13. April 2023
We live in a data-driven society. Everywhere we look, data is being generated, harvested, sorted, and stored. And no wonder. Data helps businesses better understand their customers and improve their products and services. Measure and track performance. Gain insights into market trends, customer behaviors, and new business opportunities. Drive innovation through AI and machine learning technologies. Or simply comply with legal and regulatory requirements. The fact is, data collection represents an essential driver of modern business operations.
At the same time, there are just as many reasons why businesses need to anonymize the data they use. Anonymization protects the privacy of individuals by removing personally identifiable information (PII), such as name, address, social security number, etc. It also ensures that companies comply with ever-stricter data laws, such as the GDPR, and allows them to share data with third parties, or using data for analytics and insights, without infringing the privacy of data subjects involved.
How to choose the right anonymization provider
So if your business records, collects, or uses data, the first question you need to ask is: “Do I need to anonymize that data?” And if the answer is yes, the next question goes something like this: “How do I choose the right anonymization provider?” So, let’s take a look at the five key factors you might want to consider when choosing the right anonymization provider from a tech perspective.
Factor #1: Accuracy
Accuracy is measured against two key metrics. Precision evaluates how correct a prediction is. For example, if a model detects 10 faces in the frame, how many of those 10 are actual faces, and how many are false positives? Recall assesses how effectively the model can detect PIIs. For example, if a frame contains five license plates, how many of those five did the model find? The anonymization providers you’re looking at should be able to provide these figures.
Factor #2: Data quality after redaction
It is essential to retain the visual quality of the data, especially if you’re aiming to use it for analytics and ML model training. For example, traditional blurring can lose key features of PII, such as the direction of a gaze or the origin of a license plate. This reduced quality has a knock-on effect on the analytics. For example, ML models trained on blurred data are likely to detect blurred faces or license plates instead of real ones. In cases where PII traits are not important, traditional blurring may still represent the best choice.
Factor #3: Scalability
Scalability is yet another important factor to consider when selecting an anonymization partner. As technology advances, it is becoming faster and easier to collect ever greater volumes of data – so your provider needs to be able to keep up. Anonymization allows you to store your data for long periods of time. And since anonymized data is not classed as personal data, it offers a valuable resource you can put to work whenever you want and for whatever purposes you need in the future.
A short note on infrastructure: When evaluating a solution, bear in mind that anonymization may increase the size of your data files, which may in turn lead to additional storage costs.
Factor #4: Usability
It goes without saying that you also need to consider who will be managing the anonymization software and what skills are required. Anonymization is there to solve a problem, not create new ones by being complex to use or taking up too much time and effort (and headaches). Software should be easy to integrate with your systems, easy to use for anyone who requires it, and offer the choice of cloud or on-premise deployment.
Factor #5: Data security
We all understand the importance of security, and clearly data is no exception. Look for an anonymization provider that has gained relevant certifications such as ISO27001 and comply with the benchmark regulations such as GDPR. These indicators are the reassuring hallmarks of a provider’s commitment to data security.
brighter AI. Ticks every box, works out of the box
As the global leader in anonymization, brighter AI supports many of the world’s most innovative brands. The only fully compliant anonymization software on the market, brighter AI is also the fastest and most accurate available. Scalable but simple, it works out of the box with fast and easy API integration supporting all standard formats and codecs.
On-prem or cloud – your choice
You can choose how you deploy our software based on your existing infrastructure. Cloud deployment allows you to simply upload and download data without having to worry about scaling, hardware, servers, or maintenance. We take care of everything.
On-prem deployment, on the other hand, is ideal if you already have your own hardware or cloud subscription in place. In this case, you retain complete control while remaining responsible for data security outside the anonymization pipeline. The data never leaves your own data center.
Our intuitive user interface makes the whole process simple for both on-prem and cloud customers, ensuring that everyone who needs to use anonymization is able to do so. Simply select and upload your files, then download them again as soon as they are anonymized.
DNAT: the next generation of anonymization
In addition to traditional blurring technology, brighter AI also offers a unique cutting-edge Deep Natural Anonymization (DNAT). DNAT protects identities by generating synthetic overlays of faces and license plates, preserving the original data quality and accuracy and making it the best-in-class solution for analytics and machine learning – all while remaining compliant with all relevant privacy regulations. Plus, EuroPriSe certification provides the reassurance that your anonymized data can be reused for any use case. Have a look at our whitepaper to learn more about DNAT.