Data brokers are selling flight information to CBP and ICE

Sounds like if you have a record of a lot of location/timestamp data for people, you look at the distance difference divided by the time difference. Now you have average speed for any pair of points. Now filter where the average speed is as fast as a Boeing jet. That filters out most of the data except for people who are almost certainly on a plane. Et voila, you now look at those data points geolocation and you have people who traveled from one city to another because you already have the location. Compare City1 -> City2 with any public flights in those cities around those times and you know who flew on what flight from where to where and at what time.

In this particular case it was just a proof-of-concept, albeit at scale. We did not run a proper ground-truthing process but people actually running that type of data model in production could have ground-truthed the analytic model if they wanted to.

However, it turns out that thousands of people like to talk about their flights on social media, so we scraped that as a spot check and it mostly lined up perfectly. Good enough for a demo and it would have been difficult to come up with an alternative explanation for the patterns in the data.

The purpose of the PoC was to sell the data analysis infrastructure that made that type analysis possible at scale, it wasn't about the data per se. It was a compelling demo we invented given the data that happened to be available. Startup life.

i don't have any special knowledge in this area, but just thinking about it idly while sitting here, "robbing their homes while they are away" comes to mind as a good proxy.

Could you elaborate with specifics? If it's this bad, why haven't we heard anything from a whistleblower or seen a good demo?

Anyway to combat it or stop your info from being overly harvested?

I asked this same thing in another comment here, but since you mention working in this space, I ask you directly. Where do the brokers obtain their data from? If it's easy for them to obtain, would those who buy it from brokers not be able to simply get it from its respective sources? I'm genuinely curious about how this dynamic works.

It has been truly frustrating when people will blame the "tech industry" for what is essentially reckless behavior from other industries. For a while, it was often the finance sector that did most of the crazy stuff. With crypto being an obnoxious overlap of the two.

Is that actually possible? Can we do a live test here?

Let's say we want this dataset: Credit card line items for 35-year-old dentists living on the 400 block of Elm street in local town

How much do I have to pay you to get it?

This is correct; what people fundamentally misunderstand is that data brokers directly sell personal information about people, but Google and Facebook only allow for targeted advertising while keeping personal information within the confines of their company.

I'm also surprised that this is so hidden from everyone. Where are the engineers leaking secrets? Much of the online discourse is pure speculation based on what can be observed from the very end of the chain. (ie, what your computer is giving up) The speculation is not necessarily _incorrect_ but is too vague to be useful to anyone. Where does my data _actually_ go? Does anyone know? Can anyone describe the life of my data as it goes through the whole ecosystem? Does anyone know what mitigations are, and are not effective?

Anyway to opt out of this type of data collection per company? I know for some things you can contact each individual broker and opt out (via some identifier like your email address) of your data being at least publicly available

> Your basic hackernews believes that e.g. Google is out there selling all your personal information

To add to this, any mention of "telemetry" is taken to mean your PII being taken by bad actors to abuse, instead of what it is in 99% of cases, which is usage statistics. (X% of our users use feature A, it merits investment). It can be both, but there's usually no place for differentiation, just pitchforks.

Okay, and who are these people you contact for this data, and how do they themselves obtain it so precisely? You say the big tech industry is pretty air-tight about sharing data, so how does mysterious X company have on hand the credit ratings of all those youngish dentists on Elm street, among other kinds of information? How o these dynamics work, since you seem to know it internally?

> Wouldn't it be simple for those who buy it from the brokers at a markup to just get it from its original sources themselves?

In many cases joining datasets is both labor intensive and creates a surprising amount of new information, and there is also plenty of "free" data that is incredibly tedious to work with.

I used to work with real estate data for the government and if you search for any common things you might want to know you often land on a data brokers page even though property assessor data is freely available in most counties. The problem is each county has their own system of storing data and their own process for searching it. It's a lot of work to learn how just this one dataset works, combining this for all counties in the US is a massive project.

Whenever I buy a new home I always look up all my neighbors, figure out when they bought the house, how much they paid etc. Some people get freaked out by this, but this information is public in most counties.

By joining this data with another public data set, you can actually figure out which lender your neighbors used and what their reported income at time of sale, their age and ethnic background.

Of course there are plenty of other ways data brokers come across data, but even cleaning up and joining public data can require a fair bit of time and expertise.

>My question here is also how the brokers obtain the data themselves? Wouldn't it be simple [...] to just get it from its original sources themselves?

The word "broker" in "data brokers" may be misleading. They're not like a middleman-agent type of broker that is an intermediary in between buyers & sellers for transacting houses, yachts, expensive paintings, etc. They don't really act as a classical broker for matching unknown data-sellers with unknown data-buyers.

Instead, the so-called brokers when describing big data collection companies like LexisNexis and ACXIOM are actually sophisticated data hubs that gather a lot of raw data like court house filings across all counties and states, bankruptcy filings, property records that have deeds and mortgage amounts, police arrest records, vehicle registrations, driving records, employment records, etc. Some data is so raw that they have to do OCR on document images to digitize it. A lot of those sources really aren't "for sale" to the general public. The data hubs make private contractual arrangements to buy the data.[1] They also get a lot of 1st-party data directly from participating entities like retailers and insurance companies. Example would be Equifax The Work Number getting direct employment data. Equifax would be both the original source and the so-called "data broker" in that case.

The data hubs then do massive de-duplication and correlation of all those datasets to create a composite profile and id of each person. This "complete picture" of a person (age, estimated income, etc) is what marketers are buying. Even if some data is public like court records, the random marketer who wants to do a mass-mailing to advertise a new restaurant isn't interested in logging into various court houses to look at raw data. They want the composite demographics that a company like LexisNexis has.

[1] example of DMV vehicle registrations: https://www.google.com/search?q=states+dmv+sell+car+registra...

Sellers of the data wanna deal with one or a few buyers that buy bulk. They dont wanna deal with thousands of customers.

The regulatory angle at least explains part of my wondering. I'm not really surprised that they have access to this information, I'm just surprised that they buy it, rather than just demanding it be handed over.