AI and machine learning Archives - Page 4 of 4 - ThreatsHub Cybersecurity News

Deep learning rises: New methods for detecting malicious PowerShell

September 3, 2019 TH Author AI and machine learning, Cybersecurity, deep learning, Endpoint security, machine learning, Microsoft Defender ATP, Microsoft security intelligence, PowerShell, Security Intelligence, Threat protection

We adopted a deep learning technique that was initially developed for natural language processing and applied to expand Microsoft Defender ATP’s coverage of detecting malicious PowerShell scripts, which continue to be a critical attack vector.
The post Deep learning rises: New methods for detecting malicious PowerShell appeared first on Microsoft Security. READ MORE HERE…

Microsoft Secure

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

August 8, 2019 TH Author AI and machine learning, Automation, Cybersecurity, Endpoint security, indicators of compromise (IoC), machine learning, Microsoft Defender Advanced Threat Protection, Microsoft security intelligence, Security Intelligence, threat intelligence, TTPs, Windows Security

Machine learning and natural language processing can automate the processing of unstructured text for insightful, actionable threat intelligence.
The post From unstructured data to actionable intelligence: Using machine learning for threat intelligence appeared first on Microsoft Security. READ MORE HERE…

Microsoft Secure

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

July 31, 2019 TH Author AI and machine learning, CISO series

A collaborative, inclusive approach to creating AI and machine learning models can help increase your resilience to cyberattacks.
The post CISO series: Better cybersecurity requires a diverse and inclusive approach to AI and machine learning appeared first on Microsoft Security. READ MORE HERE…

Microsoft Secure

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

July 25, 2019 TH Author AI and machine learning, antivirus, Automation, Cybersecurity, detection evasion, Endpoint security, LockerGoga, machine learning, Microsoft Defender Advanced Threat Protection, Microsoft Defender ATP, Microsoft security intelligence, monotonic models, next generation protection, Windows Defender Antivirus

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. READ MORE HERE…

Microsoft Secure

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

July 8, 2019 TH Author AI and machine learning, Antimalware Scan Interface (AMSI), Astaroth, behavior monitoring, Command-line scanning, Cybersecurity, Endpoint security, Execution stage, fileless, fileless malware, heuristics, Initial access stage, living-off-the-land, Microsoft Defender ATP, Security Intelligence, Threat protection, Windows Defender Antivirus, Windows Security, WMIC

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. READ MORE HERE…

Microsoft Secure

5 principles driving a customer-obsessed identity strategy at Microsoft

June 24, 2019 TH Author AI and machine learning, Identity and access management, Zero Trust

The cloud era has fundamentally changed the way businesses must think about security and identity. Learn the five principles driving the customer-obsessed identity strategy at Microsoft.
The post 5 principles driving a customer-obsessed identity strategy at Microsoft appeared first on Microsoft Security. READ MORE HERE…

Microsoft Secure

Inside out: Get to know the advanced technologies at the core of Microsoft Defender ATP next generation protection

June 24, 2019 TH Author AI and machine learning, Antimalware Scan Interface (AMSI), behavior monitoring, behavior-based machine learning, Cybersecurity, Endpoint security, heuristics, machine learning, memory scanning, Microsoft Defender ATP, next-generation protections, Threat protection, Windows Defender Antivirus, Windows Security

While Windows Defender Antivirus makes catching 5 billion threats on devices every month look easy, multiple advanced detection and prevention technologies work under the hood to make this happen. Multiple next-generation protection engines to detect and stop a wide range of threats and attacker techniques at multiple points, providing industry-best detection and blocking capabilities.
The post Inside out: Get to know the advanced technologies at the core of Microsoft Defender ATP next generation protection appeared first on Microsoft Security. READ MORE HERE…