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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.

The post How Windows Defender Antivirus integrates hardware-based system integrity for informed, extensive endpoint protection appeared first on Microsoft Security.

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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

The post Dismantling a fileless campaign: Microsoft Defender ATP’s Antivirus exposes Astaroth attack appeared first on Microsoft Security.

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ScadaICSSchneider
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The ISA Global Cybersecurity Alliance: Heeding the Need for Collaboration; Acting as Agents of Change

Credit to Author: Andrew Kling| Date: Fri, 26 Jul 2019 14:45:40 +0000

In January 2018, on the heels of the well-publicized but often misunderstood Triton cyber-attack, Schneider Electric made a strategic decision. Two actually. First, because the attack methodology presented new and… Read more »

The post The ISA Global Cybersecurity Alliance: Heeding the Need for Collaboration; Acting as Agents of Change appeared first on Schneider Electric Blog.

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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.

The post New machine learning model sifts through the good to unearth the bad in evasive malware appeared first on Microsoft Security.

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ScadaICSSchneider
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Control Panel Developers and Installers: Modernizing into a Smart Factory

Credit to Author: Zach Tinkler| Date: Mon, 22 Jul 2019 20:36:54 +0000

Practical Lessons Learned from a Brownfield IIoT Implementation The industry is changing as End User customers are modernizing their facilities with IIoT-based technologies. The implementation is turning their existing brownfield… Read more »

The post Control Panel Developers and Installers: Modernizing into a Smart Factory appeared first on Schneider Electric Blog.

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ScadaICSSchneider
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Modernizing Emergency Shutdown Systems Step 4: Use a Risk Approach

Credit to Author: Steve Elliott| Date: Mon, 22 Jul 2019 13:00:23 +0000

The Digital Revolution. Industry 4.0. The Industrial Internet of Things. The 4th Industrial Revolution. Call it what you will but today’s fast-accelerating technological evolution has forever changed the business of… Read more »

The post Modernizing Emergency Shutdown Systems Step 4: Use a Risk Approach appeared first on Schneider Electric Blog.

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MicrosoftSecurity
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Dismantling a fileless campaign: Microsoft Defender ATP next-gen protection exposes Astaroth attack

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

Advanced technologies in Microsoft Defender ATP next-generation protection 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

The post Dismantling a fileless campaign: Microsoft Defender ATP next-gen protection exposes Astaroth attack appeared first on Microsoft Security.

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