Encryption vs. Data Tokenization: Which is Better for Securing Your Data?

With the rise of cyber-attacks and data breaches, protecting sensitive data from falling into the wrong hands is crucial. There are two widely used techniques for safeguarding data, namely data encryption and data tokenization. In this article, I will explore the differences between the two and help you understand which method is best for securing your own data.

Data encryption and data tokenization are both methods of protecting sensitive data from unauthorized access. Both methods aim to keep data secure by rendering it unreadable to anyone who does not have the appropriate access. However, the two methods differ in their approach, and each has its own set of strengths and weaknesses.

What is data encryption, and how does it work?

Data encryption is the process of transforming plaintext into ciphertext using an algorithm and a key. The algorithm takes both the plaintext and the key as inputs and generates ciphertext as output. The key is used to scramble the plaintext in a way that makes it unreadable to anyone who does not have the key.

There are two types of data encryption: symmetric encryption and asymmetric encryption.

• Symmetric encryption employs a single key for both encrypting and decrypting the data. This means that anyone who possesses the key can perform both tasks. Due to this reason, symmetric encryption is typically faster than asymmetric encryption, but it is less secure.
• Asymmetric encryption uses two keys: a public key and a private key. The public key is used for encryption, and the private key is used for decryption. This implies that anyone can encrypt data using the public key, but only the individual possessing the private key can decrypt it. Asymmetric encryption is generally slower than symmetric encryption but more secure.

What is data tokenization, and how does it work?

Data tokenization is the process of replacing sensitive data with a token. The token is created using an algorithm that generates a unique string of characters. The sensitive data is then stored in a secure location, and the token is used in its place. When the data needs to be accessed, the token is used to retrieve the original data.

To better understand tokenization, think of subway tokens or casino chips. They replace physical currency and reduce cash handling risks such as theft. Unlike encryption, tokenization is a method that replaces sensitive data with non-sensitive substitutes without changing the type or length of the data. Tokenization is actually a broader concept. It is increasingly used in the crypto world, where tokens linked to underlying assets represent various digital assets on Bitcoin, Ethereum, and other blockchains.

There are different types of tokenization methods. Format-preserving tokenization (FPT) replaces sensitive data with a token that has the same format as the original data. Secure hashing algorithm (SHA) tokenization hashes the data and uses the hash value as a token, making it irreversible. Randomized tokenization generates a unique token for each data element, which is not related to the original data. Strong one-way hash tokenization uses a strong hash function to generate a token, making it more secure and resistant to attacks.

There is no universal classification for tokens, but they can be categorized in various ways. Tokens can be single or multi-use, authenticable or non-authenticable, cryptographic or non-cryptographic, and combinations of these.

Which is more secure: data encryption or data tokenization?

Both data encryption and data tokenization are methods used to secure sensitive data, but they differ in how they protect the data. Encryption is generally considered more secure than tokenization because it involves complex mathematical algorithms and secret keys that make it difficult for unauthorized parties to decrypt the ciphertext.

Tokenization has some advantages over encryption. For example, if an attacker gains access to the tokenized data, they will only see meaningless tokens that cannot be used for malicious purposes. In contrast, if an attacker gains access to encrypted data and is able to decrypt it, they will have access to the original sensitive data.

Using data tokenization securely

The tokenization system stores a database of tokens that are mappedlinked to the corresponding sensitive data. To protect this database, it is necessary to use industry best practices such as secure storage, audit trails, and secure authentication authorization protocols. To fully benefit from data tokenization’s security and risk reduction features, the tokenization system should be logically isolated from the systems and applications that store or process sensitive data.

Furthermore, the method used for generating tokens should be proven to make it impossible to reverse them back to the original data through cryptanalysis, brute-force attacks, side-channel analysis, and token mapping table exposure.

Using encryption securely

When using data encryption, it is important to choose a robust encryption algorithm that is widely accepted in the industry, like the Advanced Encryption Standard (AES). Avoid using outdated encryption algorithms or creating your own encryption methods.

To ensure secure key management, you can implement practices like key rotation and destruction. It is good to store keys in a secure location, such as a hardware security module (HSM).

Additionally, it is recommended to implement access controls that limit access to keys and encrypted data. This can include using Role-Based Access Control (RBAC) and Multi-Factor Authentication (MFA) to ensure that only the right people can access the data.

Which to choose?

The choice between data encryption and data tokenization depends on your organization’s specific needs. Please remember that data encryption and data tokenization can be used together. Here are some factors to consider when deciding which method is best for your data security needs:

Compliance

Some standards mandate using encryption; however, some specific regulations will allow tokenization. Data tokenization can be more effective for reducing compliance scope by reducing the amount of sensitive data that needs to be protected.

Compatibility

When considering encryption or tokenization, it is important to assess the compatibility of your existing software and processes and determine which method would be easier to implement based on your current digital infrastructure.

Resources used

Encrypting data is a resource-intensive process, requiring specialized hardware and software to be implemented, which can be costly. On the other hand, tokenization is a less resource-intensive process, making it less expensive to implement. Tokenization is a process that enables specific data to be visible for processing and analytics while keeping sensitive information concealed.

Data sharing

If you need to share sensitive data in its original value and format with a third party, encryption may be the best solution. This will minimize external access to your token vaultdatabase for de-tokenization processes.

Data format

Encryption can be used for both structured and unstructured data, including entire files. However, tokenization is more suitable for structured data fields only. It focuses on the future and involves tokenizing structured data fields like social security or payment card numbers.

Final thoughts

When deciding between tokenization or encryption, consider your data security needs. Tokenization is suitable for specific numbers like credit card or account numbers, while encryption can protect entire databases. Consider which option is easier to comply with your company’s data security policy. Also, take into account your budget when choosing between these two options. Finally, think about the potential benefits that tokenization or encryption could offer your company based on its size and customer base.

While the points mentioned above can guide you in choosing between tokenization and encryption, I recommend using both techniques together whenever possible. Tokenization and encryption are not mutually exclusive, and combining these methods can help overcome their respective limitations and improve your company’s overall data security posture.