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How Machine Learning, AI & Deep Learning Improve CybersecurityMachine intelligence is influencing all aspects of cybersecurity. Organizations are implementing AI-based security to analyze event data using ML models that identify attack patterns and increase automation. Before security teams can take advantage of AI and ML tools, they need to know what is possible. This report covers:
-How to assess the vendor's AI/ML claims
-Defining success criteria for AI/ML implementations
-Challenges when implementing AI
Incident Readiness and Building Response Playbook
In this special report, learn the Xs and Os of any good security incident readiness and response playbook.
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1 Comments
User Rank: Ninja
11/7/2017 | 7:14:38 AM
Update it - do not assume July, 2003 is a good protocol for 2017.
Workstations should store data on SERVER whenever possible so it can be backed up as above.
Ensure your risk - time window is sollid, i.,e. 24 hours of latent data, 12 hours, etc.
TEST - TEST - TEST - Do not assume a human can think straight at 2am. Solve problems NOW.
Update
Workstation rebuilds can be done in a wide range from a SIMPLE GHOST IMAGE to USB key boot over network to server or a PXE boot to server. In this case, the image server is critical to get up, if compromised, for station rebiulds. And THAT should be tested as well.