Why Security Shouldn’t Be Overlooked When Implementing Artificial Intelligence Solutions
Many researchers have proven—and continue to prove—that AI applications can be easily fooled and hacked, causing them to make incorrect decisions or fail in ways that benefit attackers. Various attack methods have been developed that compromise the confidentiality, integrity, and availability of systems using AI solutions.
These AI-specific attacks are fundamentally different from traditional cyberattacks. Unlike traditional systems, the algorithms behind AI are inherently vulnerable and cannot be easily patched or replaced. Whereas bugs in traditional code can often be resolved with updates, the complexity of AI systems makes mitigation far more difficult.
Moreover, while many industries have compliance programs in place to protect against standard cybersecurity threats, there are still no clear, standardized guidelines for implementing secure AI solutions that defend against AI-specific vulnerabilities.
Why This Publication About AI Applications?
Inspired by these concerns, this article explores some of the key attack vectors targeting AI applications. We also share best practices that businesses can adopt to protect their AI systems from malicious actors.
About the Author
Samraa Alzubi is a Cyber Security Consultant at Approach. She holds a Master’s degree in Cyber Security from ULB University. Her recent thesis focused on attacks against machine learning, where she proposed a novel black-box adversarial reprogramming attack targeting image classifiers.
