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Cyber Scams Breaking Hearts - Ep 54

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Manage episode 354788910 series 3361845
Contenu fourni par Reimagining Cyber. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Reimagining Cyber ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

Valentine’s Day is (almost) upon us, and Stan and Rob are marking this celebration of love by looking at online dating scams. Romantic, yes?!
Their guest is Dan Winchester, co-founder of Scamalytics. Scamalytics has a focus on helping dating sites automatically remove scammers from their sites in real-time.

Talking points:

- How scammers affect a dating sites business model
“Most dating services are trying to move as many of their users as possible over to a subscription. You’re not going to pay a subscription when the product you're subscribing to looks like it's just full of junk and scammers”

- On collecting data to prevent fraud
“There's a tension between privacy and safety. Users want to feel safe, but they also want to make sure that their privacy is respected. So you need to really be figuring out what's the minimum amount of data you can use in order to prevent the maximum amount of fraud.”

- Relationships with service providers
“We often have quite a tricky relationship with the service providers themselves because they may not be taking as much action as we would like when fraud happens on their networks. And you know, some of these companies are obviously massive and it's quite hard to get them to really deal with these issues.”

- On AI/machine learning
“We do a lot of machine learning stuff within Scamalytics, but I would always add a cautionary note that we find that the domain knowledge is way, way more useful than machine learning because when you're dealing with fraud, you've really got to be attuned to false positives and it's so easy for machine learning systems to get into false positive feedback loops and things like that.”

Follow or subscribe to the show on your preferred podcast platform.
Share the show with others in the cybersecurity world.
Get in touch via reimaginingcyber@gmail.com

  continue reading

101 episodes

Artwork
iconPartager
 
Manage episode 354788910 series 3361845
Contenu fourni par Reimagining Cyber. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Reimagining Cyber ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

Valentine’s Day is (almost) upon us, and Stan and Rob are marking this celebration of love by looking at online dating scams. Romantic, yes?!
Their guest is Dan Winchester, co-founder of Scamalytics. Scamalytics has a focus on helping dating sites automatically remove scammers from their sites in real-time.

Talking points:

- How scammers affect a dating sites business model
“Most dating services are trying to move as many of their users as possible over to a subscription. You’re not going to pay a subscription when the product you're subscribing to looks like it's just full of junk and scammers”

- On collecting data to prevent fraud
“There's a tension between privacy and safety. Users want to feel safe, but they also want to make sure that their privacy is respected. So you need to really be figuring out what's the minimum amount of data you can use in order to prevent the maximum amount of fraud.”

- Relationships with service providers
“We often have quite a tricky relationship with the service providers themselves because they may not be taking as much action as we would like when fraud happens on their networks. And you know, some of these companies are obviously massive and it's quite hard to get them to really deal with these issues.”

- On AI/machine learning
“We do a lot of machine learning stuff within Scamalytics, but I would always add a cautionary note that we find that the domain knowledge is way, way more useful than machine learning because when you're dealing with fraud, you've really got to be attuned to false positives and it's so easy for machine learning systems to get into false positive feedback loops and things like that.”

Follow or subscribe to the show on your preferred podcast platform.
Share the show with others in the cybersecurity world.
Get in touch via reimaginingcyber@gmail.com

  continue reading

101 episodes

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