BT has developed what it describes as ‘epidemiological AI’ based on the viruses in humans to combat cyber-attacks.

The technology, called ‘Inflame’, uses the spread of viruses in human populations as a model to form its AI. It includes deep reinforcement learning to enable companies to automatically detect and respond to cyber-attacks before they compromise a network.

Epidemiological modelling is typically associated with the spread of viruses and diseases amongst human populations, and has been used to analyse and manage the spread of COVID-19. Using the same principals of epidemiology, BT’s new technology has been developed to understand how computer viruses and cyber-attacks spread across enterprise networks, and how to prevent them from happening.

“We know the risk of cyber-attack is higher than ever and has intensified significantly during the pandemic. Enterprises now need to look to new cybersecurity solutions that can understand the risk and consequence of an attack, and quickly respond before it’s too late,” said Howard Watson, chief technology officer, BT. “Epidemiological testing has played a vital role in curbing the spread of infection during the pandemic, and Inflame uses the same principles to understand how current and future digital viruses spread through networks.

“Inflame will play a key role in how BT’s Eagle-i platform automatically predicts and identifies cyber-attacks before they impact, protecting customers’ operations and reputation.”

To develop the technology, security researchers at the BT Labs in Suffolk, UK, built models of enterprise networks which were used to test numerous scenarios based on differing R rates of cyber-infection.

This testing enabled the research team to understand how these threats can penetrate and compromise a network, and develop optimal automated responses needed to contain and prevent the spread of viruses across them.

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