Solving For Data Security And Privacy In IOT

What’s needed is a framework that enables rapid integration into the newest technologies, to allow broad access to data for secure analytics. The obvious answer for true Hadoop security is to augment infrastructure controls that protect the data itself. This data-centric security approach calls for de-identifying the data as close to its source as possible. By combining two technologies—format-preserving encryption, and Apache NiFi technology—organizations can get a framework that extends data-centric protection from simply Big Data to the IoT edge.

With format-preserving encryption, protection is applied at the data field and sub-field levels, preserving characteristics of the original data–such as numbers, symbols, or letters in a birth date or salary range–and maintaining the referential integrity across distributed data sets. This protected form of the data can then be used in applications, analytic engines, data transfers, and data stores, while being readily and securely re-identified for those specific applications and users that require it. As with other data sources, sensitive streaming information from IoT connected devices and sensors can be protected with format-preserving encryption to secure sensitive data from both insider risk and external attacks, while the values in the data maintain usability for analysis.

Apache NiFi, a recent technology innovation, is enabling IoT to deliver on its potential for a more connected world. Apache NiFi began as a Federal government project, then became a start-up, and subsequently developed into an open source platform that enables security and risk architects, as well as business users, to graphically design and easily manage data flows in their IoT or back-end environments.

The integration of high-strength format-preserving encryption with NiFi processor technology extends data-centric protection for IoT data throughout its lifecycle by enabling organizations to encrypt streaming data at scale, before it moves into the back-end Hadoop data lake for secure analytics. With these solutions, organizations can incorporate data security into their IoT strategies by allowing them to more easily manage sensitive data flows and insert encryption closer to the intelligent edge.

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