Industry Perspectives

Explore how AI risk scoring is revolutionizing cybersecurity in healthcare, enhancing threat detection, and optimizing resource management.

Surging breaches and tougher HIPAA/EU rules are forcing healthcare to adopt continuous AI security audits, real-time monitoring, stronger vendor oversight, and blockchain.

With 2025 compliance deadlines approaching, healthcare organizations must address the AI governance talent gap to ensure patient safety and data privacy.

Learn essential practices for safeguarding patient data, reducing breaches, and maintaining compliance in healthcare organizations.

Learn how to conduct effective supply chain security audits in healthcare to protect patient data and ensure compliance.

Assess 5G's impact on healthcare security, highlighting vendor risk, IoT vulnerabilities, zero-trust defenses, and the need for continuous monitoring to protect patients.

Five steps to manage third-party cloud audits in healthcare: set scope, choose auditors, align teams, assess risks, and maintain continuous monitoring.

Avoid five common vendor onboarding security errors in healthcare: poor risk classification, checkbox reviews, weak BAAs, uncontrolled integrations, and no ongoing monitoring.

Explore the top challenges in vendor risk scoring for healthcare and discover strategies to enhance data accuracy, compliance, and security.

Compare nine de-identification solutions for clinical text, structured data, and DICOM imaging, with strengths, use cases, and compliance notes.

Avoid common pitfalls in SOC 2 audits to ensure compliance and protect sensitive patient data in healthcare organizations.

Essential questions to vet healthcare AI vendors—covering performance guarantees, PHI protection, liability, governance, security, explainability, and audit readiness.

Practical steps to secure cloud-hosted PHI: MFA, least privilege, segmentation, audit logging, session controls, API security, and vendor oversight.

Guide to creating and managing FDA-compliant SBOMs for medical devices, covering NTIA elements, lifecycle and vulnerability requirements, formats, and submissions.

Apply the STRIDE threat-modeling framework to identify and mitigate Spoofing, Tampering, Disclosure, DoS, Repudiation, and Privilege risks in medical devices.

Embed security into CI/CD to protect PHI: use RBAC/MFA, IaC, SAST/SCA, centralized immutable logs, AES-256/TLS encryption, BAAs, and vendor risk controls.

Five FDA cybersecurity label elements: interfaces, secure configuration, SBOMs, updates, and disclosed vulnerabilities for medical devices.

Practical criteria for selecting HIPAA-compliant encryption: AES-256, FIPS-validated modules, robust key management, and continuous monitoring.

2026 HIPAA audit changes for HDOs: mandatory annual reviews, stricter AI and vendor risk rules, and automation to cut audit time.

Machine learning predicts vendor risks in healthcare to prevent breaches, accelerate assessments, and maintain HIPAA/NIST compliance.

Cloud providers that store or transmit ePHI are business associates under HITECH; BAAs, encryption, logging and vendor oversight are required.

Five steps to verify SOC 2 Type II for cloud vendors with PHI: validate reports, review controls, map HIPAA gaps and monitor continuously

NIST-guided de-identification lets healthcare AI advance without sacrificing patient privacy.

Secure boot, runtime checks, code signing and SBOMs to prevent tampering and meet FDA and global medical device security rules.