AI Penetration Testing
Argus Ai RED
We anticipate the future
At Argus AI Red, you'll find a partner dedicated to helping you leverage AI technology to its fullest potential, driving growth and innovation in your organization.
Information security
Argus RED
Artificial Intelligence (AI) has the potential to revolutionize many industries and change the way we live and work. However, as AI becomes more advanced, so too do the challenges it faces. One of the most significant of these is Adversarial Machine Learning (AML).
The process of AML involves feeding an AI system input data that is designed to trick it into making an incorrect decision. This is often done by adding small, carefully crafted perturbations to the input data that are not noticeable to humans, but cause the AI system to misbehave.
AML is a growing concern in the AI community, as it refers to the ability of attackers to manipulate AI systems and cause them to make incorrect decisions. This can have serious consequences, such as misclassifying a dangerous object as benign or making a false fraud detection.
Who? Why? How?
Understanding the threat
To defend against AML, it is crucial to understand the Who/Why/How of the threat in order to take the right steps to keep your organization safe. The development of AI systems that are robust and able to resist adversarial attacks is paramount to long term business sucess. This can be done by a multitude of measures fine-tuned to the threat scenario specific to your oganization.
AML is a growing concern in the AI community, as it refers to the ability of attackers to manipulate AI systems and cause them to make incorrect decisions. This can have serious consequences, such as misclassifying a dangerous object as benign or making a false fraud detection.
AML-Methods
Understanding the model
At Argus AI we spent a lot of our time by focusing on the “How” of the threat. How can algorithms be broken, tricked, and manipulated and what can be gained from these insights for the further development of machine learning models. Understanding the model and the underlying architecture creates to the ability to anticipate attack strategies and employ them proactively to improve the robustness of the organization. Some of the approaches employed by Argus AI include.
