Security is an ongoing process that needs constant awareness and response to changing cyber threats. We know how AI has changed the digital landscape by automating tedious tasks. While we talk about the ethical nature of AI, we have barely scratched the surface of the possible security risks AI could bring to the table.
Since most organizations now use AI/ML applications for their operations (and will continue to do so), cybercriminals are getting one step ahead to breach them. Therefore, it is crucial to know the security challenges linked with AI/ ML applications and how to tackle them.
This whitepaper will educate how AI is going to drastically change the cybersecurity posture. Get the strategies and best practices you need to create robust security measures for AI/ML Applications.
In this Case study, know:
The complete evolution of the cyber threat landscape
Common vulnerabilities found in AI/ML systems
Challenges in securing AI/ML applications today
The techniques involved in AI/ML security testing
How penetration testing is the secret weapon for AI/ML security
