Chinese Researchers Use Quantum Computers To Reportedly Crack RSA Encryption, Raising Alarms In Cybersecurity Community

Chinese researchers have successfully used D-Wave‘s quantum annealing systems to break classic encryption RSA, potentially accelerating the timeline for when quantum computers could pose a real threat to widely used cryptographic systems.

What Happened: The research team, led by Wang Chao from Shanghai University, demonstrated that D-Wave’s quantum computers can optimize problem-solving to attack encryption methods such as RSA, reported CSO Online.

Their findings were published in the Chinese Journal of Computers under the title “Quantum Annealing Public Key Cryptographic Attack Algorithm Based on D-Wave Advantage.”

The researchers successfully factored a 22-bit RSA integer using the D-Wave Advantage, showcasing the potential for quantum machines to tackle cryptographic problems. This study marks the first time a real quantum computer has posed a substantial threat to multiple full-scale SPN structured algorithms in use today.

“The advancement of quantum computers can seriously threaten data security and privacy for various enterprises, affecting fundamental principles such as confidentiality, integrity, and authentication,” said Prabhjyot Kaur, a senior analyst at Everest Group.

“The growing threat from quantum computers requires immediate attention to ensure the security of our digital future,” the researchers warned in the paper.

See Also: Apple’s Low-Cost Vision Pro Could Hit The Shelves Next Year — Everything You Need To Know About iPhone Maker’s Plan To Challenge Meta

Why It Matters: This development comes in the wake of other significant cybersecurity events involving China, such as the breach of AT&T and Verizon networks by Chinese hackers, further underscoring the growing cyber threat posed by China.

Earlier in 2023, a cyberattack linked to China exploited vulnerabilities in Microsoft Corp’s cloud security, compromising high-ranking U.S. officials’ accounts.

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This story was generated using Benzinga Neuro and edited by Kaustubh Bagalkote