However, we can at least surmise what they’re able to do. Next, we will discuss how they actually get this data. Who are the potential sources and how do those sources obtain your phone locations? The location data is pretty extensive for certain people. According to fog data science, the owner of this software, they have billions of data points for 250 million devices, and this is just one surveillance tool. And you should think carefully here, although I’m revealing a tool used by law enforcement, you will find that these same data sets have been used by private companies and individuals.

Are you interested in fog and how this is used? Do you want to also learn how not to be in this location database? Stay right there. What is geofencing? What’s different about this surveillance method is that it does not use Google’s sensor vault. All the data captured come from location data brokers that are outside of Apple, Google, or Facebook sources. Google, of course, has its own geofencing tool, and it is frequently used by law enforcement and was key to the trial evidence for the J6 writers in a capital in 2021. But this tool doesn’t need a request to Google.

It is freely available by subscription, and they can use it an unlimited number of times. Geofencing is the process of marking out a particular location with boundaries, like a fence, and then querying the database of phone location entries to see who was there at some specific time range. So basically is a where and a when query. The basic problem with geofencing is that it is based on a dragnet approach. If you have no suspects, you just basically query anyone in an area at a given time, and then that gives you your potential suspects.

This way of generating a list of suspects potentially runs afoul of the fourth amendment, because people’s private data are acquired without a warrant. So there is no presumption of innocence with this technique. For example, in one particular publicized case of a burglary, the police simply search for people in the area and found a bicyclist at the location in question. That person was then arrested and charged based on just being at the location, as reported by his phone. Though apparently the bicyclist lived in the neighborhood and bikes through there all the time.

He had to fight this false arrest in court. He was eventually released, but this traumatic event cost him a lot of money to defend himself. There are a lot of nonpolice related uses of geofencing that demonstrates the evil of location tracking. In one case, someone made a killing in the stock market from being the first to use this data for financial intelligence. An investor spied on Tesla facilities using data similar to that used by fog data science. They basically surveilled the number of employees working in the Tesla factory to see if Tesla was expanding its production.

And using the geofence data from the factory historically, it showed a dramatic increase in people as a percentage. Using this data, this person justified buying call options right before the quarterly earnings report. And of course, Tesla announced the increase in the price of the stock jumped up. The investor obviously made a lot of money from basically inside information, but revealed by spying. Another nefarious use was the use of this type of database to find people who went into abortion clinics. This was potentially to find people who would violate new anti-abortion laws in some states.

Fog data science. The company we will discuss today is fog data science. According to their marketing materials, they are tracking more than 250 million devices with billions of location data points. This was based on information from three years ago, so it is likely more now. And this gives a subscriber the ability to get detailed access to the histories of the average person’s lives. Some people have a few data points a day, while others have hundreds of location data points each day. This data can be used to follow you around all day, so it should be evident where you live, where you work, and where you socialize.

Plus, it should also be able to identify if you took unusual trips or went to specific places that might profile you, like specific kinds of healthcare facilities or churches or political gatherings. Because it is based on historical data, it is very good at establishing patterns, which is how it is used to identify people rather than by direct ID. The company sells subscriptions to the service using a web portal called fogreveal.com, which I couldn’t access with a VPN. And apparently, this is being used by many law enforcement teams, such as local police, state police, and county sheriffs, at a cost of around $10,000 a year or so.

And there’s heavy use in California, from what I can see. How Fog Reveal Works Fog data science starts off by aggregating location data from various sources. Clues gathered by the EFF, the Electronic Frontier Foundation, suggest that their data may come from Ventel. Ventel is a big supplier of location data to government agencies. There are many location data sources and brokers. Brokers will aggregate data from multiple sources. The way this particular data location database is organized is by latin long, meaning GPS coordinates. And then this is further organized by timestamps and then a device ID.

The specific device ID use, in this case, is the advertising ID. Advertising IDs are found in all normie phones like iPhones and Google androids. An advertising ID is a unique identifier. And I’ll explain later how this is collected by the location data brokers. Now, advertising IDs are not permanent identifiers per se, but the normal person will not mess with this. So in effect, it’s permanent for the average person that is not privacy aware and uses standard devices. Fog Data Science claims that their database does not contain personally identifiable information or PII.

But as you will see, it should be a piece of cake identifying anyone, even if you changed your advertising ID. As I mentioned, this location database is historical and long term. The Fog Data Science databases apparently go back to 2017. So it is based on historical data. And this is something that the average person is totally not versed in. If I knew someone’s location history, in the kind of detail available in this kind of database, I would know so much about a person, particularly if I overlay the locations over a Google Earth map.

And that will be obvious when you actually use Fog Reveal. Fog User Manual. Now, fortunately for this video, I have the actual user manual. And although it’s low resolution, it gives us an idea of the capabilities. The Fog Reveal web portals intended for law enforcement use. So the format is made to be filed by case at the law enforcement department system. The basic interface starts with Google Earth. So you pick out a location that you want to research, and then you find it on the map. Then you draw a boundary on the map, and it appears from the examples that you can draw a rectangular boundary or a circle.

After that, you specify a time range and perform the query. Then after a few seconds, the Apple display red dots showing phones found at that location. There’s a list of data points showing the actual lat long and device ID, plus the timestamp, and that’s shown in another window. This can then be exported to a CSV file, so you can work it in an Excel spreadsheet, for example. The area covered by the boundary of the query can apparently be very large. I’ve read that it can cover up to 20 kilometers, which is a little over 12 miles.

That creates a lot of data points, obviously, and can include millions of people. Deeper analysis. Now, here’s where some deep analysis can be performed. You’re allowed to search for multiple geofences simultaneously. For example, you can search for people that have appeared in multiple geofence locations over a period of time. This can then lead to analysis of associations and basically habits of the individuals and those they associate with. Again, know that this is a dragnet approach. There is no identified criminals in this search. This is a search of the general population. The other way it can be used is if some particular device IDs are identified.

Then you can search for known locations frequented by such device IDs. And this, of course, leads to the full identification of the individuals, since you can cross-check their home addresses. There are plenty of other databases that show verified addresses. So with or without more advanced permanent identifiers like Google ID, Apple ID, Mac address, MZ, or IMEI, it is a piece of cake to find anyone and then turn them into a specific suspect. It should be a small matter, for example, to identify all the people participating in the George Floyd BLM looting or burned buildings here in Santa Monica, California, for example, find their device identifiers, and then see where they went home that day.

And voila, you could have arrested the looters and arsonists. But of course, you will find this technology used selectively with a political focus. It was used extensively for J6 writers because that particular government wanted to make a point. While fog data science may not directly give access to fog revealed to private parties, they will do analysis for private parties. And here’s a list of what they claim they can do. Number one, verifiable presence at a location on a specific date and time. Number two, likely locations for residences, places of business, and frequent activities.

Number three, links to other individuals, places, and devices. Number four, patterns of activity correlating to certain events, times, or alibis. If this isn’t private mass surveillance, I don’t know what is. Again, realize that this is just one particular tool and one data source. How this location data is captured. There are several ways location data are captured. Google and Apple have a precise moment by moment history of locations which are collected 24-7, and this is permissionless. You cannot stop this if you have an iPhone or a Google Android. But the lower tech capability of Vental, the probable supplier of location data here, is still powerful enough.

Some parties have used this kind of data to prove political theories, for example, like tracking those people who repeatedly dropped off ballots on ballot boxes. There are plenty of uses of this, but not everyone is vulnerable to this, and I will explain that in a moment. In the meantime, this particular fog data science data is captured from mobile apps. How mobile apps sell your location. There are several apps implicated in the location selling infrastructure, specifically mentioned as sources to fog data science are Starbucks and Waze. In the past, another app publicized as profiting from location sales was the Weather Channel app which is owned by IBM.

But if you think these are the only sources, the estimate of apps providing data are around 700 apps. So if you’re fond of installing tons of apps, then the chances of you contributing to the location database is pretty high. Because the sources of locations are apps, the apps need to have location permissions. Unlike Google and Apple, these permission restrictions cannot be overridden. So some of you will allow locations while using the app, which is more restrictive. Some of you don’t care, and the apps are constantly pinging location. This is why some will report hundreds of location pings a day, while some show only a few instances a day.

The actual mechanism of collecting location data is through ads. Free apps that require you to provide location are often suspect, as the requirement to give location is often a clue that they are making money on the side. On my suspect list would be apps like Yelp, Craigslist, and potentially apps that already require location, normally like Uber, Lyft, Grubhub, and so on. The ad spaces on the apps are put in an online auction with your advertising ID and your location. And then advertisers who win a bid will be able to pop an ad on a targeted audience.

Advertising IDs are attached to a profile and combined with location shows preferences. But the people collecting the data from the ad spaces are the ones that are selling the location. They are just capturing the auction data and storing it in their database. Depending on the data broker, other pieces of data can be associated with the location, including email, phone number, login ID, and so on. What I’m demonstrating here is that even with very few pieces of information, the location data itself is already very revealing. The specific location technology. The main location sensor on the phone is the GPS when you are outdoors.

And when indoors, it switches to something called a Near Location Provider or NLP. And this gives them a location based on Wi-Fi triangulation. This ensures that the location is within six feet or even better for Apple devices. Those can give locations in inches as proven by Apple AirTags. Since the location used is app permission based, then it is possible to disable this by making sure you limit location permissions on most apps that don’t need permissions. And then limit the use of locations to apps that you feel are safe for this.

Generally, apps from banks, financial firms, and government are unlikely to be selling location data. And generally also apps that are not specifically in the location business like Uber and Lyft and so on, and do not pop ads typically will not be subject to location harvesting. But you can still always turn location off just in case. Who is vulnerable? Fortunately, many of my followers who already follow my advice and the devices I recommend may be immune from location tracking via fog data science. For example, the Google phones like the ones we sell do not have advertising IDs.

So the primary device identifier used for collecting low location data does not exist. Second, those using a safe the Google OS also have a disabled near location provider. For example, Brax OS did not have Wi-Fi triangulation enabled indoors. When indoors, it can use a rough cell tower triangulation, which can be a large location target like one half mile square. That is not accurate enough to reveal a home address. GPS, of course, can still be used to attract you if you’re using one of the dangerous apps outdoors, but at the maximum set the app permissions to be while using the app, otherwise turn location permissions off.

Fortunately, the Google phones have superior advantages to even the more advanced tracking performed by Google and collected in the Google sensor vault. Since the Google phones do not connect to Google, there’s no direct pathway for such location data to be collected, and there is no Google ID to identify the phone. So in general, it is my belief that anyone currently using a D Google phone should not exist in the Google sensor vault, nor the fog data science tool. This is why a D Google phone is one of the key ingredients to personal privacy.

There really is no choice if you care about privacy. Those who are vulnerable are the normies, the users that buy the newest iPhone and Samsung without care. All they want is to have fun with their phones. And it is their life. In another video, I will actually go into depth of what is collected by these data brokers, based on data of your internet activity and mobile phone use. And these are again, outside of the massive data already owned by Google, Apple and Facebook. Folks, as many of you know, this channel does not have sponsors.

Instead, we rely completely on community support to keep us going. Hopefully we give you enough information that you find value. Some of you support us on Patreon, locals and YouTube memberships. And though I don’t publicly acknowledge you for privacy reasons, you are very appreciated. Thank you. For most of our support, we instead strive to provide products and services that help you in your privacy journey. Our newest product is the Brax 3 Privacy Phone. This is a community project involving several companies and is currently sold on indiegogo.com. This is about to be released and we are just awaiting a final version from our OS partner, EODay OS.

We have other products and services that can be found on our privacy social media site, BraxMay. We have Brax Virtual Phone that gives you inexpensive no-KYC phone numbers. We have BraxMail, which offers unlimited illnesses and many domains to create different identifiers. We have BICE VPN, which protects your IP addresses from being harvested by data brokers. Join us here on BraxMay and meet the way over 100,000 users who discuss privacy issues daily. Thank you for watching and see you next time. [tr:trw].

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