Introducing the Otonomo Anonymization Engine

In our consumer survey earlier this year of 1,070 connected car owners and new car buyers, two-thirds reported that they have chosen not to use online services and apps because of their concerns about personal information being compromised. Drivers’ privacy concerns are one of the biggest potential barriers to developing an ecosystem of applications that utilize the data generated by connected cars. At Otonomo, we have been hard at work developing new ways to protect driver privacy, provide choices for them, and earn their trust.

In May, we announced the Consent Management Hub, which validates consent with each personal data request from third-party mobility service providers. Today, we’re announcing the Otonomo Anonymization Engine, which provides sophisticated anonymization techniques that address the unique needs of connected car data. We can now support even more use cases—both personal and anonymized—through the Otonomo platform.

The value of anonymous mobility data

Data uses that have gotten early publicity tend to enable individual driver services, which require personal data to varying degrees – your parking app needs to know where your car is; your insurer can lower your bill for driving safely if you’ve permitted them to track when and how you drive. But personal data is half the story. Anonymous mobility data can help make many services we receive today better, by offering providers a macro-level lens – your car company can detect early part failures to avoid major recalls; energy analysts can pinpoint where to best place EV charging stations; your city can reduce car idling carbon emissions; retail stores can better match store hours to traffic. We have yet to scratch the surface of what’s possible.

Preserving privacy and data usefulness

Before mobility data can be used for macro-level analysis, it must be properly anonymized, which means removing data that can identify an individual, directly or indirectly.  A driver can be identified not only by personal information but also indirectly by the vehicle’s VIN number, location, or trip patterns, such as driving daily to and from work. But ‘brute force’ anonymization would render the data useless for macro purposes. There’s a different “best way” to anonymize data for each use case. The magic of the Anonymization Engine is that it can apply different techniques depending on the intended use, providing robust GDPR-compliant data privacy safeguards while preserving the commercial value of the data.

How it works

The Anonymization Engine first strips off personal data, such as driver information or VIN. Then, it chooses the right algorithm to blur location, time or trip data while maintaining the required use case parameters. Finally, the solution is fine-tuned to user requirements, local regulations, and any other applicable privacy policies.

Announced today, the Anonymization Engine is available now as an embedded service of the Otonomo Automotive Data Services Platform, or as an on-premise managed service for OEMs, benefiting from Otonomo’s privacy platform expertise, innovative solution development, rapid implementation, and ongoing support.

Better anonymization grows the automotive data ecosystem

Above all, OEMs  get peace of mind that driver data is protected while app developers and service providers gain access to valuable data that they can confidently use to deliver a wide range of apps and services, such as mapping, managing car health, planning smart city infrastructure, or conducting traffic pattern research for retail, media, and many other use cases.

If you’d like to learn more, we’ll be available to answer questions at TU Automotive Europe in Munich today. I’ll look forward to starting a dialogue, so please stop by if you’re at the event or another one of our upcoming conferences.

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