A simple guide for how to learn AI security
Here are five simple steps to get a firm understanding of the unique security risks of AI systems
AI is everywhere in 2023 which is amazing and terrifying at the same time
Even if you do not buy into the hype, you cannot deny just how big of an impact AI is having on nearly every industry across the world
One area that is going to become huge in the coming years is that of AI security due to the massive adoption that is happening
AI is going to bring new types of security risks that the cybersecurity industry is not ready for
Unfortunately we are still in the infancy of this niche and there is not enough material present for how to learn AI security
For the vast majority of people, AI security translates to using ChatGPT to write some security related prompts !
In this article I want to go over five easy steps you can use to learn AI security and get a running start on this upcoming field
Step 1 : Understand Machine Learning concepts
Machine Learning is the engine that drives most AI implementations and it is essential to learn about it. Understand its core concepts and how it differs from normal applications. I would suggest getting a firm understanding of the below topics:
Supervised and unsupervised learning
Neural networks and deep learning
Reinforcement learning
Feature engineering
Model evaluation and validation
You do not have to become an expert or get into the nitty gritties of the different types of machine learning algorithms but have a firm understanding of the concepts that ML is based around
The reason being that a lot of the attacks on AI seek to exploit these very concepts thus a good foundational knowledge is essential !
Step 2: Learn about biases in AI systems and how to mitigate them
One of most dangerous risks in AI systems is for biases and risks to get introduced within them leading to unfair or discriminatory decisions.
Think about an AI system being used in law enforcement or the medical field that is biased towards a particular ethnicity or race ?!
To become an expert in AI security, you must know how to identify and mitigate these biases. Here’s what to study:
Types of biases (e.g., sampling bias, measurement bias, and algorithmic bias)
Ethical implications of biased AI systems
Techniques for mitigating biases (e.g., re-sampling, re-weighting, and adversarial training)
Step 3: Learn about AI unique attacks like membership inference and data poisoning
The third step is learning about AI-specific attacks. As AI systems become more prevalent, they become targets for malicious actors.
To protect these systems, you need to understand the various attacks and their implications. Some common attacks include:
Adversarial examples
Data poisoning
Model inversion and extraction
Membership inference attacks
I have written quite a bit on this topic which you can check out here
Step 4: Learn how to create an AI risk management framework
AI security does not exist in a vacuum and needs a proper framework to be implemented to function properly. Find out about the new regulations which are being introduced to regulate AI and what sort of controls they require.
Learn these topics:
AI governance frameworks and best practices
AI risk assessment methodologies
Compliance with relevant laws and regulations
Incident response and recovery plans for AI systems
Check out this article of mine
Step 5: Learn about AI specific security controls
Now that you have a firm understanding of the basics of AI, you can start to learn about AI specific security controls
Most cybersecurity professionals make the mistake of jumping to this step directly instead of creating a solid foundation first !
A few of the key topics to learn are:
Data protection (e.g., encryption, anonymization, and access controls)
Secure model training and deployment
Robustness testing and validation
Monitoring and auditing of AI systems
Check out my articles on the same
I hope this gave you a good idea of how vast a field AI security is and how it is not just restricted to ChatGPT ! If you are interested in diving deep into this topic then check out my book on the same.