Secure Azure services and workloads with Microsoft Defender
đ Ready to secure your cloud workloads like a pro? Join us for an upcoming session on Secure Azure Services and Workloads with Microsoft Defender, where weâll go beyond the basics and dive deep into real-world cloud security. đ In this session, youâll learn how to: ⢠Enable and configure Microsoft Defender for Cloud across Azure, AWS & GCP ⢠Strengthen your security posture using Secure Score & Attack Path Analysis ⢠Protect workloads across Servers, Storage, and Containers ⢠Leverage agentless scanning, vulnerability management & JIT VM access ⢠Integrate security into DevOps with GitHub & Azure DevOps ⢠Investigate threats and automate response ⢠Improve compliance using built-in regulatory dashboards Whether you're working in multi-cloud, hybrid, or Azure-native environments, this session will give you practical insights to reduce risk and improve visibility across your estate. đ Donât miss it, level up your cloud security game! đş Register and join live â StreamYard Session đď¸ Date: 11 May 2026 â° Time: 19:00 (AEST) / 11:00 (CEST) đď¸ Speaker: Arnav Sharma đ Topic: â Secure Azure services and workloads with Microsoft DefenderResponsible AI and the Evolution of AI Security
Why Responsible AI Matters Responsible AI means designing, developing, and deploying AI systems that are ethical, transparent, and accountable. It's not just about complianceâit's about building trust, protecting users, and ensuring AI benefits everyone. Key Principles of Responsible AI: Fairness: Avoiding biases and discrimination by using diverse datasets and regular audits. Reliability & Safety: Rigorous testing to ensure AI performs as intended, even in unexpected scenarios. Privacy & Security: Protecting user data with robust safeguards. Transparency: Making AI decisions explainable and understandable. Accountability: Establishing governance to address negative impacts. Inclusiveness: Considering diverse user needs and perspectives. Responsible AI reduces bias, increases transparency, and builds user trustâcritical as AI systems increasingly impact finance, healthcare, public services, and more. Implementing Responsible AI isn't just about ethical idealsâit's a foundation that demands technical safeguards. For developers, this means translating principles like fairness and transparency into secure code, robust data handling, and model hardening strategies that preempt real-world AI threats. The Evolution of AI Security: From Afterthought to Essential AI security has come a long wayâfrom an afterthought to a central pillar of modern digital defense. In the early days, security was reactive, with threats addressed only after damage occurred. The integration of AI shifted this paradigm, enabling proactive threat detection and behavioral analytics that spot anomalies before they escalate. Key Milestones in AI Security: Pattern Recognition: Early AI focused on detecting unusual patterns, laying the groundwork for threat detection. Expert Systems: Rule-based systems in the 1970s-80s emulated human decision-making for security assessments. Machine Learning: The late 1990s saw the rise of ML algorithms that could analyze vast data and predict threats. Deep Learning: Neural networks now recognize complex threats and adapt to evolving attack methods. Real-Time Defense: Modern AI-driven platforms (like Darktrace) create adaptive, self-learning security environments that anticipate and neutralize threats proactively. Why AI Security Is Now Mandatory With the explosion of AI-powered applications and cloud services, security risks have multiplied. AI attacks are a new frontier in cybersecurity. What Are AI Attacks? AI attacks are malicious activities that target AI systems and models. Data Poisoning: Attackers manipulate training data to corrupt AI outputs. Model Theft: Sensitive models and datasets can be stolen or reverse-engineered. Adversarial Attacks: Malicious inputs can trick AI systems into making wrong decisions. Privacy Breaches: Sensitive user data can leak if not properly protected. Regulatory frameworks and industry standards now require organizations to adopt robust AI security practices to protect users, data, and critical infrastructure. Tools and Techniques for Secure AI Infrastructure and Applications Zero Trust Architecture Adopt a "never trust, always verify" approach. Enforce strict authentication and authorization for every user and device Data Security Protocols Encrypt data at rest, in transit, and during processing. Use tools like Microsoft Purview for data classification, cataloging, and access control Harden AI Models Train models with adversarial examples. Implement input validation, anomaly detection, and regular security assessments Secure API and Endpoint Management Use API gateways, OAuth 2.0, and TLS to secure endpoints. Monitor and rate-limit API access to prevent abuse. Continuous Monitoring and Incident Response Deploy AI-powered Security Information and Event Management (SIEM) systems for real-time threat detection and response Regularly audit logs and security events across your infrastructure. DevSecOps Integration Embed security into every phase of the AI development lifecycle. Automate security testing in CI/CD pipelines. Employee Training and Governance Train teams on AI-specific risks and responsible data handling. Establish clear governance frameworks for AI ethics and compliance Azure-Specific Security Tools Microsoft Defender for Cloud: Monitors and protects Azure resources. Azure Resource Graph Explorer: Maintains inventory of models, data, and assets. Microsoft Purview: Manages data security, privacy, and compliance across Azure services. Microsoft Purview provides a centralized platform for data governance, security, and compliance across your entire data estate. Why Microsoft Purview Matters for Responsible AI Microsoft Purview offers a unified, cloud-native solution for: Data discovery and classification Access management and policy enforcement Compliance monitoring and risk mitigation Data quality and observability Purview's integrated approach ensures that AI systems are built on trusted, well-governed, and secure data, addressing the core principles of responsible AI: fairness, transparency, privacy, and accountability. Conclusion Responsible AI and strong AI security measures are no longer optional; they are essential pillars of modern application development and integration on Azure. By adhering to ethical principles and utilizing cutting-edge security tools and strategies, organizations can drive innovation with confidence while safeguarding users, data, and the broader society.Grow your security skill set with the latest resources on Microsoft Learn
Keeping pace with todayâs security challenges, changing business needs, and rapidly evolving technology starts with up-to-date and innovative training, which is why weâre glad to share the latest Microsoft Security skill-building resources and offerings. Advance your expertise with the refreshed Security hub on Microsoft Learn Redesigned for learners of all abilities, this centralized hub is your go-to resource for Microsoft Security skill-building content and resources. The hub is now even easier to explore for multiple focus areas and your unique learning objectives. Find expert guidance aligned to your security journey. Whether you need to build foundational security skills, gain specialized knowledge, or prove your capabilities with Microsoft Credentials, get the guidance you need. Explore the latest resources organized by security focus area. Discover advances in Zero Trust principles, identity and access, security operations, IT security, and much more. Connect with like-minded communities, colleagues, partners, and thought leaders. Join the conversation and get inspired to level up your skills and knowledge. Find the latest cybersecurity skill-building content on our Security hub. Prove your real-world technical expertise with our latest Microsoft Applied Skills Professionals who are focused on data security and threat protection can validate and differentiate their expertise by earning these new Microsoft Applied Skills: Implement information protection and data loss prevention by using Microsoft Purview. Demonstrate your ability to implement Microsoft Purview Information Protection and Microsoft Purview Data Loss Prevention, and prove that you can discover, classify, and protect sensitive data in MicrosoftâŻ365, effectively implementing data security. This Applied Skill is particularly relevant for information protection and compliance administrators and for security operations analysts. Implement retention, eDiscovery, and Communication Compliance in Microsoft Purview. To earn this Applied Skill, validate your proficiency in working with Microsoft Purview. This credential could be an especially good fit for compliance administrators who are familiar with MicrosoftâŻ365 services and Microsoft Purview and who have experience administering compliance in MicrosoftâŻ365. Defend against cyberthreats with Microsoft DefenderâŻXDR. Earn this credential by demonstrating your ability to use Microsoft DefenderâŻXDR to detect and respond to cyberthreats. Candidates for this Applied Skill should be familiar with investigating and gathering evidence about attacks on endpoints. They should also have experience using Microsoft Defender for Endpoint and Kusto Query Language (KQL). Take the most up-to-date Microsoft Security Virtual Training Days No matter the depth of your security skills, our free Microsoft Security Virtual Training Days can help you build on those skills and gain the technical abilities and knowledge that you need to enable employees to work securely and achieve more from anywhere. To keep pace with todayâs fast-moving security landscape, weâve updated three of our most popular Virtual Training Days: Modernize Your Security Operations with Microsoft Sentinel. Learn how to deploy Microsoft Sentinel security information and event management (SIEM), migrate your existing rules, and add content hub solutions, including data connectors, analytic rules, hunting queries, and workbooks. Get the details on how you can use these tools to detect, investigate, manage incidents, and hunt threats. Additionally, find out how to maximize your coverage and better manage costs. Plus, learn how Microsoft Security Copilot can help improve security operations teamsâ response times, with features like guided response, natural language to KQL translation, and malicious script analysis. Implement Data Security with Microsoft Purview. Discover how to identify sensitive data, pinpoint critical data security risks, and build targeted data loss protection measures with Microsoft Purview solutions, including Information Protection, Data Loss Prevention, Insider Risk Management, and Adaptive Protection. Explore practical use cases and learn how to secure AI applications and identify organizational risks. Plus, find out how to secure your data and maintain the integrity of your information systems by using generative AI tools, including MicrosoftâŻ365 Copilot and third-party AI apps, as you implement dynamic measures to help prevent data leaks and address compliance in the era of AI. Defend Against Threats with Extended Detection and Response. Learn how to investigate and mitigate cyberthreats with Microsoft DefenderâŻXDR and Defender for Endpoint. Get an introduction to the unified security operations platform and find out how to deploy Microsoft Sentinel with Microsoft DefenderâŻXDR and Defender for Endpoint. Explore ways to optimize your security operations center using Microsoft Sentinel SIEM, learn about cyberattack mechanisms through incidents and alerts, and get the details on how to automate incident management by using Microsoft Security Copilot. Earn your wings: Microsoft Security Copilot Flight School Building on the foundational learning in Learn Live: Get started with Microsoft Security Copilot, host Ryan Munsch, Principal Tech Specialist at Microsoft, explores several intermediate technical topics in our Flight School videosâranging from what Microsoft Security Copilot is (and what it isnât) to key capabilities, experiences, and how to extend Copilot to your ecosystem. Each topical video is 10 mins or less, aligning to relevant learning modules on Microsoft Learn. These videos can prove especially valuable for IT pros looking to enhance their ability to process security signals and protect at the speed and scale of AI. Flight School training topics include: What is Microsoft Security Copilot? AI orchestration Standalone and embedded experiences Copilot in Microsoft Entra and Microsoft Purview Managing your plugins Prompting in Copilot Prompt engineering Using promptbooks Custom promptbooks Logic apps Extending Copilot to your ecosystem Find Flight School videos on Microsoft Learn. You can also explore Microsoft Security Copilot Flight School videos on YouTube.
