The world is currently generating up to 2.5 quintillion bytes of data every day.
Here are more statistics on data: Americans produce 265.77 gigabytes of data per minute, 46,800 photos are uploaded to Instagram every minute, and internet users make 3.6 million searches on Google per minute.
Big data and artificial intelligence have brought huge changes to the finance industry. Wearable technology has also fueled the rapid growth of life science data.
Be it financial data such as assets and credit ratings, or health and medical statistics, such information is highly sensitive and could have a far-reaching impact if it falls into the wrong hands.
It has become increasingly difficult to control data leak risk using existing management rules and procedures. That’s why it has caught the attention of regulators.
In fact, regulators from various nations have started to draft rules aimed at enhancing big data protection. In the United States, top universities such as MIT and UC Berkeley are working on data security.
There are three main directions.
First, data used for making analysis are placed under encryption, such as homomorphic encryption.
Second, data can be locked in a closed environment, and only approved analysts can access the data. This is called differential privacy.
Third, data is stored separately based on the source of the information. It is transmitted and shared under encryption, and managed under a private key agreement enabled by blockchain technology. This is called secure multiparty computing for data mining.
These technologies are all intended to reduce the costs associated with meeting compliance requirements.
This article appeared in the Hong Kong Economic Journal on March 22
Translation by Julie Zhu
[Chinese version 中文版]
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