Mobito Marketplace feature release: Dynamic Data Masking

Mobito Marketplace Data Exchange Tools

At Mobito we strive to unlock the value of data for companies and society at large. Exchanging data should not be limited by regulations that attempt to correct it but rather evolve to reflect the multi-stakeholders requirements. Acknowledging the uncertainty, anxiety and lack of comfort that organisations feel in navigating these requirements, we are developing tools that empower data owners with data sharing control. With dynamic data masking, data owners can select what part of their data to share with which recipients, allowing more precision and flexibility in data sharing

Data-privacy vs data exchange incentives

First some context. 3 years have passed since GDPR (General Data Protection Regulation) was established as a new law governing data privacy across EU countries. Worldwide, the discussion for data privacy protection has been evolving and has led to other regulations including the Australia’s Privacy Act, Canada’s Personal Information Protection and Electronic Documents Act (PIPEDA) and the most recent California Consumer Privacy Act (CCPA). At the same time, the appetite of companies and industries to combine data from different sources for the generation of smarter products and services is increasing. This appetite is often at odds with data sharing restrictions that may paralyze initiatives that lack the knowledge to achieve business goals while preserving privacy and respecting relevant regulations.

Similar restrictions have existed long before GDPR as businesses, governments and organizations needed to communicate data with third parties and internal collaborators while taking care of data-parts that were private or confidential from a personal, enterprise and commercial standpoint. As more data is becoming available from IOT devices and enterprise operations, data sharing is increasingly locking horns with data-privacy concerns.

Use Cases

The mobility space and the movement and interaction of people generate massive amounts of data that can fuel innovation and better services that address a lot of the urban-life challenges. However, mobility data is often classified as personal data, insofar the geolocation of individuals can be revealing of an individual’s identity when combined with other datasets (e.g. addresses). Therefore it becomes a challenge for data owners including cities and mobility operators to utilize effectively this valuable informational asset while remaining compliant.

In another front insurance companies depend on various sources of data so as to improve existing products or create new ones. Pay-as-you drive insurance, claims management, forecasting models or real-time notifications, are use cases heavily dependent on data. Many datasets that are accessed by clients or acquired externally contain sensitive information that often act as barriers to their effective use. Data usage and sharing in a structured and controlled environment is again crucial.

Moreover, in insurance as well as a variety of other industries the sensitivity-barriers in leveraging the most value from data exist within the organisation as well. Moving sensitive data between departments, allowing access to privacy sensitive information and creating unmonitored copies, increases data vulnerability and compliance risks. Instead of blocking this vital information flow, data sharing with appropriate masking tools can allow departments to collaborate effectively and confidently.

Dynamic Data Masking

Data providers in the Mobito Marketplace can now access on-the-fly, or dynamic data masking of their data. Data providers can choose which parts of their data contain sensitive information and should be marked as such. Moreover, providers can select for each approved data collaborator/ consumer which parts of pre-tagged sensitive data should be masked and how- choosing from a drop-down list of masking tools. This way both what is shared and who can access it is controlled through an intuitive tool kit.

Step 1: Data owner tags API properties

Step 2: Data owner applies masking rule on tagged properties for each data request

Next steps

We will next support Static Data Masking allowing data providers to create a masked copy of their data before sharing- addressing the cases where data is exchanged via files, rather than through APIs. This solution serves well in cases of internal sharing in an organization, where once-off data exchanges are often most efficient.

Mobito is a tech company. We help businesses unlock the value of data by exchanging data in a scalable & controlled way and monetizing it in our Marketplace.

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