BT has announced its new epidemiology-based cybersecurity prototype, “Inflame”, which uses deep reinforcement learning to enable companies to automatically detect and respond to cyber-attacks.
Using the spread of viruses in human populations as a model to inform its AI, Inflame is a key component in BT’s recently-announced Eagle-i platform.
To develop the technology, security researchers at the BT Labs built models of enterprise networks, which were used to test numerous scenarios based on differing R rates of cyber-infection.
The 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.
Epidemiological modelling is typically associated with the spread of viruses and diseases amongst human populations, and has been critical in analysing and managing the spread of COVID-19 over the past 20 months.
Using the same principals of epidemiology, BT’s Inflame solution has been developed to understand how computer viruses and cyber-attacks spread across enterprise networks, and how to prevent them from happening.
BT’s chief of technology, Howard Watson, said: “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.”
“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.”