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).

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.

 

 

 

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.

 

 

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.

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:

These are just a few of the methodologies employed by Argus AI for adversarial machine learning. Each has its own strengths and weaknesses, and the best approach for a given problem will depend on the specifics of the problem and the data being used.

At Argus AI, we are at the forefront of research and development in the field of AML. Our team of experts has a deep understanding of the challenges posed by AML and how to defend against them. Whether you are looking to improve the security and reliability of your AI systems, or you are interested in exploring new ways to use AI to tackle challenging problems, we are here to help.

If you are interested in learning more about Adversarial Machine Learning and how it can impact your business, please reach out to us. Our team of experts would be happy to answer any questions you may have and provide you with the guidance and support you need to succeed.