CISO Spotlight: How diversity of data (and people) defeats today’s cyber threats

Credit to Author: Teri Seals-Dormer| Date: Tue, 20 Oct 2020 16:00:50 +0000

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. It allows us to respond swiftly…

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Microsoft Digital Defense Report 2020: Cyber Threat Sophistication on the Rise

Credit to Author: Jim Flack| Date: Tue, 29 Sep 2020 16:00:51 +0000

A new report from Microsoft shows it is clear that threat actors have rapidly increased in sophistication over the past year, using techniques that make them harder to identify.

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Microsoft Security: How to cultivate a diverse cybersecurity team

Credit to Author: Jim Flack| Date: Mon, 31 Aug 2020 18:00:30 +0000

A diverse cybersecurity team will help you generate the innovative ideas you need to confront today and tomorrow’s cyber threats.

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Seeing the big picture: Deep learning-based fusion of behavior signals for threat detection

Credit to Author: Eric Avena| Date: Thu, 23 Jul 2020 16:00:53 +0000

Learn how we’re using deep learning to build a powerful, high-precision classification model for long sequences of wide-ranging signals occurring at different times.

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Misconfigured Kubeflow workloads are a security risk

Credit to Author: Jim Flack| Date: Wed, 10 Jun 2020 18:00:40 +0000

Azure Security Center monitors and defends thousands of Kubernetes clusters running on top of Azure Kubernetes Service. In this blog, we’ll reveal a new campaign that was observed recently by ASC that targets Kubeflow, a machine learning toolkit for Kubernetes.

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The science behind Microsoft Threat Protection: Attack modeling for finding and stopping evasive ransomware

Credit to Author: Eric Avena| Date: Wed, 10 Jun 2020 17:42:07 +0000

Microsoft Threat Protection uses a data-driven approach for identifying lateral movement, combining industry-leading optics, expertise, and data science to deliver automated discovery of some of the most critical threats today.

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Microsoft researchers work with Intel Labs to explore new deep learning approaches for malware classification

Credit to Author: Eric Avena| Date: Fri, 08 May 2020 18:30:34 +0000

Researchers from Microsoft Threat Protection Intelligence Team and Intel Labs collaborated to study the application of deep transfer learning technique from computer vision to static malware classification.

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Secure the software development lifecycle with machine learning

Credit to Author: Jim Flack| Date: Thu, 16 Apr 2020 16:00:04 +0000

A collaboration between data science and security produced a machine learning model that accurately identifies and classifies security bugs based solely on report names.

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