Lifeboat Foundation

As computer scientists tackle a greater range of problems, their work has grown increasingly interdisciplinary. This year, many of the most significant computer science results also involved other scientists and mathematicians. Perhaps the most practical involved the cryptographic questions underlying the security of the internet, which tend to be complicated mathematical problems. One such problem — the product of two elliptic curves and their relation to an abelian surface — ended up bringing down a promising new cryptography scheme that was thought to be strong enough to withstand an attack from a quantum computer. And a different set of mathematical relationships, in the form of one-way functions, will tell cryptographers if truly secure codes are even possible.

Computer science, and quantum computing in particular, also heavily overlaps with physics. In one of the biggest developments in theoretical computer science this year, researchers posted a proof of the NLTS conjecture, which (among other things) states that a ghostly connection between particles known as quantum entanglement is not as delicate as physicists once imagined. This has implications not just for our understanding of the physical world, but also for the myriad cryptographic possibilities that entanglement makes possible.

China’s ByteDance is using data from TikTok to track journalists and this is now raising eyebrows. There is growing fears that security concerns over TikTok might actually be true. The Chinese ByteDance wants to know which of its employees are speaking to the media.

#china #tiktok #bytedance.

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Giving children the nasal flu vaccine may help protect them against strep A, according to analysis by the UK Health Security Agency.

UKHSA pilot scheme shows strep A infections lower in areas where nasal vaccine offered to all young children.

Alexandra Topping

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Face recognition tools are computational models that can identify specific people in images, as well as CCTV or video footage. These tools are already being used in a wide range of real-world settings, for instance aiding law enforcement and border control agents in their criminal investigations and surveillance efforts, and for authentication and biometric applications. While most existing models perform remarkably well, there may still be much room for improvement.

Researchers at Queen Mary University of London have recently created a new and promising architecture for face recognition. This architecture, presented in a paper pre-published on arXiv, is based on a strategy to extract facial features from images that differs from most of those proposed so far.

“Holistic methods using convolutional neural networks (CNNs) and margin-based losses have dominated research on face recognition,” Zhonglin Sun and Georgios Tzimiropoulos, the two researchers who carried out the study, told TechXplore.

Check out all the on-demand sessions from the Intelligent Security Summit here.

Simulation can help engineers overcome these challenges. Rather than tweaking the AI model’s architecture and parameters, it has been shown that time spent improving the training data can often yield more extensive improvements in accuracy.

Check out all the on-demand sessions from the Intelligent Security Summit here.

The adoption of a password-free future is hyped by some of the biggest tech companies, with Apple, Google, and Microsoft committing to support the FIDO standard this past May. Along with the Digital ID Bill reintroduced to Congress this past July, we’re poised to take a giant leap away from the password to a seemingly more secure digital future. But as we approach a post-password world, we still have a long way to go in ensuring the security of our digital lives.

As companies continue developing solutions to bridge us to a passwordless world, many have prioritized convenience over security. Methods of two-factor authentication (2FA) and multi-factor authentication (MFA) such as SMS or email verification — or even the use of biometrics — have emerged as leading alternatives to the traditional username/password. But here’s the catch: Most of these companies are validating devices alone and aren’t properly leveraging this technology, leaving the door open for bad actors.

Check out all the on-demand sessions from the Intelligent Security Summit here.

With the arrival of AI-generated art and the proliferation of tools like Midjourney, Stable Diffusion and DALL-E, questions have been rife in circles across the creative industry.

Is this a temporary trend? Or a would-be essential tool in creative communication?

Check out all the on-demand sessions from the Intelligent Security Summit here.

On September 15, 2022, the Ethereum network migrated from a proof-of-work to a proof-of-stake consensus mechanism called the Merge. Apart from reducing energy consumption by 99%, the Merge laid the foundations for building a highly secure and scalable blockchain. However, despite the benefits of the Merge, it also marks a regression in privacy, which is a significant concern for Ethereum users.

Privacy generally takes a backseat to other core blockchain topics such as decentralization and scalability. In fact, blockchain networks’ zeal for data transparency often comes at the cost of compromising individual and enterprise privacy. But without a privacy-focused approach — even one that gives users optional privacy — Ethereum decentralized applications (dapps) will repeat the same mistakes of Web2 applications.

Leading Canada’s Bio-Safety & Security R&D — Dr. Loren Matheson PhD, Defence Research and Development Canada, Department of National Defence.

Dr. Loren Matheson, Ph.D. is a Portfolio Manager at the Center For Security Science, at Defence Research and Development Canada (DRDC — https://www.canada.ca/en/defence-research-development.html), which is a special operating agency of the Department of National Defence, whose purpose is to provide the Canadian Armed Forces, other government departments, and public safety and national security communities with knowledge and technology.

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