"Researchers' Approach May Protect Quantum Computers from Attacks"
Quantum computers can solve complex problems significantly faster than classical computers and are expected to improve Artificial Intelligence (AI) applications in devices such as self-driving cars. However, quantum computers are vulnerable to adversarial attacks. A team of researchers from the University of Texas at Dallas and an industry collaborator have developed a method to strengthen the protection of quantum computers against these attacks. Their solution, Quantum Noise Injection for Adversarial Defense (QNAD), addresses attacks aimed at disrupting the ability of AI to make decisions or carry out tasks in quantum computers. This article continues to discuss the team's approach to counteracting the impact of attacks designed to disrupt AI's ability to make decisions or solve tasks in quantum computers.
Submitted by grigby1