First Known When Lost
February 3, 2015·0 comments·big data
We guard our social security numbers obsessively while handing over something far more revealing without a second thought: our behavioral patterns. A small amount of anonymous transaction data can expose who we are, where we live, and what we do with better accuracy than any name or account number ever could.
- The re-identification paradox: Researchers found that just four pieces of metadata (timing, location, and similar details) were enough to uniquely identify 90 percent of people in a dataset of 1.1 million anonymous credit card transactions. Traditional security thinking protects the wrong information.
- Non-human pattern recognition: Big Data systems don't think like humans hunting for your identity. They process behavioral patterns across millions of people simultaneously, inferring what any of us will do under similar conditions. This creates possibilities that human brains can barely comprehend.
- Private institutions are building the machine: Mega-banks and asset managers are now collecting portfolio behavioral data with the same casual access they have to transaction data. Systems being built today can predict investment decisions with 90 percent accuracy based on nothing but anonymous behavioral history.
- Regulators aren't defending against this: Government agencies are too busy running their own data collection projects to constrain private sector surveillance. Once data gets collected, it sits in databases waiting for someone competent enough to mine its value.
- The magic is already here: We convince ourselves this is a future threat, but the capability to map our lives through metadata already exists. The only question remaining is how, and by whom, it gets weaponized.
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