Episode 245: How AI is remaking knowledge-based authentication

In this episode of the Security Ledger podcast, we interview Matt Salisbury of Honey Badger HQ, about his anti-fraud startup and how AI and machine learning are breathing new life (and potency) into knowledge-based authentication. If you find it interesting, check out the rest of our Life After the Password series of podcasts. As always,  you can check our full conversation in our latest Security Ledger podcast at Blubrry. You can also listen to it on iTunes and Spotify. Or, check us out on Google Podcasts, Stitcher, Radio Public and more. Also: if you enjoy this podcast, consider signing up to receive it in your email. Just point your web browser to securityledger.com/subscribe to get notified whenever a new podcast is posted. Usernames and passwords have been with us almost as long as computers themselves – at least since the early 1960s when MIT introduced the Compatible Time-Sharing System (CTSS), an operating system, that was the first computer system to implement password login.  60 years in, passwords at a breaking point Matt Salisbury is the co-founder and CEO of Honey Badger HQ Six decades later, however, password use has tipped into the absurd. A 2017 study by Lastpass of its business users found that the average employee maintained 191 passwords in their account. That means the average 250 person company maintained more than 47,000 passwords. If the data is right, many of the passwords employees use are weak and easily guessed  – or used across multiple applications.  Passwordless? Imagining the Future of Authentication The adoption of so-called “two factor” authentication has helped with that problem, but even that technology has its limitations, as the recent hack of ride sharing firm Uber showed. But the key question for companies and employers remains the same: what is the most reliable and secure way to make sure someone seeking access to our network or applications is who they say they are? AI juices knowledge-based authentication