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Solving For Data Security And Privacy In IOT
Carole Murphy, Product Marketing Manager, HPE Security – Data Security, Hewlett Packard Enterprise
The data generated from IoT is a valued commodity for adversaries, as they can piece together sensitive information to build a user profile that contains Personally Identifiable Information (PII), Payment Card Information (PCI) or Protected Health Information (PHI). For example, a breach of a connected blood pressure monitor’s readings alone may have no value to an attacker, but when paired with a patient’s name, it could become identity theft and a violation of (HIPAA) regulations. A “data-centric” approach to security is essential in protecting this sensitive information in the instance of a breach.
However, implementing a data-centric security approach can be a daunting process, especially in the rapidly evolving Hadoop space. It is essential for long-term success and future-proofing investments, to apply technology via a framework that can adapt to the rapid changes in Hadoop “data lake” and IoT environments.
The integration of high-strength format-preserving encryption with NiFi processor technology extends data centric protection for IoT data
Unfortunately, implementations based on agents frequently face issues when new releases or technologies are introduced into the stack, and require updating in Hadoop multiple times.
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.
Headquartered in California, USA, Hewlett Packard Enterprise (NYSE: HPE) specializes in IT services and has catered to numerous businesses in their transition from traditional technology platforms to the IT systems of the future.
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