PETs and the architecture issue
In a constant attempt to maintain data compliance and meet multiple sets of international data regulation measures, keeping updated on the rapidly evolving technology landscape, many organisations have resorted to quickly finding external solutions.
One such solution is in consistently incorporating numerous Privacy Enhancing Technologies (PETs) into their current architecture. Initially, this may seem an ideal solution, with numerous technologies ensuring larger coverage and security.
However, with more and more technologies and techniques, greater complexity is introduced to current architecture, as challenges such as a lack of quantifiable security become more difficult to navigate.
This approach may cause serious consequences to your business’s operations, damaging your data strategy rather than enabling it.
What are PETs?
PETs are a wide range of technologies through both hardware and software, that allow organisations to make use of all their existing data to enable data-driven strategic decisions.
PETs achieve this by applying data protection principles to an organisation’s data architecture, without impeding access. This can be done through a variety of techniques. Two of these are:
1. Homomorphic encryption
Homomorphic encryption is an incredibly popular PET, due to its ability to allow data to be consistently secure, even when it’s in use by teams or an individual.
To achieve this, it uses a public key to encrypt datasets. Differing from other PETs, homomorphic encryption incorporates an algebraic system to allow functions to be performed on the data while it’s still encrypted for maximum security and confidence.
To access the original, unencrypted data after this process, a user must provide a matching key. Currently, there are three variations of homomorphic encryption – partial, somewhat, and full – providing increasing levels of security.
2. Differential Privacy
Differential Privacy allows organisations to access sensitive data to increase the efficacy of their strategy and operations, without breaching compliance with data privacy regulations.
It achieves this by utilising complex mathematical equations to withhold certain information and introduce a vague amount of uncertainty through adding ‘random noise’ to the aggregate data. This ensures that even if a user held complete information for nine out of ten users, they could still not gain complete information of the tenth.
To achieve this effect, random noise is incorporated into datasets, which are then retrieved by various queries.
The common challenges of PETs
In search of a solution that ensures compliance and protects them against the risk of facing heavy fines of as much as £1.6bn, as well as protecting against malevolent actors, these PETs often promise the latest technology, sophisticated processes, and optimised security.
However, there are key considerations that businesses must take into account if they wish to implement PETs that threaten the overall data strategy:
- Lack of accessibility
One of the most common challenges and criticisms of adopting PETs is that they’re highly specialised and require significant technical expertise and experience in cryptology.
This lack of accessibility makes them often ineffectual unless organisations possess the necessary specialists.
- Restricted due to large process times
In a world where markets are increasingly competitive and consumer behaviour shifts in seconds, it’s important to ensure that your insights are available at a glance and consistently up to date.
The incorporation of PETs makes this difficult as they are often incredibly time-consuming. It’s not unusual to hear of a thousand records taking ten minutes to process – which makes insights based on vast datasets highly difficult.
- Lack of cost-effective approaches.
Privacy Enhancing Technologies are often highly expensive and require advanced computational capacity. This means that they are often unavailable to many organisations that don’t possess highly advanced functionality or necessary funding – potentially leaving their data vulnerable and threatening compliance in the process.
- Difficult to measure effectiveness.
Often, PETs lack common definitions and standards. This means that it’s difficult to evaluate overall efficacy. This can be seen in Differential Privacy – where the introduction of ambiguity through random noise may skew perceptions and results. With this difficulty, many question the efficacy of these techniques when considering high-profile strategic decisions, lacking confidence in their data.
An innovative approach to consolidating PETs
Recognising that there must be a smarter, more intuitive way to interact with multiple PETs within an architecture, eXate’s universal data privacy platform is designed to integrate and orchestrate all your current PETs into one simple dashboard, removing unnecessary complexity in the process while ensuring international compliance with data protection laws and regulations.
The DataSecOps platform resolves many common issues of navigating multiple PETs within your architecture, with an emphasis on accessibility throughout.
We believe that true data privacy should be achievable to all, not just those that possess vast experience, training, and qualifications. That’s why our platform is designed for ease of use, so that all designated members of the team, regardless of certification, can effortlessly interact with, and govern their datasets.
Book a free demonstration
Organisations will find that, without a unified approach to navigating their wealth of PETs, their architecture and data strategy will suffer from unnecessary complexity and computational demands. The DataSecOps platform removes this challenge, empowering data and streamlining intense processes.
In the meantime, if you have any queries or questions about the importance of Data Privacy, you can contact us here.