Lifeboat Foundation

Asteroid Bennu was in the news recently for an astonishing discovery. NASA scientists revealed that the asteroid has a surface that appears similar to plastic balls. The discovery dates back to October 2020, when NASA successfully collected a sample from the asteroid.

During the sampling event, the sampling head of the OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, Security-Regolith Explorer) spacecraft had sunk by 1.6 feet (0.5 meters) into the surface of the asteroid. The space agency found that Bennu’s exterior is made of loosely packed particles that are haphazardly packed together. The spacecraft would have sunk right into the asteroid if it hadn’t fired its thruster to back away after collecting dust and rocks.

Over the past decade, digital cameras have been widely adopted in various aspects of our society, and are being massively used in mobile phones, security surveillance, autonomous vehicles, and facial recognition. Through these cameras, enormous amounts of image data are being generated, which raises growing concerns about privacy protection.

Some existing methods address these concerns by applying algorithms to conceal sensitive information from the acquired images, such as image blurring or encryption. However, such methods still risk exposure of sensitive data because the raw images are already captured before they undergo digital processing to hide or encrypt the sensitive information. Also, the computation of these algorithms requires additional power consumption. Other efforts were also made to seek solutions to this problem by using customized cameras to downgrade the image quality so that identifiable information can be concealed. However, these approaches sacrifice the overall image quality for all the objects of interest, which is undesired, and they are still vulnerable to adversarial attacks to retrieve the sensitive information that is recorded.

A new research paper published in eLight demonstrated a new paradigm to achieve privacy-preserving imaging by building a fundamentally new type of imager designed by AI. In their paper, UCLA researchers, led by Professor Aydogan Ozcan, presented a smart camera design that images only certain types of desired objects, while instantaneously erasing other types of objects from its images without requiring any digital processing.

The quadrupedal robots are well suited for repetitive tasks.

Mankind’s new best friend is coming to the U.S. Space Force.

The Space Force has conducted a demonstration using dog-like quadruped unmanned ground vehicles (Q-UGVs) for security patrols and other repetitive tasks. The demonstration used at least two Vision 60 Q-UGVs, or “robot dogs,” built by Ghost Robotics and took place at Cape Canaveral Space Force Station on July 27 and 28.

Some signed third-party bootloaders for the Unified Extensible Firmware Interface (UEFI) could allow attackers to execute unauthorized code in an early stage of the boot process, before the operating system loads.

Vendor-specific bootloaders used by Windows were found to be vulnerable while the status of almost a dozen others is currently unknown.

Threat actors could exploit the security issue to establish persistence on a target system that cannot be removed by reinstalling the operating system (OS).

Researchers have observed the formation of 2D ice on gold surfaces that were thought to be too hydrophilic and too rough to support this type of ice.

Mobile devices use facial recognition technology to help users quickly and securely unlock their phones, make a financial transaction or access medical records. But facial recognition technologies that employ a specific user-detection method are highly vulnerable to deepfake-based attacks that could lead to significant security concerns for users and applications, according to new research involving the Penn State College of Information Sciences and Technology.

Mobile devices use facial recognition technology to help users quickly and securely unlock their phones, make a financial transaction or access medical records. But facial recognition technologies that employ a specific user-detection method are highly vulnerable to deepfake-based attacks that could lead to significant security concerns for users and applications, according to new research involving the Penn State College of Information Sciences and Technology.

The researchers found that most application programming interfaces that use facial liveness verification—a feature of facial recognition technology that uses computer vision to confirm the presence of a live user—don’t always detect digitally altered photos or videos of individuals made to look like a live version of someone else, also known as deepfakes. Applications that do use these detection measures are also significantly less effective at identifying deepfakes than what the app provider has claimed.

“In recent years we have observed significant development of facial authentication and verification technologies, which have been deployed in many security-critical applications,” said Ting Wang, associate professor of information sciences and technology and one principal investigator on the project. “Meanwhile, we have also seen substantial advances in deepfake technologies, making it fairly easy to synthesize live-looking facial images and video at little cost. We thus ask the interesting question: Is it possible for malicious attackers to misuse deepfakes to fool the facial verification systems?”

Water scarcity is a major global crisis that already affects every continent. Around 1.2 billion people, or almost one-fifth of the world’s population, lack access to safe drinking water. Desalination is the answer to long-term water security, but it’s also expensive, energy-intensive, and often inaccessible to isolated regions. This is why sustainable off-grid desalination systems powered by renewable energy are essential.

But thanks to the innovative microbial desalination cell (MDC) technology that follows a green, low-energy process with electro-active bacteria to desalinate and sterilize seawater, desalination is becoming a viable low-cost solution for water resources in many areas of the world and is putting an end to water scarcity even in isolated regions.

Now, researchers from the EU-funded W20 project have developed an off-grid innovative solution – the world’s first wave-driven desalination system – called Wave2O. The new system can be deployed quickly, operate completely off-grid, and supply large quantities of fresh water at a competitive cost. The technology uses the power of the ocean waves, a consistent and inexhaustible renewable energy source.

Online safety and ethics are serious issues and can adversely affect less experienced users. Researchers have built upon familiar human verification techniques to add an element of discrete learning into the process. This way users can learn about online safety and ethics issues while simultaneously verifying they are human. Trials show that users responded positively to the experience and felt they gained something from these microlearning sessions.

The internet is an integral part of modern living, for work, leisure, shopping, keeping touch with people, and more. It’s hard to imagine that anyone could live in an affluent country, such as Japan, and not use the internet relatively often. Yet despite its ubiquity, the internet is far from risk-free. Issues of safety and security are of great concern, especially for those with less exposure to such things. So a team of researchers from the University of Tokyo including Associate Professor Koji Yatani of the Department for Electrical Engineering and Information Systems set out to help.

Continue reading “Digital security dialogue: Leveraging human verification to educate people about online safety” »

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In a paper distributed via ArXiv, titled “Exploring the Unprecedented Privacy Risks of the Metaverse,” boffins at UC Berkeley in the US and the Technical University of Munich in Germany play-tested an “escape room” virtual reality (VR) game to better understand just how much data a potential attacker could access. Through a 30-person study of VR usage, the researchers – Vivek Nair (UCB), Gonzalo Munilla Garrido (TUM), and Dawn Song (UCB) – created a framework for assessing and analyzing potential privacy threats. They identified more than 25 examples of private data attributes available to potential attackers, some of which would be difficult or impossible to obtain from traditional mobile or web applications. The metaverse that is rapidly becoming a part of our world has long been an essential part of the gaming community. Interaction-based games like Second Life, Pokemon Go, and Minecraft have existed as virtual social interaction platforms. The founder of Second Life, Philip Rosedale, and many other security experts have lately been vocal about Meta’s impact on data privacy. Since the core concept is similar, it is possible to determine the potential data privacy issues apparently within Meta.

There has been a buzz going around the tech market that by the end of 2022, the metaverse can revive the AR/VR device shipments and take it as high as 14.19 million units, compared to 9.86 million in 2021, indicating a year-over-year increase of about 35% to 36%. The AR/VR device market will witness an enormous boom in the market due to component shortages and the difficulty to develop new technologies. The growth momentum will also be driven by the increased demand for remote interactivity stemming from the pandemic. But what will happen when these VR or metaverse headsets start stealing your precious data? Not just headsets but smart glasses too are prime suspect when it comes to privacy concerns.

Continue reading “Metaverse Headsets and Smart Glasses are the Next-gen Data Stealers” »