Register for Microsoft Secure on March 28, 2023, for insights on AI, identity, data security, and more. In this blog post, we preview what to expect and session highlights you won’t want to miss.
Today marks a significant shift in endpoint management and security. We are launching the Microsoft Intune Suite, which unifies mission-critical advanced endpoint management and security solutions into one simple bundle.
Vasu Jakkal invites you to join us at the Microsoft Secure digital event to discover exciting product announcements and what an AI-driven future means for cybersecurity.
Today, we are releasing an AI security risk assessment framework as a step to empower organizations to reliably audit, track, and improve the security of the AI systems. In addition, we are providing new updates to Counterfit, our open-source tool to simplify assessing the security posture of AI systems.
We developed a cloud-based machine learning system that, when queried by a device, intelligently predicts if it is at risk, then automatically issues a more aggressive blocking verdict to protect the device, thwarting an attacker’s next steps.
Today, we are open-sourcing Cloud Katana, a cloud-native tool under development, to automate simulation steps on-demand in multi-cloud and hybrid cloud environments. This tool is an event-driven, serverless compute application built on the top of Azure Functions that expedites the research process and validation of security controls.
Today, we are launching MLSEC.IO, a new machine learning security evasion competition as an educational effort for the AI and security communities to exercise their muscle to attack critical AI systems in a realistic setting.
Counterfit is a command-line tool for security professionals to red team AI systems and systematically scans for vulnerabilities as part of AI risk assessment.
Machine learning (ML) is making incredible transformations in critical areas such as finance, healthcare, and defense, impacting nearly every aspect of our lives. Many businesses, eager to capitalize on advancements in ML, have not scrutinized the security of their ML systems.
This year, we have seen five significant security paradigm shifts in our industry. This includes the acknowledgment that the greater the diversity of our data sets, the better the AI and machine learning outcomes. This diversity gives us an advantage over our cyber adversaries and improves our threat intelligence.
