Securing the Healthcare AI Frontier: Safeguarding SaMDs and GenAI Ecosystems with AI Cybersecurity

As AI becomes increasingly integrated into healthcare systems, prioritizing AI cybersecurity in healthcare is paramount to ensure comprehensive risk management.

How can healthcare organizations protect their valuable data from threats and attacks? How can they lead the AI revolution in SaMDs and medical systems?

The security risks of AI-driven healthcare systems are always on the minds of healthcare professionals and those who handle patient safety and healthcare accessibility. Awareness of solutions is imperative to safeguard against malicious attacks and identify and fortify systems against them preemptively.

In 'Securing Healthcare AI Frontier,' AIShield experts Mukul Dongre and Manpreet Dash share emerging threats in healthcare AI adoption. They delve into practical insights on protecting AI-driven SaMDs and Generative AI ecosystems.

This webinar covers:

1. Why AI healthcare systems like AI-enabled SaMDs and GenAI ecosystems are susceptible to risks, and what these risks are

2. The need to safeguard sensitive information from attacks on AI-enabled healthcare systems with a comprehensive solution

3. The features that a solution in AI cybersecurity in healthcare should have to protect against security vulnerabilities via case studies

AI experts at the 2023 Artificial Intelligence True Quality Summit spoke of threats in the dynamic AI landscape. They dove deep into AI cybersecurity in healthcare. The discussion defined AIShield as a product that packs the edge of 40 patents. It also highlighted it as a complete solution recognized by industry analysts and trusted by over 40 organizations.

Today's healthcare sector faces new AI risks that strongly affect patient safety. Using multi-modal data sets makes healthcare perfect for bringing out AI's advantages of efficiency, personalization, and effectiveness. The investments in drug development make AI the harbinger of opportunities to speed up research and clinical trials. This transformation also means risks of security breaches – these translate into patient safety issues, penalties, and device-inoperability fears.

AI algorithms can be prone to manipulation, evasion, and inference attacks. Examples of misdiagnosis, identity theft, and fraud reaffirm this danger. Beyond threats of malicious attacks, healthcare organizations bear the imperatives of heavy regulatory compliance. The EU AI Act comes to mind here.

Users, builders, platforms – everyone has stakes, responsibilities, and roles in this AI world. Many enterprises are, however, not confident and equipped to deal with severe AI risks and implications.

On the solution side for AI risk management, AIShield is a one-stop security platform. The API-based enterprise-ready platform gives enterprises the confidence they seek.

The solution packs protection against adversarial AI attacks, model functionality checks, validation measures, and security and vulnerability assessments. Plus, it helps enterprises spot loopholes, fix them, and retrain models against attack vectors.

AIShield is a razor-sharp, comprehensive, and proactive AI ML security solution for enterprises. Real-time alerts and advanced telemetry make it powerful for current scenarios. In a case study about using a chest model- x-ray scans, AIShield proved its purpose. It helped the user with intelligent risk assessment tests and vulnerability checks, significantly boosting detection accuracy.

We need to be aware of Generative AI in the security context. Generative AI is bringing speed and efficiency to many processes. Enterprises that use GenAI applications require adequate guardrails.

AI ML security solutions like AIShield are necessary in contemporary, AI-enabled healthcare. Everyone, from builders to adopters, can gain an edge by being prepared and precise about AI risks through effective AI risk management with AIShield.

Watch the video