Unsupervised Learning

By Daniel MiesslerTechnology

Unsupervised Learning episodes

May 20, 2020 Analysis of the 2020 Verizon Data Breach Report
In this episode, Daniel takes a look at the 2020 Verizon Data Breach Investigations Report. He looks at the key findings and talks about what they might mean to us going forward.
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11 min
May 18, 2020 Unsupervised Learning: No. 229
Feds Release Top Vulns, China Brainwave Tracking, Europe CISSP Masters, Army Electronic Warfare, Microsoft Third-largest Patch Tuesday, Technology News, Human News, Ideas Trends & Analysis, Discovery, Recommendations, and the Weekly Aphorism…
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20 min
May 12, 2020 Unsupervised Learning: No. 228
Thunderbolt Attack, Celebrity Ransomware, ClearView Government, Blackhat DEFCON Virtual, War Thunder, 5G Bio Attacks, PC Game Cheating, Zoom Keybase, Technology News, Human News, Ideas Trends & Analysis, Discovery, Recommendations, and the Weekly Aphorism…
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17 min
May 04, 2020 Unsupervised Learning: No. 227
VICE vs. Chinese Surveillance, Indian Contact Tracing, NHS + GCHQ, Banjo Racism, Singapore Requires Check-ins, Bruce on Contact Tracing, Technology News, Human News, Ideas Trends & Analysis, Discovery, Recommendations, and the Weekly Aphorism…
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21 min
April 28, 2020 Unsupervised Learning: No. 226
Bay Area Lockdown Til May, The Swedish Approach, California Autopsies, Zoom Security Updates, Palantir Contacts, NSA Web Vulns, GreyNoise Services, Technology News, Human News, Ideas Trends & Analysis, Discovery, Recommendations, and the Weekly Aphorism…
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21 min
April 22, 2020A Conversation with Renée DiResta: Disinformation and Conspiracy Propagation
In this episode, Daniel speaks with Renée DiResta about her work tracking narratives online. They discuss:

The different strains of false information

Her work at the Stanford Internet Observatory

How the same narrative can be used by multiple sides

The origin of the Bill Gates conspiracies

Mapping campaigns to actor strategies

What she recommends others do who are interested in her field

Other topics around disinformation, conspiracy, and narrative tracking

Renée DiResta is the technical research manager at Stanford Internet Observatory, a cross-disciplinary program of research, teaching and policy engagement for the study of abuse in current information technologies. Renee investigates the spread of malicious narratives across social networks, and assists policymakers in devising responses to the problem.

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1 hr 7 min
April 21, 2020 Unsupervised Learning: No. 225
Flu Simulations, Amazon Thermal Cameras, Facebook Bad Info Tracing, 5G Gates Conspiracies, Google Slows Hiring, Amazon Hires More, Technology News, Human News, Ideas Trends & Analysis, Discovery, Recommendations, and the Weekly Aphorism…
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15 min
April 14, 2020 Unsupervised Learning: No. 224
Biogen Superspreaders, African Locusts, Game of Life, Meat Troubles, 5G Conspiracies, Japan Getting Out of China, Technology News, Human News, Ideas Trends & Analysis, Discovery, Recommendations, and the Weekly Aphorism…
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21 min
April 07, 2020 Unsupervised Learning: No. 223
Coronavirus unemployment rate, 2 million guns, UK 5G attacks, German Antibodies, Zoom Drama, New Cloudflare Servers, Technology News, Human News, Ideas Trends & Analysis, Discovery, Recommendations, and the Weekly Aphorism…
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16 min
April 02, 2020 A Conversation With Leif Dreizler About Security Engineering at Segment
So today I’m talking to Leif Dreizler. Leif is a buddy of mine who also works in San Francisco. He’s a developer at a company called Segment, and over the last year or so he’s been telling me about all kinds of cool stuff he’s been working on, how his team is set up, and how they see security teams being built in the future. So we’re going to cover those topics and more in a conversation that ranges from security engineering strategy to solving specific problems through custom tooling.
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55 min

About Unsupervised Learning

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Unsupervised Learning is about ideas and trends in Cybersecurity, National Security, AI, Technology, and Culture—and how best to upgrade ourselves to be ready for what's coming.