- To protect Gen AI systems and solutions,
it is important to understand common attack vectors.
Before we proceed, let's clarify the difference
between Gen AI systems and Gen AI solutions.
While Gen AI solutions refer to the applications
or implementations of generative AI technology
to solve specific problems,
Gen AI systems encompass broader infrastructure,
architecture, and ecosystem.
For the purposes of this course,
we'll use systems and solutions interchangeably
because the attack vectors
span across systems and solutions.
Training data attacks include dataset poisoning
and hyperparameter tempering.
Dataset poisoning is when bad actors inject biased
or malicious data into the training dataset
of a generative AI model.
This can lead to model learning incorrect patterns,
or making biased predictions,
compromising its integrity and reliability.
Attackers could use deepfakes to prompt Gen AI systems
to generate realistic,
but fabricated content such as fake news articles
or videos featuring manipulated political speeches.
Hyperparameter tempering refers
to manipulating hyperparameters,
such as learning rate and batch size
to significantly compromise performance,
functionality, or integrity.
Now let's talk about adversarial attacks
like prompt injection and adversarial examples.
Prompt injection refers to using specific prompts
or questions to trick the system
into generating harmful content,
leaking sensitive information,
or bypassing safety protocols.
Adversarial examples are specifically designed inputs
that cause the solution to produce incorrect outputs.
Other attack vectors include bias amplification,
data breaches, and model stealing and hijacking.
Model stealing attacks aim to reverse engineer
or replicate the generative AI model
by querying it repeatedly and analyzing its responses.
Attackers can then create a copy of the model
without access to the underlying architecture
or training data, posing intellectual property risks.
By proactively addressing these vulnerabilities,
organizations can mitigate the security
and ethical risks associated
with deploying Gen AI solutions.