Encryption is one of the most effective ways to protect data, alongside other strategies like access control, regular software updates, and private networking etc. However, adding encryption into an existing tech stack can be challenging. Data pipelines today aren’t typically designed to handle encryption, which can add operational complexity, additional migration work, and increased data pipeline compute costs.
Data encryption presents its own challenges in modern times. While at-rest and in-transit encryption are common, they often fall short of preventing data breaches within the data store itself. Unlike typical encryption in TLS, where AES and RSA are effective for securing data during transmission, applying these methods to long-term data storage introduces unique challenges.
Currently, there is no well established strategy for maintaining long-lived encryption keys. Managing keys and performing key rotations can be error-prone and costly in many data pipelines today. The high computational cost of processing encrypted data further complicates maintaining secure encryption over time. This shows the importance to have a more data-specific security strategies that go beyond encryption in-transit or at-rest, ensuring robust protection throughout the entire data lifecycle.
Today’s data pipelines are often not designed with the flexibility to handle encryption and decryption processes. For example, a pipeline designed to compute feature values from event data may need to be re-engineered to include encryption and decryption layers, adding cost and complexity to the implementation. Adding data encryption can also require updates to APIs, databases, and storage systems to support encrypted data formats. This involves updating the codebase, rewriting queries to handle encrypted fields, and ensuring that encryption keys are properly managed and accessible to services and compute environments.
Encrypting and decrypting data in real-time data pipeline introduces higher latency. In high-throughput use cases, as large volumes of data are processed, the extra time needed to encrypt or decrypt each piece can slow down data processing. Encryption and decryption involve mathematical operations that require additional computational resources. When handling large datasets, this can be both costly and time-consuming, making it prohibitive for organizations to adopt encryption, even if it's a better data security practice.
Currently, there’s no unified key management system specifically for data encryption. Common use cases like TLS are designed for short-lived keys, and long-lived key management lacks standardized solutions. Like any security component, visibility into key lifecycle and usage is important -— understanding when and how a key was created, when and where it has been accessed, and how long it’s been in use before being rotated. Without the visibility, maintaining secure and effective data encryption practices can be challenging and error-prone. The complexity increases when different teams within a company, or across partner organizations, need to securely share or manage keys. Challenges in key management practices can further lead to security breaches, misconfigurations, and unauthorized access.
Adding encryption to an existing tech stack can lead to additional development work. The encryption and decryption processes require more computational resources, which can lead to higher operational and cloud infrastructure costs. However, the financial impact of a breach can be enormous, including fines for non-compliance with regulations, legal fees, and the costs associated with incident response and remediation. Like many security practices, the cost of data encryption must be balanced against the potential costs of a data breach—fines for non-compliance with regulations, legal fees, incident response and remediation expenses, and the reputational damage to the brand.
Existing data security practices are increasingly insufficient to defend the increasing frequency and scale of data breaches. As the technology involve, data and software engineers will also need to catch up on the corresponding skills and knowledge to implement data security effectively. This requires a commitment to continuous learning and adaptation by the companies and organizations.
Technology is ever-evolving, and so too is software implementation. However, a complete rewrite is not only costly but can also be detrimental to businesses. Instead, a less risky but more common approach is to identify high-impact, low-interruption service areas to roll out the change by phases. By starting small, organizations can try out new technologies and processes, minimizing risks and disruptions to the business while gradually increase the coverage.
Field-level encryption aims at specific sensitive information within a data object. Whole message or full file encryption, by contrast, encrypts entire data objects in one shot, making the entire content inaccessible without the proper decryption key. For real-time or data processing pipelines, field-level encryption allows the system to continue operating, enabling engineering teams to update dependencies or downstream steps in a much longer time frame. In complex systems, a hard, full cutover can be challenging and risky. Field-level encryption lowers the adoption barrier by avoiding the need for an immediate, full migration, allowing for a more manageable and phased approach.
Field-level encryption also opens the door for additional privacy-preserving techniques like data masking, redaction, and deterministic encryption, which can be tailored to meet the specific security needs of your organization.
While field-level encryption works well in real-time systems, whole file encryption is especially useful for remediating security vulnerabilities. Encrypting entire files containing sensitive information can help security teams act quickly without needing to consult legal or engineering teams about whether data can be deleted. By encrypting the data, we can protect sensitive information from unauthorized access while ensuring it remains accessible when needed.
Whether you are a security team focused on data security vulnerability remediation or a data engineering team implementing field-level encryption, Keyper can help greatly reduce the complexity of implementing data security best practices. Keyper wraps access control, data encryption key management, and data encryption and decryption into three simple commands, so you can focus on your work while Keyper ensures that data encryption meets the highest security standards.
While data encryption is effective for protecting sensitive information, it can be costly to implement. Taking a phased approach, starting with high-impact areas like field-level and whole file encryption, makes adoption more manageable and practical. As technology and security threats evolve, adopting new security strategies is critical to your organization. With the right migration strategy, you can keep your tech stack up to date without excessive risks of disrupting your day-to-day business operations.