Sari la conținut

Română · beta. Traducerea a fost făcută automat și este încă în curs de revizuire. Citește pagina în engleză

perspectiva aiqbenchComunicații cuantice

analiza aiqbench

The collapse of the SIKE algorithm underscores how frontier AI systems are rapidly accelerating the discovery of obscure mathematical vulnerabilities in post-quantum cryptography, potentially shrinking the security window for critical infrastructure. This development highlights a paradigm shift where AI no longer just assists research but independently solves decades-old problems, directly impacting the timeline for identifying weaknesses in encryption standards before they can be formally adopted.
Sursă care acoperăQuantum Zeitgeist
Ce este aceastaLectura unui model asupra articolului și a acoperirii conexe, scrisă pentru aiqbench. Nu sunt cuvintele publicației.

Quantum-safe algorithms may fail faster with powerful AI tools From SIKE

Quantum Zeitgeist10 min de cititArticolul și perspectiva sunt în engleză.

The SIKE algorithm, a contender for post-quantum cryptography, rapidly collapsed after mathematicians linked it to a 1997 theorem.

A cryptographic algorithm once considered a leading candidate for quantum-resistant encryption fell in just one hour on a standard laptop, not to a quantum computer, but to a mathematical insight from 1997. The Supersonic Multivariates Isogeny Key Encapsulation (SIKE) protocol advanced to the fourth round of evaluation by the National Institute of Standards and Technology before mathematicians Wouter Castryck and Thomas Decru connected its structure to Ernst Kani’s decades-old theorem. This collapse highlights a growing vulnerability, as frontier AI systems now possess the capacity to rapidly explore obscure mathematical connections, potentially shortening the window between overlooked weakness and successful attack, according to security leaders. “Years without a successful attack provide evidence, but they cannot establish that every useful mathematical connection has been explored,” the researchers noted. In May 2026, OpenAI reported that an internal model disproved a longstanding conjecture associated with Erdős’s planar unit-distance problem, first posed in 1946. The model applied sophisticated algebraic number theory to a seemingly elementary geometry question, a transfer of ideas between fields that produced a major result. This month, OpenAI announced an AI-generated solution to the Navier-Stokes existence and smoothness problem, unresolved for roughly 90 years, and released…

Extras afișat conform termenilor RSS ai publicației · 194 cuvinte · textul integral și figurile sunt pe site-ul publicației

Subiecte conexe