The security of applications is not just a technical issue but a cornerstone of business integrity and continuity.
The aurora borealis, or northern lights, is known for a stunning spectacle of light in the night sky, but this near-Earth manifestation, which is caused by explosive activity on the sun and carried by the solar wind, can also interrupt vital communications and security infrastructure on Earth. Using artificial intelligence, researchers at the University of New Hampshire have categorized and labeled the largest-ever database of aurora images that could help scientists better understand and forecast the disruptive geomagnetic storms.
The research, recently published in the Journal of Geophysical Research: Machine Learning and Computation, developed artificial intelligence and machine learning tools that were able to successfully identify and classify over 706 million images of auroral phenomena in NASA’s Time History of Events and Macroscale Interactions during Substorms (THEMIS) data set collected by twin spacecrafts studying the space environment around Earth. THEMIS provides images of the night sky every three seconds from sunset to sunrise from 23 different stations across North America.
“The massive dataset is a valuable resource that can help researchers understand how the solar wind interacts with the Earth’s magnetosphere, the protective bubble that shields us from charged particles streaming from the sun,” said Jeremiah Johnson, associate professor of applied engineering and sciences and the study’s lead author. “But until now, its huge size limited how effectively we can use that data.”
On Monday, the United Nations’ International Civil Aviation Organization (ICAO) announced it was investigating what it described as a “reported security incident.”
Established in 1944 as an intergovernmental organization, this United Nations agency works with 193 countries to support the development of mutually recognized technical standards.
“ICAO is actively investigating reports of a potential information security incident allegedly linked to a threat actor known for targeting international organizations,” ICAO said in a statement.
A recent campaign targeting browser extensions illustrates that they are the next frontier in identity attacks. Learn more about these attacks from LayerX Security and how to receive a free extension audit.
Common methods of communicating flood risk may create a false sense of security, leading to increased development in areas threatened by flooding.
This phenomenon, called the “safe development paradox,” is described in a new paper from North Carolina State University. Lead author Georgina Sanchez, a research scholar in NC State’s Center for Geospatial Analytics, said this may be an unintended byproduct of how the Federal Emergency Management Agency classifies areas based on their probability of dangerous flooding.
The findings are published in the journal PLOS ONE.
Discover the groundbreaking world of quantum teleportation! Learn how scientists are revolutionizing data transfer using quantum entanglement, enabling secure, instant communication over vast distances. From integrating quantum signals into everyday internet cables to overcoming challenges like noise, this technology is reshaping our future. Explore the possibilities of a quantum internet and its role in computing and security. Watch our full video for an engaging dive into how quantum teleportation works and why it’s a game-changer for technology. Don’t miss out!
Paper link: https://journals.aps.org/prl/abstract…
Continue reading “Quantum Teleportation Made Possible! Scientists Achieved Near-Perfect Results” »
Researchers used electromagnetic signals to steal and replicate AI models from a Google Edge TPU with 99.91% accuracy, exposing significant vulnerabilities in AI systems and calling for urgent protective measures.
Researchers have shown that it’s possible to steal an artificial intelligence (AI) model without directly hacking the device it runs on. This innovative technique requires no prior knowledge of the software or architecture supporting the AI, making it a significant advancement in model extraction methods.
“AI models are valuable, we don’t want people to steal them,” says Aydin Aysu, co-author of a paper on the work and an associate professor of electrical and computer engineering at North Carolina State University. “Building a model is expensive and requires significant computing sources. But just as importantly, when a model is leaked, or stolen, the model also becomes more vulnerable to attacks – because third parties can study the model and identify any weaknesses.”
By November 2024, 15 U.S. states had established regulations on ghost guns, though exact requirements vary. The rules typically require a serial number, background checks for firearm component purchases and reporting to authorities that a person is producing 3D-printed guns.
For instance, in New Jersey, a 2019 law mandates that all ghost guns have a serial number and be registered. Under current New York law, possession or distribution of a 3D-printed gun is classified as a misdemeanor. However, a proposed law seeks to elevate the manufacturing of firearms using 3D-printing technology to a felony offense.
The research team, led by physics professor Nuh Gedik, concentrated on a material called FePS₃, a type of antiferromagnet that transitions to a non-magnetic state at around −247°F. They hypothesized that precisely exciting the vibrations of FePS₃’s atoms with lasers could disrupt its typical antiferromagnetic alignment and induce a new magnetic state.
In conventional magnets (ferromagnets), all atomic spins align in the same direction, making their magnetic field easy to control. In contrast, antiferromagnets have a more complex up-down-up-down spin pattern that cancels out, resulting in zero net magnetization. While this property makes antiferromagnets highly resistant to stray magnetic influences – an advantage for secure data storage – it also creates challenges in intentionally switching them between “0” and “1” states for computing.
Gedik’s innovative laser-driven approach seeks to overcome this obstacle, potentially unlocking antiferromagnets for future high-performance memory and computational technologies.
Run by the team at orchestration, AI, and automation platform Tines, the Tines library contains pre-built workflows shared by real security practitioners from across the community, all of which are free to import and deploy via the Community Edition of the platform.
Their bi-annual “You Did What with Tines?!” competition highlights some of the most interesting workflows submitted by their users, many of which demonstrate practical applications of large language models (LLMs) to address complex challenges in security operations.
One recent winner is a workflow designed to automate CrowdStrike RFM reporting. Developed by Tom Power, a security analyst at The University of British Columbia, it uses orchestration, AI and automation to reduce the time spent on manual reporting.
