How Data Tokenization Can Help Minimize Data Breach in Web 3.0

Introduction: Understanding Data Tokenization in Web 3.0

Web 3.0 has revolutionized the internet and ushered in a new wave of decentralized technologies and applications. Underpinning Web 3.0 are decentralization, advanced technologies, privacy, and user-centric networks, which enable increased user control, transparency, and autonomy.

The aim of Web 3.0 is to distribute the economic benefits of the Internet to participants. The first generation of the web, also called Web 1.0, limited users to consuming the static information uploaded by site admins. Users had minimal control during the Web 1.0 era, offering them little ownership of their data.

The advent of Web 2.0 brought a revolution that unlocked user-generated content. As opposed to Web 1.0, which is usually termed the “read-only web,” Web 2.0 is a “read-write web.” In Web 2.0, billions of people began interacting with the internet and entrusted websites with their content, personal information, financial information, and highly sensitive data. This allowed big tech companies to amass significant centralized data, thereby controlling wealth and users’ information. This internet era was also confronted with huge data thefts, privacy risks, and fraud.

Source: Medium.com/@UBET Sports — Differences between Web 1.0, Web 2.0, and Web 3.0

Web 3.0, popularly known as the “read-write-interact web,” marked an unprecedented turning point because it gives participants power over their data via its underlying blockchain technology. It counteracts the risks of monopolization caused by centralized big names because decentralized databases and ledgers are distributed over nodes that are available to anyone. Since information is distributed over several nodes, the risks of theft, monopolization, and fraud are significantly decreased. In addition, blockchain allows any activity to be uniquely represented via tokenization, increasing users’ confidence in their data.

Source: Dock.io

Essentially, data tokenization is one of the methods Web 3.0 uses to solve data security problems on the modern internet. Malicious actors are never relenting; thus, finding a way to keep users’ information secure can be tricky. Through tokenization, blockchain systems can minimize data breaches and protect the countless amounts of sensitive data transacted on the internet daily. However, despite the ability of data tokenization to solve data security problems, it comes with some challenges. Therefore, it is important to understand how it works and how effectively it can minimize data breaches.

Data Security Risks in Web 3.0

Like any other technology, Web 3.0 has its share of security concerns. Some of these gaps come from the dependence and interactions between some Web 3.0 systems and Web 2.0. Others are caused by inherent flaws in blockchain protocols and the delays in implementing fixes due to the reliance on network consensus for updates.

Below are a few security risks associated with Web 3.0.

Data Manipulation

This is a significant problem in Web 3.0, and blockchain systems are susceptible to it. Although blockchain transactions are immutable and encrypted, malicious actors can alter data at the beginning and end of a transaction. The data manipulation risks in Web 3.0 include the following:

• Intercepting or eavesdropping on unencrypted data transmitted across a network
• If hackers have access to users’ passphrases, they can clone a wallet and take over its content
• Injection of harmful scripts into the programming language used in executing application commands in Web 3.0 systems
• Unauthorized access to data, enabling scammers to impersonate end-user nodes
• Altering transaction data or forging the user’s digital signature

Data Authenticity Problems

Because greater control is with end-user nodes, data availability challenges can arise if the nodes are breached. Although decentralization makes censorship difficult on Web 3.0 systems, there is a question of data quality and accuracy. It is unclear how zero trust, gatekeeping, and blockchain interaction with AI models can affect the quality and availability of data stored on blockchain systems.

Reduced Centralized Oversight

A benefit of Web 2.0 is the ability of centralized authorities to safeguard the security of data stored on their systems. The corporations are in charge of maintaining the integrity of data gathered and they commit significant human and technological resources in achieving that. However, the data stored on Web 3.0 is not managed by an entity and the whole network participants are responsible for maintaining the quality of the data. This may lead to data security challenges, especially on unpopular networks that need to implement strong security measures.

What is Data Tokenization and How Does it Work?

Source: Mineraltree

Data tokenization is an advanced form of pseudonymization that protects users’ data while maintaining its original meaning. It turns sensitive data into a randomized token that can be sent over blockchain systems without revealing details about the original data.

Tokenized data is always randomized rather than a coded version of the original data. By this, when someone gains access to the token, they cannot decode or convert it back to the original data.

Despite having no connection to the original data, tokenized data can function exactly the same way. They can replicate all the functions of the original data, thereby securing the data from any form of attack.

Source: Piiano

Although the precise details of the tokenization process can change with the network used and the type of data involved, tokenization typically follows the following steps:

Step 1: The user provides data to a token provider.

Step 2: The token provider confirms the data and attaches a token to it.

Step 3: The token provider gives the user the token in exchange for the original data.

Step 4: If the user needs to distribute the data to a third party, they give the tokenized data instead of the original data.

Step 5: The third party works on the data, contact the token provider about the specific token they have received.

Step 6: The token provider confirms the validity of the underlying data.

Step 7: The third party then validates their transaction with the user.

Benefits of Data Tokenization

Source: Piiano

Data tokenization has been extensively used for purposes like transmission of healthcare data, confirming transactions, finalizing credit card payments, and others. As blockchain systems become more popular, data tokenization is getting more attention for their multiple benefits.

Improved Security

Data stored on a Web 3.0 network may exist as a token, enhancing the community’s security. If a data breach happens to the system, the hacker cannot easily access sensitive data like private keys and wallet passkeys; they will only see undecipherable tokens. This protects the system adequately and decreases the risk of data theft. Data tokenization is so important that several regulatory mechanisms like GLBA and PCI DSS now require it as a standard for compliance with regulations.

Simplicity

Data tokenization simplifies numerous processes and reduces the number of security measures needed to be implemented on Web 3.0 networks. This makes it simpler to develop decentralized applications and blockchain protocols.

For users, tokenization makes handling and interacting with their information easy. It also allows users to interact with multiple digital platforms without individually inputting their details into each.

Efficiency

Data tokenization allows for faster transactions and settlements through the automation of processes. It also reduces the need for paperwork and other manual processes, leading to simplified processes with efficient finality. This has helped speed up cross-border transactions and removed geographical barriers to asset movement.

Enhanced Traceability and Transparency

By tokenizing the information on the blockchain, altering or manipulating records becomes almost impossible. This improves data transparency, visibility, and traceability, resulting in much more secure and reliable systems.

Reduced Costs

Data tokenization can hugely decrease the cost of data breaches to individuals and businesses. The financial toll caused by data breaches is alarming, and data tokenization can be an effective strategy to curtail this. IBM’s 2023 Cost of Data Breach Report revealed that the healthcare industry had the highest data breach in 2023, while the United States had the most expensive data breach cost globally.

Source: IBM’s 2023 Cost of Data Breach Report — The United States had the most expensive data breach cost in 2023

Source: IBM’s 2023 Cost of Data Breach Report — The healthcare industry had the highest data breach in 2023

Challenges of Data Tokenization

Despite the numerous benefits of data tokenization, there are potential issues that people may face while using tokenized data.

Interoperability Issues

Data tokenization may decrease the usefulness of the data on certain systems. There are numerous blockchains, exchange platforms, and DeFi ecosystems available, and not all of them handle data in the same way. If a user tokenized data in a particular ecosystem, they may not be able to use the data when they are interacting with another ecosystem.

Regulatory Concerns

Regulatory uncertainty is another barrier to data tokenization in Web 3.0. Because of the multiple ways in which data can be tokenized, there is no common standard that guides tokenization. In addition, different national and regional regulatory approaches to blockchain systems, cryptocurrencies, and ICOs create confusion and may restrict the application of data tokenization.

Limited Awareness and Knowledge

The lack of adequate knowledge and awareness about blockchain and tokenization may also challenge its widespread use and adoption. Due to the relative novelty of Web 3.0, some individuals lack understanding and confidence in the technology. There is a need for awareness campaigns on data tokenization to increase the adoption of the concept.

Data Tokenization: Real-World Use Cases

Owing to its importance in data security, data tokenization already has a stronghold in the financial industry like DeFi. This is not limited to the finance sector as many other sectors have started using data tokenization measures. The real-world use cases of data tokenization include the following:

Gaming

Gaming in Web 3.0 has ushered in the innovative play-to-earn concept that allows players to earn in-game assets which can be converted to crypto or NFTs. However, many games have limited capability of sending in-game assets to real-world accounts. Data tokenization can potentially make this process convenient by allowing gamers to tokenize their in-game assets and connect their game accounts to crypto wallets.

NFTs

Data tokenization adds another layer of security to NFTs. Because NFTs are valuable assets, they are often the targets of malicious attacks, birthing the need to secure them optimally. If a bad actor gets access to a user’s wallet keys or NFT IDs, they can launch a highly targeted attack. By tokenizing NFT IDs, users can confirm their NFT ownership without sharing risky information. This secures the user and increases their confidence in owning NFTs.

Social Media

Data tokenization can also be used in social media platforms built on blockchain networks. Tokenization can provide a way of creating a digital identity and interacting with others while maintaining user anonymity. Without revealing any identifying clues, users can design a token that links to their real identity anonymously.

What is De-Tokenization?

De-tokenization is the reverse process of exchanging the token for the original data. While de-tokenization is possible, it cannot be achieved by just anybody. The original tokenization system or token provider is the only actor able to confirm the content of a token or view the original data attached to the token. Aside from this method, there is no way to make sense of tokenized data.

There are certain instances where de-tokenization may be needed. This occurs when authorized individuals require access to the original data for specific purposes such as transaction settlement, auditing, etc. The token provider uses the token map stored in a token vault for the exchange to achieve this. Notably, platforms use the Principle of Least Privilege to allow access to de-tokenization services to actualize data security.

Tokenization Vs. Encryption

Source: Skyflow

Although tokenization and encryption seem similar, there is a significant difference between them. Unlike encrypted data, tokenized data is irreversible or undecipherable. There is no mathematical connection between tokenized data and the original data, the tokens cannot be reversed to their original forms without the presence of the tokenizing infrastructure. In essence, a compromization of the tokenized data cannot breach the original data.

Encryption, on the other hand, is another data security mechanism that converts data into a string of random letters, numbers, and symbols. Encryption is reversible, and anyone with the encryption key can decrypt the data. Therefore, the strength of encryption depends on the strength and secrecy of the encryption key.

Some platforms combine encryption and tokenization for maximum security of their data. Comparing the two, tokenization seems to be safer for keeping data. However, the best one will depend on the data type stored. For large amounts of data, encryption tends to be the best choice. However, tokenization has proven to be the best method of keeping digital assets safe.

Conclusion

Data tokenization has been used in many Web 3.0 projects to safeguard user and sensitive data. It increases the difficulty bad actors face when attempting to steal information. Tokenized data cannot be reversed or reverted to their original form, rendering them useless if attackers obtain them. Although data tokenization may not totally protect an individual or business from data breaches, it offers a secure alternative that can significantly decrease the financial fallout from any potential breach.