Combing through the fuzz: Using fuzzy hashing and deep learning to counter malware detection evasion techniques

Credit to Author: Eric Avena| Date: Tue, 27 Jul 2021 16:00:17 +0000

A new approach for malware classification combines deep learning with fuzzy hashing. Fuzzy hashes identify similarities among malicious files and a deep learning methodology inspired by natural language processing (NLP) better identifies similarities that actually matter, improving detection quality and scale of deployment.

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Lock and Code S1Ep21: Lesson planning your school’s cybersecurity with Doug Levin

Credit to Author: Malwarebytes Labs| Date: Mon, 07 Dec 2020 14:10:00 +0000

This week on Lock and Code, we discuss the top security headlines generated right here on Labs and around the Internet. In addition, we talk to Doug Levin, founder of the K12 cybersecurity resource center and advisor to the K12 Security Information Exchange, about how schools can plan for a cybersecure 2021. Education faced a…

Categories: Podcast

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Deep learning: An explanation and a peek into the future

Credit to Author: Pieter Arntz| Date: Tue, 01 Dec 2020 15:36:57 +0000

Deep learning is a special field in machine learning that is showing new developments in many industries. We explain the concept and give some examples of the latest and greatest.

Categories: Explained

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The post Deep learning: An explanation and a peek into the future appeared first on Malwarebytes Labs.

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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.

The post Seeing the big picture: Deep learning-based fusion of behavior signals for threat detection appeared first on Microsoft Security.

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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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Deep learning rises: New methods for detecting malicious PowerShell

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.

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