and freedom of expression.
Data interoperability
Data tokenization can increase the difficulty of working together for various systems that use or process the data. For example, if a user tokenizes a phone number, it could hinder their ability to receive or make text messages or calls, depending on the companies they use.
Data recovery
If a tokenization system goes down, users may face complications when exchanging data. Companies need to restore the original data and tokenized data. However, this increases the complications.
Data quality
The accuracy and quality of the data can be affected by tokenization. With this procedure there is a chance that certain information will be distorted or lost.
Conclusion
Many industries, such as social networking, media, and healthcare finance, have already adopted the concept of data tokenization. Driven by increasing regulatory compliance and data security requirements, this procedure may continue to evolve. Implementing the respective approach efficiently requires careful consideration. Data tokenization must be carried out responsibly and clearly, respecting consumers’ expectations and rights while adhering to relevant regulations and laws.
