Artificial intelligence (AI), one of the technology industry’s most exciting and most hyped advancements, is being used to create cyberattacks that target businesses of all sizes and in all industries.
This may feel like a betrayal – after all, businesses are starting to see significant benefits from using AI and its subset, machine learning (ML) to automate and streamline business processes and inform decision-making.
However, it’s essential for business decision-makers to understand that the very benefits AI and ML provide to organisations are also available to unscrupulous actors, including cybercriminals.
These technologies are helping cybercriminals launch attacks faster and more successfully.
They are delivering economies of scale that would never have been possible if cybercriminals were manually launching their attacks. And, they’re exposing new areas of risk for organisations, including those that have substantial security measures in place already.
The risks come from three key challenges facing security teams:
- Increasingly sophisticated attacks are harder to detect
Because cybercriminals are using advanced technology to launch automated attacks, these attacks move faster than traditional threats and are harder to detect and remediate.
- The attack surface is expanding
Digital transformation is essential for survival and competitiveness but organisations need to accompany any expansion of digital networks and systems with purpose-built security. The more cloud-based applications and connected devices, a company relies on, the greater the attack surface for cybercriminals. This can stretch cybersecurity resources thin
- The skills shortage means teams are overwhelmed
The ongoing cyberskills gap means that security teams are often overwhelmed and spent too much of their team remediating serious attacks and not enough time proactively building defences.
The only viable option for businesses is, therefore, to fight fire with fire. This means adopting AI and ML-powered security solutions that can beat sophisticated hackers at their own game.
Manually-managed cybersecurity systems are no longer sufficient to keep up with the volume and velocity of attacks. AI-driven threat intelligence is required to detect threats faster and more accurately. These solutions can use ML to identify, classify, and investigate sophisticated threats in a tiny fraction of the time that humans would take to do the same thing.
Self-learning deep neural networks can remove the burden of manual, time-consuming security tasks from teams and increase the strength of an organisation’s protection. Meanwhile, security teams are free to focus on more proactive and innovative work, further contributing to a hardened security posture.
With an AI-powered solution, organisations can be confident that, even with a small team, their security defences are strong. The team can spend less time on manual identification and classification tasks, focusing on accelerating their threat response to keep up with the threats.
The ideal solution will also draw on threat intelligence gathered by additional sources, preferably globally. This will make it easier for the team to ensure that potential gaps and vulnerabilities are addressed before cyber-attackers can exploit them.
Automating cyberbreach protection is the only viable way forward for organisations as they face an evolving threat landscape in which the cybercriminals are equipped with state-of-the-art technology to increase their chances of a successful attack.
To prevent automated attacks, organisations need to deploy automated solutions delivered by a reputable cybersecurity provider.
Ilan Rubin, managing director of Fortinet distributor, Wavelink
