Learn why data encryption alone isn’t enough and how tokenization enhances protection against modern data breaches.
In today's digital environment, data protection is paramount due to the ever-growing threats of cybercrime, unauthorized access, and data breaches.
Data encryption is a crucial security measure that converts readable data into an unreadable, secure format, making it unintelligible to unauthorized users and safeguarding sensitive information both in transit and at rest.
It is one among several options, with the other being data tokenization, which replaces the sensitive data wth non-sensitive substitutes called tokens.
Data encryption is the process of converting readable information (plaintext) into an unreadable format (ciphertext) using mathematical algorithms and cryptographic keys. Only those with the correct key can reverse this process – or decrypt – and restore the original data.f
According to Google Cloud, encryption “protects data from being stolen, changed, or compromised” whether it’s stored (at rest) or sent over networks (in transit). IBM and Kaspersky similarly describe it as a core safeguard for ensuring confidentiality, integrity, authentication, and non-repudiation, i.e., the four pillars of secure communication.
In modern environments, encryption isn’t limited to files or databases. It’s foundational to securing APIs, SaaS applications, and multi-cloud systems.
Combined with technologies like tokenization and network-layer monitoring, data encryption becomes part of a continuous data-centric defense model.
The purpose of encryption is simple: even if attackers steal your data, they can’t read or use it.
From accidental exposure to credential theft, encrypted security ensures that sensitive information (from personal identifiers to payment details) remains safe from unauthorized use, even when stored in vulnerable systems or transmitted across open networks.
Encryption is also a regulatory requirement, with the Payment Card Industry Data Security Standard (PCI DSS), Health Insurance Portability and Accountability Act (HIPAA), and General Data Protection Regulation (GDPR), all mandating or strongly recommending encryption for protecting sensitive or regulated data.
However, encryption alone is not enough. It protects the content of data but not its context — meaning an attacker can still steal encrypted files or keys.
Some data security platforms close this gap with network-layer enforcement, thereby ensuring encryption policies are validated in-line and that data flows cannot be manipulated, exfiltrated, or mirrored by unauthorized systems.
Data encryption works by applying cryptographic algorithms to convert readable data, known as plaintext, into an encoded format called ciphertext, which cannot be understood without the corresponding decryption key.
Encryption algorithms typically fall into two categories: symmetric encryption, which utilizes a single private key for both encryption and decryption, and asymmetric encryption, which relies on a pair of keys – a public key and a private key, one used for encryption and the other for decryption.
During encryption, algorithms transform the plaintext by systematically scrambling data into a complex format. For example, symmetric algorithms like AES (Advanced Encryption Standard) use a private key to secure data swiftly and efficiently, while an asymmetric one like RSA is used for encrypting symmetric keys.
When encrypted data reaches the intended recipient or an authorized system, it undergoes decryption – a process that reverses the cryptographic operation.
The recipient applies the corresponding private key to the ciphertext, systematically unscrambling it back into its original plaintext form. Because keys are essential for both encrypting and decrypting data, proper key management – i.e., secure generation, storage, distribution, and disposal – is critical.
Strong encryption ensures that data intercepted or accessed by unauthorized entities remains indecipherable, significantly reducing the risk of data breaches and ensuring compliance with security regulations.
Symmetric encryption, also known as private-key encryption, uses a single cryptographic key for both encryption and decryption processes. This approach ensures rapid and efficient handling of data, making it ideal for securing large volumes of information or streaming data.
The most common symmetric encryption algorithm is the Advanced Encryption Standard (AES), recognized globally for its speed, simplicity, and strong security.
While symmetric encryption provides excellent performance, the challenge lies in securely managing and exchanging the private key, as anyone possessing this key can access the encrypted data.
Asymmetric encryption, commonly called public-key encryption, employs two mathematically related keys: a public key for encryption and a private key for decryption (or vice versa).
This method ensures secure communication, as the data encrypted with one key can only be decrypted by the other corresponding key.
RSA (Rivest-Shamir-Adleman) is a prominent asymmetric encryption algorithm, widely used for secure data transmission, digital signatures, and key exchanges.
Although asymmetric encryption provides robust security and solves the issue of secure key distribution inherent in symmetric encryption, it demands significantly higher computational resources, making it less suited for encrypting large datasets. Therefore, asymmetric encryption is deployed for very different use cases than symmetric encryption.
The key distinction between symmetric and asymmetric encryption lies in how cryptographic keys are used.
Most real-world encryption systems use both symmetric and asymmetric encryption. For example, RSA or ECC may be used to exchange an AES key, which then encrypts the actual data. This hybrid approach strikes a balance between security and performance, serving as the foundation of HTTPS, VPNs, and modern zero-trust architectures.
AES is the most widely adopted symmetric encryption algorithm globally, known for its strong security, efficiency, and speed.
AES operates using a block cipher that encrypts data in fixed-size blocks of 128 bits, employing keys of varying lengths – i.e., 128, 192, or 256 bits – with AES-256 providing the highest level of security.
Due to its robust security and excellent performance, AES is used by organizations worldwide, including governments and financial institutions, to safeguard sensitive data
Twofish is a symmetric encryption algorithm that, like AES, encrypts data in fixed-size blocks of 128 bits, supporting keys up to 256 bits in length.
Developed as an alternative to earlier encryption standards, Twofish is renowned for its flexibility, speed, and security, having been a finalist in the competition to become the AES standard.
Although not as universally adopted as AES, Twofish remains an attractive encryption option due to its open-source availability and effectiveness, especially in software environments that demand both strong security and high-speed data processing.
RSA is one of the most prominent asymmetric encryption algorithms, widely used to encrypt symmetric keys. Its main use cases include secure key exchange, digital signatures, SSL/TLS certifications, and small data encryption.
It relies on the mathematical complexity of factoring large prime numbers to generate its public-key and private-key pairs. RSA's security strength typically increases with key size, with common key lengths ranging from 1024 to 4096 bits.
Due to its computational intensity, RSA is predominantly employed for encrypting small amounts of data, establishing secure communication channels, and authenticating digital identities rather than for bulk data encryption.
ECC is an advanced asymmetric encryption technique that uses mathematical operations on elliptic curves to generate cryptographic keys. Its typical use cases are secure key exchange, digital signatures, HTTPS/TLS, and mobile and internet-of-things (IoT) security.
ECC provides equivalent or stronger security than traditional asymmetric methods, like RSA, but with significantly shorter key lengths, hence requiring less computing power and enabling more efficient encryption.
This makes ECC particularly suitable for resource-constrained environments, such as mobile devices or IoT applications. Due to its superior efficiency, ECC is increasingly becoming used for securing sensitive data transmission, digital signatures, and authentication processes.
Blowfish is a symmetric block cipher designed as a fast, free alternative to DES. It uses a variable key length (up to 448 bits) and operates on 64-bit blocks of data.
Although considered secure and efficient, Blowfish has largely been succeeded by newer algorithms like AES and Twofish due to its smaller block size and slower key setup time.
Still, it remains popular in legacy applications and embedded systems where licensing-free, lightweight encryption is required.
Triple DES (3DES) is an enhancement of the original Data Encryption Standard (DES), applying the DES algorithm three times to each data block for improved security.
Despite its historical significance, 3DES is now considered deprecated due to its limited 56-bit key strength and vulnerability to brute force attacks. Regulatory frameworks such as PCI DSS have begun phasing out 3DES in favor of AES, which offers higher performance and security.
RC4 is a stream cipher that was once widely used in SSL/TLS protocols and wireless encryption (e.g., WEP). It is fast and straightforward to implement, but has since been proven vulnerable to multiple attacks due to biases in its key scheduling algorithm.
As a result, RC4 is no longer considered secure for modern applications and has been replaced by stronger methods such as AES in GCM mode.
DES, introduced in the 1970s, was one of the first widely adopted encryption algorithms. It uses a 56-bit key and encrypts data in 64-bit blocks.
While DES laid the groundwork for modern cryptography, advancements in computing have rendered it vulnerable to brute force attacks. Its primary contribution today lies in its historical influence and as a foundation for successor algorithms, such as 3DES and AES.
IDEA is a symmetric block cipher developed as a replacement for DES. It utilizes 128-bit keys and operates on 64-bit blocks, offering robust resistance against cryptanalysis.
Though robust, IDEA’s adoption has declined due to patent restrictions and the emergence of AES. However, it remains an academically significant encryption method and is still found in some legacy applications.
ChaCha20 is a modern stream cipher designed for performance and security in software implementations, particularly on mobile and embedded devices.
It offers protection against timing attacks and has replaced RC4 in protocols like TLS 1.3.
When combined with the Poly1305 authenticator (as in ChaCha20-Poly1305), it provides both encryption and message authentication, making it a trusted choice for securing data across today’s web and mobile applications.
With quantum computing on the horizon, traditional algorithms such as RSA and ECC may eventually be compromised.
Quantum-resistant (post-quantum) encryption schemes, such as lattice-based or hash-based cryptography, are designed to withstand attacks from quantum computers.
These methods are becoming a strategic focus area for organizations preparing for “harvest now, decrypt later” threats and aligning with emerging standards from NIST’s Post-Quantum Cryptography project.
While data encryption offers robust security benefits, it also has limitations that may necessitate the use of additional solutions, such as data tokenization.
Encryption offers end-to-end protection of sensitive information by converting it into unreadable code, ensuring that only authorized individuals can access it.
Data encryption maintains confidentiality, integrity, and authenticity, preventing unauthorized modification or misuse of data. Even if data is intercepted during transmission or extracted from compromised systems, it remains unintelligible without the decryption key.
Encryption is particularly vital for data at rest (stored files, databases, backups) and data in transit (network communications, API calls, email).
When properly implemented, it can render breached data effectively useless, turning potential data breaches into mere exposure of indecipherable ciphertext.
Encryption not only keeps data private but also reinforces its integrity. Any unauthorized alteration to an encrypted file typically causes decryption to fail or produce invalid results, alerting administrators to tampering.
In high-trust environments such as financial systems and healthcare, maintaining data integrity is crucial for compliance with PCI DSS and HIPAA, both of which require controls to ensure that sensitive information is not modified without authorization.
Encryption applies across nearly all digital domains – from files, databases, and backups to SaaS applications and APIs. It’s adaptable to both on-premises and cloud environments, providing consistent protection regardless of where data resides or how it moves.
Techniques such as AES-256 encryption and ECC enable the secure storage of massive datasets and high-speed communications while maintaining optimal performance.
This versatility is why encryption underpins everything from secure web browsing (HTTPS) to VPN tunnels and database encryption.
However, while encryption secures the content of data, it doesn’t inherently secure its context.
This limitation introduces the need for inline protection, which is where DataStealth extends encryption’s power by monitoring, validating, and securing data as it flows between systems.
Encryption adds a computational burden because every encryption and decryption operation consumes processing power. Symmetric algorithms, such as AES, are highly efficient, but asymmetric systems, like RSA and ECC, require more resources.
In high-transaction environments, this performance impact can accumulate, leading organizations to rely on hardware acceleration (e.g., HSMs) or distributed encryption management to maintain system responsiveness.
DataStealth mitigates this overhead with an inline architecture that intercepts, classifies, and secures data without forcing application rewrites or performance penalties.
Key management remains one of the most challenging aspects of encrypted security. Losing or mishandling cryptographic keys means losing access to the encrypted data itself.
At scale, this challenge becomes even more significant: organizations must generate, rotate, store, and destroy thousands, sometimes millions, of keys across hybrid environments.
Key misuse, insider errors, and failure to enforce proper storage controls (such as in HSMs or dedicated KMS systems) all heighten the risk.
This is why DataStealth integrates network-layer tokenization — replacing sensitive values with non-sensitive tokens — which dramatically reduces the number of keys that must be managed while keeping sensitive data entirely out of scope.
Encryption protects what data says, but not where it goes. Once an attacker gains access to an encrypted file or system, they can exfiltrate ciphertext wholesale, waiting for an opportunity to decrypt it later – a practice known as “harvest now, decrypt later.”
Encryption also cannot prevent credential misuse or API abuse, where an attacker uses valid authentication tokens to request encrypted data legitimately.
DataStealth’s inline architecture addresses this gap by enforcing encryption validation at the network layer. It inspects and validates encrypted data traffic in real-time, blocking suspicious requests or unapproved destinations before the data ever leaves the organization’s perimeter.
Modern cloud systems expose encryption APIs that attackers can exploit.
By hijacking these APIs, threat actors can re-encrypt victim data with their own keys, effectively locking the organization out. This form of “encryption takeover” mimics ransomware but operates through legitimate cloud controls.
Attackers can steal encrypted data by exploiting poorly secured APIs or using legitimate cloud storage transfer services, as shown in the 2024 Snowflake breach, where hackers accessed customer accounts using stolen credentials.
Encryption is ineffective if sensitive data isn’t properly classified and encrypted; misconfigured databases, cloud buckets, or SaaS exports can expose plaintext data.
Without automated discovery, organizations often underestimate the volume of dark data – i.e., untagged, unencrypted information hidden in backups, logs, or third-party systems.
DataStealth mitigates this by discovering, classifying, and automatically applying encryption or tokenization policies in-line, ensuring no sensitive data leaves unprotected.
If malware compromises an endpoint before encryption occurs – or gains access to decrypted data in memory – encryption provides no defence. Ransomware, keyloggers, and infostealers operate at this layer.
This is why multi-layered security is crucial: endpoint protection must complement encryption to ensure decrypted data in use remains secure.
DataStealth strengthens this by ensuring sensitive data remains encrypted or tokenized even as it travels between applications, reducing exposure at the device level.
Brute force attacks attempt to guess encryption keys through repeated trials. While modern standards, such as AES-256 and ECC, are effectively immune to brute force attacks due to their vast key spaces, older methods like DES or 3DES are vulnerable to brute force attacks.
Organizations still relying on outdated algorithms face unnecessary exposure and potential non-compliance with current data encryption standards.
Cryptanalysis is the mathematical study of breaking cryptographic systems. It targets flaws in algorithms or their implementation.
Though rare in modern encryption standards, poor configurations or outdated ciphers can expose organizations to attacks that bypass brute force entirely.
Side-channel attacks exploit physical or environmental signals (like timing, power consumption, or electromagnetic leaks) to infer encryption keys.
These attacks highlight that encryption’s strength is not purely mathematical; implementation matters. Using hardware-based cryptography modules (HSMs) and ensuring proper isolation are critical to defence.
Standards like PCI DSS, for example, place systems “performing encryption and/or decryption of cardholder data, and systems performing key management functions” under scope.
So, in addition to the risk that encrypted data can be stolen, organizations often have to manage compliance requirements (despite securing their data).
In effect, securing what surrounds your data (like encryption) is no longer enough; organizations must now think about protecting their data in and of itself.
Encryption is not just a tool; it’s an architectural principle.
To truly protect sensitive information, organizations must consider where their data lives, how it moves, and what touches it along the way.
Encrypting files or databases in isolation no longer guarantees security when sensitive data constantly flows through APIs, SaaS platforms, and third-party integrations.
Modern protection demands an understanding of the entire data lifecycle — from creation and transmission to storage and deletion.
This is where the concept of inline data security becomes essential.
Rather than treating encryption as a downstream control, organizations should enforce it within the fabric of their architecture, i.e., validating encryption policies, classifying data in real time, and protecting information as it moves between systems.
Encryption is no longer a static control; it’s part of a dynamic, multilayer data security platform that must operate in-line with how data actually moves through your organization.
Protecting data requires seeing beyond files and databases — it demands visibility into data flows, validation at the network layer, and integration with tokenization and discovery systems.
By aligning encryption with the wider architecture — not just where data rests, but how it travels — organizations can evolve from passive protection to proactive data resilience
Bilal is the Content Strategist at DataStealth. He's a recognized defence and security analyst who's researching the growing importance of cybersecurity and data protection in enterprise-sized organizations.
