AI & CYBERSECURITYCan Quantum Computing Protect AI from Cyberattacks?

Published 30 May 2023

AI algorithms are everywhere. They underpin nearly all autonomous and robotic systems deployed in security applications. This includes facial recognition, biometrics, drones and autonomous vehicles used in combat surveillance and military targeting applications. Can we prevent malicious attacks and improve the cybersecurity of algorithms powered by artificial intelligence (AI)? Quantum machine learning may hold the key.

AI algorithms are everywhere. They underpin nearly all autonomous and robotic systems deployed in security applications. This includes facial recognition, biometrics, drones and autonomous vehicles used in combat surveillance and military targeting applications.

Machine learning and AI algorithms are trained to classify and identify image features, like the features of our faces in facial recognition. But the data underpinning these algorithms can be vulnerable to cyberattacks. Subtle manipulation of image data by removing only a few pixels – invisible to the human eye – can result in incorrect predictions and even pose serious security threats.

Is Quantum Computing the Answer?
Research funded by the Australian Army through the Quantum Technology Challenge (QTC) and published in Nature Machine Intelligence by researchers from CSIRO’s Data61 and University of Melbourne reveals that advances in quantum technology may hold the key to protecting AI algorithms from cyberattacks.

Dr. Muhammad Usman is lead senior author of the paper and team leader of Quantum Systems at CSIRO’s Data61. He described the potential of integrating quantum computing with AI as a game-changing technology.

“The hunt for quantum advantage is heating up,” Usman said.

“Quantum machine learning is one of the front-runner applications of quantum computing. By integrating quantum with machine learning we can speed up AI training and enhance robustness against cyberattacks.”

What’s All the Fuss About Quantum Computing?
Worldwide, interest in quantum is surging. On 3 May 2023, the Australian Government launched the National Quantum Strategy, with a vision for Australia to be recognised as a leader in the global quantum industry by 2030. The Strategy stated that quantum technologies are expected to create an Australian quantum industry worth $6B by 2045.

We have established our ambitious Quantum Future Science Platform to develop these world-leading technologies and launched a new program that will soon be accepting students to become the next generation of quantum technology specialists.

How It Works
Quantum computing is a new field of computing. It stores information as ‘qubits’ rather than as binary ‘bits’. While a single bit can store or process information in the form of ‘0’ and ‘1’ on a conventional computer, a quantum qubit can be placed in a ‘0’ or ‘1’ state or represent both states simultaneously. This is called superposition.

A second special property of quantum mechanics is known as entanglement, which allows qubits to interact with each other at long distances without any physical connection. Einstein famously called it “spooky action at a distance”.

Calculations or code-breaking functions that may take a conventional computer thousands of years could take just hours on a quantum computer.

The Quantum Advantage
As more industries from transport to defense and banking incorporate AI, security will be paramount. Quantum could help ensure AI-powered technologies are resilient to attacks and may provide a competitive advantage for early adopters.

But Usman cautions that quantum computers could also be used to generate very powerful cyberattacks.

This is a very serious cybersecurity threat. However, rapid advancements in quantum hardware and software and more sophisticated error mitigation strategies are coming. Quantum computers of the near future should enable quantum machine learning algorithms to start demonstrating advantages,” Usman said.

“This is a very exciting research direction which could have significant socio-economic and security implications for Australia.”

The paper ‘Towards quantum enhanced adversarial robustness in machine learning’ was published today in Nature Machine Intelligence.

Alice Trend is Artificial Intelligence Communication and Engagement Lead at CSIRO. Muhammad Usman is Team Leader Quantum Systems with CSIRO. The article was first published on the CSIRO website.