From unstructured data to actionable intelligence: Using machine learning for threat intelligence

Credit to Author: Eric Avena| Date: Thu, 08 Aug 2019 16:30:12 +0000

Machine learning and natural language processing can automate the processing of unstructured text for insightful, actionable threat intelligence.

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Protect against BlueKeep

Credit to Author: Todd VanderArk| Date: Thu, 08 Aug 2019 16:00:57 +0000

DART offers steps you can take to protect your network from BlueKeep, the “wormable” vulnerability that can create a large-scale outbreak due to its ability to replicate and propagate.

The post Protect against BlueKeep appeared first on Microsoft Security.

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A case study in industry collaboration: Poisoned RDP vulnerability disclosure and response

Credit to Author: Eric Avena| Date: Wed, 07 Aug 2019 23:50:25 +0000

Through a cross-company, cross-continent collaboration, we discovered a vulnerability, secured customers, and developed fix, all while learning important lessons that we can share with the industry.

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How Windows Defender Antivirus integrates hardware-based system integrity for informed, extensive endpoint protection

Credit to Author: Eric Avena| Date: Wed, 31 Jul 2019 16:30:35 +0000

The deep integration of Windows Defender Antivirus with hardware-based isolation capabilities allows the detection of artifacts of attacks that tamper with kernel-mode agents at the hypervisor level.

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CISO series: Better cybersecurity requires a diverse and inclusive approach to AI and machine learning

Credit to Author: Todd VanderArk| Date: Wed, 31 Jul 2019 16:00:51 +0000

A collaborative, inclusive approach to creating AI and machine learning models can help increase your resilience to cyberattacks.

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Dismantling a fileless campaign: Microsoft Defender ATP’s Antivirus exposes Astaroth attack

Credit to Author: Eric Avena| Date: Mon, 08 Jul 2019 16:00:51 +0000

Advanced technologies in Microsoft Defender ATP’s Antivirus exposed and defeated a widespread fileless campaign that completely “lived off the land” throughout a complex attack chain that run the info-stealing backdoor Astaroth directly in memory

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Council of EU Law Enforcement Protocol improves cross-border cooperation

Credit to Author: Todd VanderArk| Date: Tue, 30 Jul 2019 16:00:00 +0000

The new EU Law Enforcement Emergency Response Protocol addresses the growing problem of planning and coordinating between governments, agencies, and companies when cyberattacks occur across international boundaries.

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The evolution of Microsoft Threat Protection—July update

Credit to Author: Todd VanderArk| Date: Mon, 29 Jul 2019 16:00:50 +0000

Learn about the latest enhancements to Microsoft Threat Protection, the premier solution for securing the modern workplace across identities, endpoints, user data, apps, and infrastructure.

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New machine learning model sifts through the good to unearth the bad in evasive malware

Credit to Author: Eric Avena| Date: Thu, 25 Jul 2019 16:30:55 +0000

Most machine learning models are trained on a mix of malicious and clean features. Attackers routinely try to throw these models off balance by stuffing clean features into malware. Monotonic models are resistant against adversarial attacks because they are trained differently: they only look for malicious features. The magic is this: Attackers can’t evade a monotonic model by adding clean features. To evade a monotonic model, an attacker would have to remove malicious features.

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