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True single-photon source boosts secure key rates in quantum key distribution systems

Quantum key distribution (QKD), a cryptographic technique rooted in quantum physics principles, has shown significant potential for enhancing the security of communications. This technique enables the transmission of encryption keys using quantum states of photons or other particles, which cannot be copied or measured without altering them, making it significantly harder for malicious parties to intercept conversations between two parties while avoiding detection.

As true single-photon sources (SPS) are difficult to produce, most QKD systems developed to date rely on attenuated light sources that mimic single photons, such as low-intensity . As these laser pulses can also contain no photons or more than one photon, only approximately 37% of pulses employed by the systems can be used to generate secure keys.

Researchers at the University of Science and Technology of China (USTC) were recently able to overcome this limitation of previously proposed QKD systems, using a true SPS (i.e., a system that can emit only one photon on demand). Their newly proposed QKD system, outlined in a paper published in Physical Review Letters, was found to outperform techniques introduced in the past, achieving a substantially higher secure key rate (SKR).

Webinar: Stolen credentials are the new front door to your network

Cybercriminals no longer need zero-day exploits or other vulnerabilities to breach your systems—these days, they just log in.

On July 9th at 2:00 PM ET, BleepingComputer and SC Media will co-host a live webinar with identity security expert Darren Siegel of Specops Software (part of Outpost24), exploring how threat actors are increasingly breaching networks by simply logging in with stolen credentials.

The webinar “Stolen credentials: The New Front Door to Your Network” will unpack the real-world mechanics behind credential-based attacks and how to stop them before damage is done.

Nanofibers yield stronger, tougher carbon fiber composites

Researchers at the U.S. Department of Energy (DOE)’s Oak Ridge National Laboratory (ORNL) have developed an innovative new technique using carbon nanofibers to enhance binding in carbon fiber and other fiber-reinforced polymer composites—an advance likely to improve structural materials for automobiles, airplanes and other applications that require lightweight and strong materials.

The results, published in the journal Advanced Functional Materials, show promise for making products that are stronger and more affordable, opening new options for U.S. manufacturers to use in applications such as energy and national security.

“The challenge of improving adhesion between carbon fibers and the that surrounds them has been a concern in industry for some time, and a lot of research has gone into different approaches,” said Sumit Gupta, the ORNL researcher who led the project. “What we found is that a hybrid technique using to create chemical and mechanical bonding yields excellent results.”

MiniMax-M1 is a new open source model with 1 MILLION TOKEN context and new, hyper efficient reinforcement learning

From a data platform perspective, teams responsible for maintaining efficient, scalable infrastructure can benefit from M1’s support for structured function calling and its compatibility with automated pipelines. Its open-source nature allows teams to tailor performance to their stack without vendor lock-in.

Security leads may also find value in evaluating M1’s potential for secure, on-premises deployment of a high-capability model that doesn’t rely on transmitting sensitive data to third-party endpoints.

Taken together, MiniMax-M1 presents a flexible option for organizations looking to experiment with or scale up advanced AI capabilities while managing costs, staying within operational limits, and avoiding proprietary constraints.

Quantum mechanics provide truly random numbers on demand

Randomness is incredibly useful. People often draw straws, throw dice or flip coins to make fair choices. Random numbers can enable auditors to make completely unbiased selections. Randomness is also key in security; if a password or code is an unguessable string of numbers, it’s harder to crack. Many of our cryptographic systems today use random number generators to produce secure keys.

But how do you know that a random number is truly random?

Classical computer algorithms can only create pseudorandom numbers, and someone with enough knowledge of the algorithm or the system could manipulate it or predict the next number. An expert in sleight of hand could rig a coin flip to guarantee a heads or tails result. Even the most careful coin flips can have bias; with enough study, their outcomes could be predicted.