Cybersecurity and Data Science are tightly intertwined. Kirill Eremenko, CEO of SuperDataScience, and I had a great time discussing the risks and opportunities in his latest podcast Predict, Prevent, Detect: Cyber Security (episode #273).
Data is the life's blood of digital protection and deep analysis of massive data sets is key to deciphering threats but also represents an emerging vector for new risks.
Powerful tools such as Artificial Intelligence, specifically machine learning and deep learning, can be used for good or malice. The security industry is working to leverage these capabilities but those who seek to undermine trust or misuse technology are also working to apply these instruments to the detriment of digital security, personal privacy, and physical safety.
The podcast captured a wonderful conversation about the risks and opportunities at the intersection of data analysis and security. In an interesting turn, the discussion did dive into an uncomfortable example, guaranteed to make you smile or cringe, as we explored the risks of aggregated data sets. Combining deep analysis across domains can create new information connections and an entirely new narrative that can be both greatly beneficial as well as disturbingly caustic.
For those data scientists interested in cybersecurity I provide some starter advice as the industry needs such skills and perspectives to thrive. There are vast opportunities for those keen on figuring out how to detect and protect digital technology through the use of data analysis driven decisions.
It was a fantastic discussion and I look forward to talking with Kirill and his ardent followers in the future. Teamwork and collaboration across many domains are necessary to build long lasting trust in digital technologies.
I fully recommend listening to all his podcasts. There are some great topics and speakers. Visit https://www.superdatascience.com/podcast site for the full list.
