Machine Learning & Connected Cars with Security Journeyman Josh Lemos
Jan 04, 2020•1 hr 15 min
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Episode description
Our 1st episode of 2020 is a story in three parts, beginning with hard fought wisdom of a veteran security practitioner, then diving deep into machine learning (ML) before wrapping up with how both security and AI apply to connected vehicles.
The first part of our 74 minute conversation with Josh Lemos is the backstory of how he started his career in cybersecurity as a consultant... and left services to join ServiceNow as a practitioner. His time at ServiceNow lays out a solid formula for fixing application security inside a growth company who can little afford to slow down-- or suffer the pain of the inevitable breach if the situation doesn’t improve.
Jack & Dave’s conversation with Josh on ML lays down many of the basics and is intended to be a rough primer for future episodes where we will further explore the topic. We discuss how ML projects often take much more preparation than originally planned and topics that range from class imbalances, the differences between supervised/unsupervised ML, a starter’s toolkit and what to expect along with some rookie mistakes to avoid.
As part of Cylance/Blackberry, Josh has recently been involved with connected vehicle projects where standard security techniques for detecting executable malware on laptops and servers can start to look like child’s play in comparison to effort required to properly diagnose events across the diverse hardware and software found in a modern car. Before wrapping with our speed round, we look ahead at areas where ML may be able to make leaps forward in both vehicles and across cyber security.
The first part of our 74 minute conversation with Josh Lemos is the backstory of how he started his career in cybersecurity as a consultant... and left services to join ServiceNow as a practitioner. His time at ServiceNow lays out a solid formula for fixing application security inside a growth company who can little afford to slow down-- or suffer the pain of the inevitable breach if the situation doesn’t improve.
Jack & Dave’s conversation with Josh on ML lays down many of the basics and is intended to be a rough primer for future episodes where we will further explore the topic. We discuss how ML projects often take much more preparation than originally planned and topics that range from class imbalances, the differences between supervised/unsupervised ML, a starter’s toolkit and what to expect along with some rookie mistakes to avoid.
As part of Cylance/Blackberry, Josh has recently been involved with connected vehicle projects where standard security techniques for detecting executable malware on laptops and servers can start to look like child’s play in comparison to effort required to properly diagnose events across the diverse hardware and software found in a modern car. Before wrapping with our speed round, we look ahead at areas where ML may be able to make leaps forward in both vehicles and across cyber security.
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