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Can ransomware turn machines against us? [Research Saturday]

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Manage episode 354449016 series 2925132
Content provided by N2K Networks, Inc. and N2K Networks. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by N2K Networks, Inc. and N2K Networks or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Tom Bonner and Eoin Wickens from HiddenLayer's SAI Team to discuss their research on weaponizing machine learning models with ransomware. Researchers at HiddenLayer’s SAI Team have developed a proof-of-concept attack for surreptitiously deploying malware, such as ransomware or Cobalt Strike Beacon, via machine learning models.

The attack uses a technique currently undetected by many cybersecurity vendors and can serve as a launchpad for lateral movement, deployment of additional malware, or the theft of highly sensitive data. In this research the team raising awareness by demonstrate how easily an adversary can deploy malware through a pre-trained ML model.

The research can be found here:

  continue reading

2818 episodes

Artwork
iconShare
 
Manage episode 354449016 series 2925132
Content provided by N2K Networks, Inc. and N2K Networks. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by N2K Networks, Inc. and N2K Networks or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Tom Bonner and Eoin Wickens from HiddenLayer's SAI Team to discuss their research on weaponizing machine learning models with ransomware. Researchers at HiddenLayer’s SAI Team have developed a proof-of-concept attack for surreptitiously deploying malware, such as ransomware or Cobalt Strike Beacon, via machine learning models.

The attack uses a technique currently undetected by many cybersecurity vendors and can serve as a launchpad for lateral movement, deployment of additional malware, or the theft of highly sensitive data. In this research the team raising awareness by demonstrate how easily an adversary can deploy malware through a pre-trained ML model.

The research can be found here:

  continue reading

2818 episodes

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