The tech giant has revealed that the ability to lock Incognito sessions in Chrome behind biometric authentication on mobile devices is currently making its way to Android users after debuting on iOS. When this feature is turned on, users will have to confirm their identity via facial or fingerprint authentication every time they return to the Incognito tab after exiting Chrome or switching to another app.

With online risks on the rise, Chrome’s “privacy by design” approach means users can complete an online purchase, get work done or pay a bill with a little more peace of mind.

Built-in features like Google Password Manager make logging in safe across all devices and help detect compromised passwords. Along with providing strong default protections, the company makes privacy controls easy to find, understand, and use in Chrome. While many of these features are widely known, Chrome includes many privacy settings and security features that may be new to most users.

Locked Incognito sessions first became available on Android in 2022 – more than a year after Google began testing them for iPhone and iPad – but as an experimental feature that must be enabled via a flag.

Based on 9to5Google’s experience using it on Android last year, this feature will show a gray screen with the Incognito logo in the center when you return to a tab protected by the privacy feature. You’ll then need to tap “Unlock Incognito” to open biometric authentication or choose to verify your identity with a PIN.

However, no one said that the company has put an end to the project.

On February 8, 2022 Fairplay sent a letter to Meta’s CEO Mark Zuckerberg by more than 75 religious leaders who insist on a complete termination of Instagram’s kids version project. The letter says:

“A pause is not enough. Instagram poses a danger to young children, as your own research indicates. Plans for Instagram must end permanently.”

Children’s safety, especially on the internet, is a priority for every parent. Maybe that’s the reason for an Instagram post, published in March 2021 which provides more information for parents about their kids’ privacy and security in the app.

According to the publication the company is already trying to figure out how to verify childrens’ actual age as there are many kids who lie about it. The company revealed that it works on AI technology and machine learning which are supposed to keep teens safe and apply new age-appropriate features.

“Being able to reach Chinese consumers online has never been more important, as wealthy Chinese consumers travel less and spend more on their home turf, according to research from consultancy firm Bain. This will have a profound impact on the luxury retail sector, for example, with China set to become the world’s biggest luxury market by 2025.

Loqate’s China Premium Data Set is integrated into Loqate’s existing solutions, Capture and Verify, ensuring Loqate can now provide scalable address data capture, verification and enrichment solutions to businesses looking to reach the Chinese consumer. With more accurate address data on Chinese consumers, businesses will now be able to:

• Reduce failed deliveries: Verifying addresses up-front can save businesses wasted costs in failed delivery attempts and chargebacks. Loqate customers have reduced failed delivery rates by up to 70%;
• Enhance the customer experience: Loqate’s Address Capture will auto-populate any Chinese address fields in three keystrokes or less, reducing data entry time by more than 78% and errors by 20%;
• Meet regional compliance requirements: Improved address-level data can help companies better verify shoppers, while also helping ensure Know Your Customer (KYC), anti-fraud regulations and address data quality requirements in region are me;

Matt Navara, a social media consultant, spotted that Instagram has already started using video selfie identity verification. As we all know, Facebook, recently re-named as Meta, is Instagram’s owner which now promises that those video selfies will never be visible on the platform and they will be deleted in about 30 days. Biometric data will not be used by the company’s new face recognition technology. What about all the newly arrived users? Well, they will be asked to shoot a short video selfie which will be used only by the company’s AI algorithms and that’s only for proving that you are a real person.

A while ago Instagram started working on the new feature. In August last year, this security check was rolled out but it turned out to have some technical issues which are obviously solved now because the feature is broadly available.

We need to specify that right now the video selfie recognition is acquirable only for newly created accounts. For all existing profiles, this feature is not pinpointed yet.

Some dating applications such as Bumble or Tinder have used a photo verification system that requires users to upload selfies but from a different angle. Instagram’s video selfie verification, however, appears to be more reliable and it won’t be easy to rib for all the scammers out there.

Researchers at MIT, Boston University, and Maynooth University in Ireland have now created the first silicon chip that is able to decode any code, regardless of its structure, with maximum accuracy, using a universal decoding algorithm called Guessing Random Additive Noise Decoding (GRAND). By eliminating the need for multiple, computationally complex decoders, GRAND enables increased efficiency that could have applications in augmented and virtual reality, gaming, 5G networks, and connected devices that rely on processing a high volume of data with minimal delay.

Focus on noise

One way to think of these codes is as redundant hashes added to the end of the original data. The rules for the creation of that hash are stored in a specific codebook.

As the encoded data travels over a network, they are affected by noise or energy that disrupts the signal, which is often generated by other electronic devices. When that coded data and the noise that affected them arrive at their destination, the decoding algorithm consults its codebook and uses the structure of the hash to guess what the stored information is.

Instead, GRAND works by guessing the noise that affected the message and uses the noise pattern to deduce the original information. GRAND generates a series of noise sequences in the order they are likely to occur, subtracts them from the received data, and checks to see if the resulting codeword is in a codebook. While the noise appears random in nature, it has a probabilistic structure that allows the algorithm to guess what it might be. Médard says:

“In a way, it is similar to troubleshooting. If someone brings their car into the shop, the mechanic doesn’t start by mapping the entire car to blueprints. Instead, they start by asking, ‘What is the most likely thing to go wrong?’ Maybe it just needs gas. If that doesn’t work, what’s next? Maybe the battery is dead?”

Novel hardware

The GRAND chip uses a three-tiered structure, starting with the simplest possible solutions in the first stage and working up to longer and more complex noise patterns in the two subsequent stages. Each stage operates independently, which increases the throughput of the system and saves power.

The device is also designed to switch seamlessly between two codebooks. It contains two static random-access memory chips, one that can crack codewords, while the other loads a new codebook and then switches to decoding without any downtime.

The researchers tested the GRAND chip and found it could effectively decode any moderate redundancy code up to 128 bits in length, with only about a microsecond of latency. Médard and her collaborators had previously demonstrated the success of the algorithm, but this new work showcases the effectiveness and efficiency of GRAND in hardware for the first time.

Developing hardware for the novel decoding algorithm required the researchers to first toss aside their preconceived notions, Médard says.

“We couldn’t go out and reuse things that had already been done. This was like a complete whiteboard. We had to really think about every single component from scratch. It was a journey of reconsideration. And I think when we do our next chip, there will be things with this first chip that we’ll realize we did out of habit or assumption that we can do better,”

A chip for the future

Since GRAND only uses codebooks for verification, the chip not only works with legacy codes but could also be used with codes that haven’t even been introduced yet.

In the lead-up to 5G implementation, regulators and communications companies struggled to find consensus as to which codes should be used in the new network. Regulators ultimately chose to use two types of traditional codes for 5G infrastructure in different situations. Using GRAND could eliminate the need for that rigid standardization in the future, Médard says.

The GRAND chip could even open the field of coding to a wave of innovation. She also commented:

“For reasons, I’m not quite sure of, people approach coding with awe, like it is black magic. The process is mathematically nasty, so people just use codes that already exist. I’m hoping this will recast the discussion so it is not so standards-oriented, enabling people to use codes that already exist and create new codes.”

Moving forward, Médard and her collaborators plan to tackle the problem of soft detection with a retooled version of the GRAND chip. In soft detection, the received data are less precise. They also plan to test the ability of GRAND to crack longer, more complex codes and adjust the structure of the silicon chip to improve its energy efficiency.

The neural decoder architecture. Photo Credits: Torlai et al. ©2017 American Physical Society