SEC595: Applied Data Science and AI/Machine Learning for Cybersecurity Professionals

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Event Overview
There is little doubt that we have entered the information age. In recent years, the human race has generated more information than in all previous human history - and the pace of information generation is accelerating. The security industry is no different, our data processing requirements are increasing on a near daily basis.
As one example, consider Windows event logs. In Windows Server 2003, there were three event logs: System, Application, and Security. While those event logs remain today, the event log folder now looks like an extended family reunion with 337 total event logs in place. Whatever processes organizations were using to successfully process security related data previously clearly wont scale for today. Organizations need tools that can distill meaning from large data sets that are constantly increasing in size.
Organizations that suffer data breaches typically dont suffer from a lack of data, they simply struggle to discover actionable findings in the data. To that end, Artificial Intelligence (AI) and Machine Learning (ML) can help. Example uses for AI/ML include:
Renewed focus on supply chain security suggests that organizations will be storing their security data for longer periods as well. The SolarWinds breach was not discovered until victims had been infected for as long as nine months. Simply searching nine months of data for known indicators doesnt require AI or ML. But if you already have the data, why not do more with it? AI and ML hold the keys to unlocking the potential of this data.
As the quantity of security data continues to increase, AI and ML solutions hold the promise of delivering actionable recommendations to security professionals. Come learn from our featured vendors how their solutions deliver on the promises of increased security through this fascinating technology.