machine learning – Page 4 – Computer Security Articles

Deep learning rises: New methods for detecting malicious PowerShell

September 3, 2019 admin AI and machine learning, cybersecurity, deep learning, Endpoint security, machine learning, Microsoft Defender ATP, Microsoft security intelligence, Powershell, Security Intelligence, Threat protection

Credit to Author: Eric Avena| Date: Tue, 03 Sep 2019 16:00:03 +0000

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 .

Microsoft Security

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

August 8, 2019 admin 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

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.

The post From unstructured data to actionable intelligence: Using machine learning for threat intelligence appeared first on Microsoft Security .

Microsoft Security

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

July 25, 2019 admin 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

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 .

Security Sophos

The security of machine learning

July 24, 2019 admin Corporate, Intercept X, machine learning, Sophos Intercept X

Credit to Author: Greg Iddon| Date: Wed, 24 Jul 2019 08:42:37 +0000

Artificial intelligence and machine learning are persistently in the headlines with rich debate over its next advances. Will cybercriminals further leverage machine learning to craft attacks? Can defenders build a machine learning model capable of detecting all malware? We believe machine learning is an essential and critical piece of cybersecurity, but it must be only […]<img src=”http://feeds.feedburner.com/~r/sophos/dgdY/~4/z8gcd4bDkho” height=”1″ width=”1″ alt=””/>

Security Sophos

Stop facial recognition trials now, warns UK committee

July 23, 2019 admin biometrics, Facial Recognition, Government security, government surveillance, machine learning, privacy, security threats, UK Government

Credit to Author: Danny Bradbury| Date: Mon, 22 Jul 2019 10:26:39 +0000

The UK government should suspend trials of automatic facial recognition systems until it can meet regulators’ concerns about the technology, according to a report released Friday.<img src=”http://feeds.feedburner.com/~r/nakedsecurity/~4/0CSbKeo22L8″ height=”1″ width=”1″ alt=””/>

Microsoft Security

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

June 25, 2019 admin 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

Credit to Author: Eric Avena| Date: Mon, 24 Jun 2019 15:00:55 +0000

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 .

MalwareBytes Security

Labs report: Malicious AI is coming—is the security world ready?

June 19, 2019 admin AI, Anomaly Detection, Artificial Intelligence, deep learning, deepfakes, fake news, machine learning, social media, vulnerabilities

Credit to Author: Malwarebytes Labs| Date: Wed, 19 Jun 2019 15:00:00 +0000

Malwarebytes Labs’ latest report looks at the near-future reality of malicious artificial intelligence (AI), evaluating how the technology is being used today, and how it realistically might be abused in the next few years.

Categories:

Artificial Intelligence

Tags: AI Anomaly Detection artificial intelligence deep learning deepfakes fake news machine learning social media vulnerabilities

Security Sophos

Il machine learning affina le armi nella lotta contro i documenti dannosi

April 29, 2019 admin machine learning, Sophos News

Credit to Author: Sophos Italia| Date: Fri, 19 Apr 2019 05:30:22 +0000

Una grande vittoria per il machine learning nella sua lotta contro i malware<img src=”http://feeds.feedburner.com/~r/sophos/dgdY/~4/DP51KDsRM8c” height=”1″ width=”1″ alt=””/>