Artificial intelligence (AI) has been helping humans in IT security operations since the 2010s, analyzing massive amounts of data quickly to detect the signals of malicious behavior. With enterprise cloud environments producing terabytes of data to be analyzed, threat detection at the cloud scale depends on AI. But can that AI be trusted? Or will hidden bias lead to missed threats and data breaches?
Bias in Cloud Security AI Algorithms
Bias can create risks in AI systems used for cloud security. There are steps humans can take to mitigate this hidden threat, but first, it’s helpful to understand what types of bias exist and where they come from.
Threats to Cloud Security from AI Bias
We refer to AI bias as a hidden threat to cloud security because we often don’t know that bias is present unless we specifically look for it — or until it is too late and a data breach has happened. Here are some of the things that can go wrong if we fail to address bias:
Mitigating Bias and Strengthening Cloud Security
While humans are the source of bias in AI security tools, human expertise is essential to building AI that can be trusted for securing the cloud. Here are steps that security leaders, SOC teams, and data scientists can take to mitigate bias, foster trust, and realize the enhanced threat detection and accelerated response that AI offers.
The Takeaway
Given the scale and complexity of enterprise cloud environments, using AI for threat detection and response is essential, whether in-house or outside services. However, you can never replace human intelligence, expertise, and intuition with AI. To avoid AI bias and protect your cloud environments, equip skilled cybersecurity professionals with powerful, scalable AI tools governed by strong policies and human oversight.