Cybersecurity tagged posts

The limit of what artificial intelligence can achieve, known as frontier AI, has crossed another threshold. AI can now plan and execute sophisticated cyber operations with minimal guidance at speeds far beyond human capability.

That, at least, is the evidence from an independent test of Claude Mythos Preview, the latest and most advanced model in the Claude family of AI systems, developed by US tech firm Anthropic. Similar to ChatGPT, these can understand and generate human-like text, analyze information, and solve complex problems.

The finance sector is alarmed. It relies on highly interconnected digital systems that are especially attractive targets for sophisticated cyber-attacks...

Researchers at IMDEA Networks Institute, together with European partners, have found that tire pressure sensors in modern cars can unintentionally expose drivers to tracking. Over a ten-week study, they collected signals from more than 20,000 vehicles, revealing a hidden privacy risk and highlighting the need for stronger security measures in future vehicle sensor systems.

How tire sensors quietly share data
Most modern cars are equipped with a Tire Pressure Monitoring System (TPMS), mandatory since the late 2000s in many countries for their contribution to road safety...

Researchers have found two novel types of attacks that target the conditional branch predictor found in high-end Intel processors, which could be exploited to compromise billions of processors currently in use.

The multi-university and industry research team led by computer scientists at University of California San Diego will present their work at the 2024 ACM ASPLOS Conference that begins tomorrow...

“All things are numbers,” avowed Pythagoras. Today, 25 centuries later, algebra and mathematics are everywhere in our lives, whether we see them or not. The Cambrian-like explosion of artificial intelligence (AI) brought numbers even closer to us all, since technological evolution allows for parallel processing of a vast amounts of operations.

Progressively, operations between scalars (numbers) were parallelized into operations between vectors, and subsequently, matrices. Multiplication between matrices now trends as the most time- and energy-demanding operation of contemporary AI computational systems...