Personally identifiable information (PII) is frequently compromised. This is a crucial issue because compromised PII can and does result in identity theft. Yet the storage and query techniques currently used to process PII facilitate, rather than guard against, breaches to such information. Although research and development of distributed systems has greatly improved the performance of Big Data analytics, the best practices implemented within that context have not been extended to security standards for personal information. As a result, the breach of a single database can expose millions of full sets of PII. In this research, we design a structure of individually secured nodes. Then, taking a set of PII, we strategically group specific elements of personal information together and distribute those subsets across our structure, applying best practices as seen in other fields to PII security. In so doing, we demonstrate how the well-established concepts of data and server isolation can be extended to PII.
