Protegrity Blog

Balancing Privacy and Big Data

In a recent article from the NY Times titled “Big Data is Opening Doors, but Maybe Too Many“, Steve Lohr details the delicate balance of privacy restrictions and the use of Big Data analytics to make smarter decisions in every field from business and biology to public health and energy conservation. Big Data is a new and exciting asset, but in order for the information to be useful, it must be liquid. Data privacy laws could put a significant halt to the fast moving train of Big Data unless the industry adopts effective data protection. Current regulations only provide for access controls on data, which have been proven ineffective against data leakage. Multi-tenant central storage environments put the data at risk for internal data breaches and external threats. Data breaches can cost organizations all of their hard earned investments in Big Data solutions, with millions in breach fees and incalculable damage to brand image. “We do need use restrictions, but there is a real problem with getting rid of data collection restrictions,” says David C. Vladeck, a professor of law at Georgetown University. “And that’s where they are headed.” Anonymization or de-identification of the data is the key to success, as only solutions that provide privacy and true data security without losing the statistical value of the information can achieve the balance required to make secure use of Big Data analytics. These solutions include:

  • Data Tokenization
  • Data Encryption
  • Data Masking

Organizations need to be proactive on privacy when storing personal information, as retroactive protection can be a harrowing process, especially in read-only Big Data environments, where the data cannot be altered once it enters the system. In addition, new regulations requiring anonymized or de-identified data are on the horizon, and preparing for them now could pay huge dividends later, saving the time and money required to anonymize or de-identify millions or billions of backlogged records stored in Big Data environments. To read the full NY Times article, please click here.

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