Lifeboat Foundation

People in movies are often quick to resort to sawing off someone’s hand to get past a fingerprint scanner. A report from the Kraken Security Labs Team shows that it would be much easier—and less gruesome—to recreate someone’s fingerprint using a little bit of off-the-shelf wood glue.

Kraken notes that biometric security has become increasingly common as smartphone, tablet, and laptop manufacturers have incorporated fingerprint scanners into their products. These scanners offer a convenient way to access those devices without entering a password.

The report says a fingerprint scanner can be “hacked” by using a picture of the target’s fingerprint, creating a negative in Photoshop, printing the resulting image, and then putting some wood glue on top of the imitated fingerprint so it can be used to trick many commercial scanners.

Imagine that your team is meeting to decide whether to continue an expensive marketing campaign. After a few minutes, it becomes clear that nobody has the metrics on-hand to make the decision. You chime in with a solution and ask Amazon’s virtual assistant Alexa to back you up with information: “Alexa, how many users did we convert to customers last month with Campaign A?” and Alexa responds with the answer. You just amplified your team’s intelligence with AI. But this is just the tip of the iceberg.

Intelligence amplification is the use of technology to augment human intelligence. And a paradigm shift is on the horizon, where new devices will offer less intrusive, more intuitive ways to amplify our intelligence.

Hearables, or wireless in-ear computational earpieces, are an example of intelligence amplification devices that have been adopted recently and rapidly. An example is Apple’s AirPods, which are smart earbuds that connect to Apple devices and integrate with Siri via voice commands. Apple has also filed a patent for earbuds equipped with biometric sensors that could record data such as a user’s temperature, heart rate, and movement. Similarly, Google’s Pixel Buds give users direct access to the Google Assistant and its powerful knowledge graph. Google Assistant seamlessly connects users to information stored in Google platforms, like email and calendar management. Google Assistant also provides users with highly-personalized recommendations, helps automate personal communication, and offloads monotonous tasks like setting timers, managing lists, and controlling IoT devices.

Forget about Mark Zuckerberg, Facebook and all the talk about a metaverse. The real future will be a world that is convenient and scary and fantastical — at least according to futurologists. As this year ends, here’s a glimpse at what life might be like … one day.

Facial recognition is already common for phones, but “In 30 years it’s quite possible that you will not use a key or even a credit card. You’ll use your face or iris to make purchases and open locks. Recognition will be that good,” said Martin Ford, author of “Rule of the Robots: How Artificial Intelligence will Transform Everything.”

“The scary thing, though, will be if someone hacks your biometric data. Right now you can call the bank to change your pin or cancel a credit card. But you can’t cancel your biometrics.”

Scientists with the help of next gen Artificial Intelligence managed to create the smallest and most efficient camera in the world. A specialist medical camera that measures just under a nanometer has just entered the Guinness Book of Records. The size of the grain of sand, it is the camera’s tiny sensor that is actually being entered into the world-famous record book, for being the smallest commercially available image sensor.
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TIMESTAMPS:
00:00 A new leap in Material Science.
00:57 How this new technology works.
03:45 Artificial Intelligence and Material Science.
06:00 The Privacy Concerns of Tiny Cameras.
07:45 Last Words.
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#ai #camera #technology

Facebook plans to shut down its decade-old facial recognition system this month, deleting the face scan data of more than one billion users and effectively eliminating a feature that has fueled privacy concerns, government investigations, a class-action lawsuit and regulatory woes.

Jerome Pesenti, vice president of artificial intelligence at Meta, Facebook’s newly named parent company, said in a blog post on Tuesday that the social network was making the change because of “many concerns about the place of facial recognition technology in society.” He added that the company still saw the software as a powerful tool, but “every new technology brings with it potential for both benefit and concern, and we want to find the right balance.”

The decision shutters a feature that was introduced in December 2010 so that Facebook users could save time. The facial-recognition software automatically identified people who appeared in users’ digital photo albums and suggested users “tag” them all with a click, linking their accounts to the images. Facebook now has built one of the largest repositories of digital photos in the world, partly thanks to this software.

In a wide-ranging interview at the WSJ Tech Live conference that touched on topics like the future of remote work, AI innovation, employee activism and even misinformation on YouTube, Alphabet CEO Sundar Pichai also shared his thoughts on the state of tech innovation in the U.S. and the need for new regulations. Specifically, Pichai argued for the creation of a federal privacy standard in the U.S., similar to the GDPR in Europe. He also suggested it was important for the U.S. to stay ahead in areas like AI, quantum computing and cybersecurity, particularly as China’s tech ecosystem further separates itself from Western markets.

In recent months, China has been undergoing a tech crackdown, which has included a number of new regulations designed to combat tech monopolies, limit customer data collection and create new rules around data security, among other things. Although many major U.S. tech companies, Google included, don’t provide their core services in China, some who did are now exiting — like Microsoft, which just this month announced its plan to pull LinkedIn from the Chinese market.

Pichai said this sort of decoupling of Western tech from China may become more common.

Passengers on the Moscow metro can now pay for their commute using facial recognition technology. The system is called “Face Pay” — and connects passengers’ biometric data with their credit cards.
It’s been rolled out across all 241 stations in the Russian capital — but privacy activists are sounding the alarm.

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This week, The European Parliament, the body responsible for adopting European Union (EU) legislation, passed a non-binding resolution calling for a ban on law enforcement use of facial recognition technology in public places. The resolution, which also proposes a moratorium on the deployment of predictive policing software, would restrict the use of remote biometric identification unless it’s to fight “serious” crime, such as kidnapping and terrorism.

The approach stands in contrast to that of U.S. agencies, which continue to embrace facial recognition even in light of studies showing the potential for ethnic, racial, and gender bias. A recent report from the U.S. Government Accountability Office found that 10 branches including the Departments of Agriculture, Commerce, Defense, and Homeland Security plan to expand their use of facial recognition between 2020 and 2023 as they implement as many as 17 different facial recognition systems.

Commercial face-analyzing systems have been critiqued by scholars and activists alike throughout the past decade, if not longer. The technology and techniques — everything from sepia-tinged film to low-contrast digital cameras — often favor lighter skin, encoding racial bias in algorithms. Indeed, independent benchmarks of vendors’ systems by the Gender Shades project and others have revealed that facial recognition technologies are susceptible to a range of prejudices exacerbated by misuse in the field. For example, a report from Georgetown Law’s Center on Privacy and Technology details how police feed facial recognition software flawed data, including composite sketches and pictures of celebrities who share physical features with suspects.

Circa 2019

Crime causes significant damage to the society and property. Different kinds of physical or direct methods are devised by the law and order department to spot out the criminals involved in the crime. This techniques will explore the evidences at crime site. For instance if it finds a fingerprint then the system will capture and send it to forensic department for fingerprint matching, which can be later used for identifying the suspects or criminals by investigations etc. Yet, it is a huge challenge for them to find the criminal due to less or no evidence and incorrect information, which can change the direction of investigation to the end. This paper proposes a data analysis approach to help the police department by giving them first-hand information about the suspects. It automates the manual process for finding criminal and future crime spot by using various techniques such as pattern matching, biometric and crime analytics. Based on the availability of information, the system is able to produce the expected accuracy.