Friendly Webcam Robot Keeps An Eye On Privacy

June 14, 2021 by Kristina Panos 8 Comments

Wouldn’t it be nice if every webcam had a hardware switch? Especially for those built-in webcams like the one in your laptop. Since they don’t have switches yet, we’re just stuck trying to remember to turn them off or re-apply the sticker after every meeting. [Becky Stern] was tired of trying to remember to blind the all-seeing eye, and decided to make a robot companion that would do it for her.

Essentially, a servo-driven, 3D-printed eyelid covers the eye’s iris and also the web cam directly underneath. At first, we though [Becky] had liberated the business parts of a cheap webcam and built it into the eyeball, but this is far less intrusive. The eyeball simply sits atop the monitor, and [Becky] can control the eyelid two ways: she can set a timer with the potentiometer to close it automatically after some number of minutes, or else do it on demand using the momentary button. We’d love to see it tied directly to Zoom and or whatever else [Becky] uses regularly. Be sure to check out the build and demo video after the break to see it in action.

We love this cute and friendly reminder that the camera could be watching us. It’s way less creepy than this realistic eyeball webcam that looks around and blinks.

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Speech Recognition On An Arduino Nano?

May 26, 2021 by Orlando Hoilett 24 Comments

Like most of us, [Peter] had a bit of extra time on his hands during quarantine and decided to take a look back at speech recognition technology in the 1970s. Quickly, he started thinking to himself, “Hmm…I wonder if I could do this with an Arduino Nano?” We’ve all probably had similar thoughts, but [Peter] really put his theory to the test.

The hardware itself is pretty straightforward. There is an Arduino Nano to run the speech recognition algorithm and a MAX9814 microphone amplifier to capture the voice commands. However, the beauty of [Peter’s] approach, lies in his software implementation. [Peter] has a bit of an interplay between a custom PC program he wrote and the Arduino Nano. The learning aspect of his algorithm is done on a PC, but the implementation is done in real-time on the Arduino Nano, a typical approach for really any machine learning algorithm deployed on a microcontroller. To capture sample audio commands, or utterances, [Peter] first had to optimize the Nano’s ADC so he could get sufficient sample rates for speech processing. Doing a bit of low-level programming, he achieved a sample rate of 9ksps, which is plenty fast for audio processing.

To analyze the utterances, he first divided each sample utterance into 50 ms segments. Think of dividing a single spoken word into its different syllables. Like analyzing the “se-” in “seven” separate from the “-ven.” 50 ms might be too long or too short to capture each syllable cleanly, but hopefully, that gives you a good mental picture of what [Peter’s] program is doing. He then calculated the energy of 5 different frequency bands, for every segment of every utterance. Normally that’s done using a Fourier transform, but the Nano doesn’t have enough processing power to compute the Fourier transform in real-time, so Peter tried a different approach. Instead, he implemented 5 sets of digital bandpass filters, allowing him to more easily compute the energy of the signal in each frequency band.

The energy of each frequency band for every segment is then sent to a PC where a custom-written program creates “templates” based on the sample utterances he generates. The crux of his algorithm is comparing how closely the energy of each frequency band for each utterance (and for each segment) is to the template. The PC program produces a .h file that can be compiled directly on the Nano. He uses the example of being able to recognize the numbers 0-9, but you could change those commands to “start” or “stop,” for example, if you would like to.

[Peter] admits that you can’t implement the type of speech recognition on an Arduino Nano that we’ve come to expect from those covert listening devices, but he mentions small, hands-free devices like a head-mounted multimeter could benefit from a single word or single phrase voice command. And maybe it could put your mind at ease knowing everything you say isn’t immediately getting beamed into the cloud and given to our AI overlords. Or maybe we’re all starting to get used to this. Whatever your position is on the current state of AI, hopefully, you’ve gained some inspiration for your next project.

PSA: Amazon Sidewalk Rolls Out June 8th

May 19, 2021 by Kristina Panos 41 Comments

Whether you own any Amazon surveillance devices or not, we know how much you value your privacy. So consider this your friendly reminder that Amazon Sidewalk is going live in a few weeks, on June 8th. A rather long list of devices have this setting enabled by default, so if you haven’t done so already, here’s how to turn it off.

Don’t know what we’re talking about? Our own Jenny List covered the topic quite concretely a few months back. The idea behind it seems innocent enough on the surface — extend notoriously spotty Wi-Fi connectivity to devices on the outer bounds of the router’s reach, using Bluetooth and LoRa to talk between devices and share bandwidth. Essentially, when Amazon flips the switch in a few weeks, their entire fleet of opt-in-by-default devices will assume a kind of Borg hive-mind in that they’ll be able to share connectivity.

A comprehensive list of Sidewalk devices includes: Ring Floodlight Cam (2019), Ring Spotlight Cam Wired (2019), Ring Spotlight Cam Mount (2019), Echo (3rd Gen), Echo (4th Gen), Echo Dot (3rd Gen), Echo Dot (4th Gen), Echo Dot (3rd Gen) for Kids, Echo Dot (4th Gen) for Kids, Echo Dot with Clock (3rd Gen), Echo Dot with Clock (4th Gen), Echo Plus (1st Gen), Echo Plus (2nd Gen), Echo Show (1st Gen), Echo Show (2nd Gen), Echo Show 5, Echo Show 8, Echo Show 10, Echo Spot, Echo Studio, Echo Input, Echo Flex. — Amazon Sidewalk FAQ

Now this isn’t a private mesh network in your castle, it’s every device in the kingdom. So don’t hesitate, don’t wait, or it will be too late. Grab all your Things and opt-out if you don’t want your doorbell cam or Alexa machine on the party line. If you have the Alexa app, you can allegedly opt out on all your devices at once.

Worried that Alexa is listening to you more often than she lets on? You’re probably right.

Telemetry Debate Rocks Audacity Community In Open Source Dustup

May 17, 2021 by Tom Nardi 107 Comments

Starting an open source project is easy: write some code, pick a compatible license, and push it up to GitHub. Extra points awarded if you came up with a clever logo and remembered to actually document what the project is supposed to do. But maintaining a large open source project and keeping its community happy while continuing to evolve and stay on the cutting edge is another story entirely.

Just ask the maintainers of Audacity. The GPLv2 licensed multi-platform audio editor has been providing a powerful and easy to use set of tools for amateurs and professionals alike since 1999, and is used daily by…well, it’s hard to say. Millions, tens of millions? Nobody really knows how many people are using this particular tool and on what platforms, so it’s not hard to see why a pull request was recently proposed which would bake analytics into the software in an effort to start answering some of these core questions.

Now, the sort of folks who believe that software should be free as in speech tend to be a prickly bunch. They hold privacy in high regard, and any talk of monitoring their activity is always going to be met with strong resistance. Sure enough, the comments for this particular pull request went south quickly. The accusations started flying, and it didn’t take long before the F-word started getting bandied around: fork. If Audacity was going to start snooping on its users, they argued, then it was time to take the source and spin it off into a new project free of such monitoring.

The situation may sound dire, but truth be told, it’s a common enough occurrence in the world of free and open source software (FOSS) development. You’d be hard pressed to find any large FOSS project that hasn’t been threatened with a fork or two when a subset of its users didn’t like the direction they felt things were moving in, and arguably, that’s exactly how the system is supposed to work. Under normal circumstances, you could just chalk this one up to Raymond’s Bazaar at work.

But this time, things were a bit more complicated. Proposing such large and sweeping changes with no warning showed a troubling lack of transparency, and some of the decisions on how to implement this new telemetry system were downright concerning. Combined with the fact that the pull request was made just days after it was announced that Audacity was to be brought under new management, there was plenty of reason to sound the alarm.

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A Dutch City Gets A €600,000 Fine For WiFi Tracking

May 8, 2021 by Jenny List 51 Comments

It’s not often that events in our sphere of technology hackers have ramifications for an entire country or even a continent, but there’s a piece of news from the Netherlands (Dutch language, machine translation) that has the potential to do just that.

Enschede is an unremarkable but pleasant city in the east of the country, probably best known to international Hackaday readers as the home of the UTwente webSDR and for British readers as being the first major motorway junction we pass in the Netherlands when returning home from events in Germany. Not the type of place you’d expect to rock a continent, but the news concerns the city’s municipality. They’ve been caught tracking their citizens using WiFi, and since this contravenes Dutch privacy law they’ve been fined €600,000 (about $723,000) by the Netherlands data protection authorities.

The full story of how this came to pass comes from Dave Borghuis (Dutch language, machine translation) of the TkkrLab hackerspace, who first brought the issue to the attention of the municipality in 2017. On his website he has a complete timeline (Dutch, machine translation), and in the article he delves into some of the mechanics of WiFi tracking. He’s at pains to make the point that the objective was always only to cause the WiFi tracking to end, and that the fine comes only as a result of the municipality’s continued intransigence even after being alerted multiple times to their being on the wrong side of privacy law. The city’s response (Dutch, machine translation) is a masterpiece of the PR writer’s art which boils down to their stating that they were only using it to count the density of people across the city.

The events in Enschede are already having a knock-on effect in the rest of the Netherlands as other municipalities race to ensure compliance and turn off any offending trackers, but perhaps more importantly they have the potential to reverberate throughout the entire European Union as well.

“Alexa, Stop Listening To Me Or I’ll Cut Your Ears Off”

February 2, 2021 by Dan Maloney 88 Comments

Since we’ve started inviting them into our homes, many of us have began casting a wary eye at our smart speakers. What exactly are they doing with the constant stream of audio we generate, some of it coming from the most intimate and private of moments? Sure, the big companies behind these devices claim they’re being good, but do any of us actually buy that?

It seems like the most prudent path is to not have one of these devices, but they are pretty useful tools. So this hardware mute switch for an Amazon Echo represents a middle ground between digital Luddism and ignoring the possible privacy risks of smart speakers. Yes, these devices all have software options for disabling their microphone arrays, but as [Andrew Peters] relates it, his concern is mainly to thwart exotic attacks on smart speakers, some of which, like laser-induced photoacoustic attacks, we’ve previously discussed. And for that job, only a hardware-level disconnect of the microphones will do.

To achieve this, [Andrew] embedded a Seeeduino Xiao inside his Echo Dot Gen 2. The tiny microcontroller grounds the common I²S data line shared by the seven (!) microphones in the smart speaker, effective disabling them. Enabling and disabling the mics is done via the existing Dot keys, with feedback provided by tones sent through the Dot speaker. It’s a really slick mod, and the amount of documentation [Andrew] did while researching this is impressive. The video below and the accompanying GitHub repo should prove invaluable to other smart speaker hackers.

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Teardown: Tap Trapper

January 14, 2021 by Tom Nardi 46 Comments

The modern consumer is not overly concerned with their phone conversations being monitored. For one thing, Google and Amazon have done a tremendous job of conditioning them to believe that electronic gadgets listening to their every word isn’t just acceptable, but a near necessity in the 21st century. After all, if there was a better way to turn on the kitchen light than having a recording of your voice uploaded to Amazon so they can run it through their speech analysis software, somebody would have surely thought of it by now.

But perhaps more importantly, there’s a general understanding that the nature of telephony has changed to the point that few outside of three letter agencies can realistically intercept a phone call. Sure we’ve seen the occasional spoofed GSM network pop up at hacker cons, and there’s a troubling number of StingRays floating around out there, but it’s still a far cry from how things were back when folks still used phones that plugged into the wall. In those days, the neighborhood creep needed little more than a pair of wire strippers to listen in on your every word.

Which is precisely why products like the TA-1356 Tap Trapper were made. It was advertised as being able to scan your home’s phone line to alert you when somebody else might be listening in, whether it was a tape recorder spliced in on the pole or somebody in another room lifting the handset. You just had to clip it onto the phone distribution panel and feed it a fresh battery once and awhile.

If the red light came on, you’d know something had changed since the Tap Trapper was installed and calibrated. But how did this futuristic defender of communications privacy work? Let’s open it up and take a look.

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