These are also closely related to: "Neutralize emerging threats through collaboration"

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  Bolster signature-based malware detection with machine learning

  By: Sentinel Labs, Inc.

  Type: eGuide

  While signature-based detection is a tried-and-true method for identifying malicious code, it simply can’t keep up with the advanced, metamorphic malware that’s constantly evolving to sneak past defensive measures.

  This expert e-guide explores how to improve advanced malware threat detection as well as network and endpoint security. Hear from security experts Michael Cobb and Karen Scarfone about:

  • How machine learning improves signature-based detection
  • Combining signature-based and anomaly-based behavior detection
  • 10 questions to ask endpoint security vendors
  • And more

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  Hacking the Human Operating System

  By: TechTarget ComputerWeekly.com

  Type: Essential Guide

  The prevalence of social engineering in many publicly disclosed cyber attacks suggests there is either an inherent weakness in the ability of victims to distinguish malicious communications or that cyber criminals are using more complex methods to bypass the “human firewall”. 

  The truth likely lies somewhere between these two statements, but, regardless of the root cause, we can see that the first line of defence is evidently failing. More importantly, to blame users for breaches is not entirely fair. There are many examples of clearly unsafe user behaviour, but this report will demonstrate that attackers often bypass the consciousness of their targets and attempt to manipulate victims through subconscious influences.

  This report will review the concept of social engineering. We will consider the techniques used in recent cyber attacks, as well as the levers to influence victims, communication channels and suggested controls to reduce the risks.

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