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How To Defend A Bank, Part 1: Fusion Centers
Triton, Part 2: The World’s Most Dangerous Malware
Deep Fakes are set to revolutionize content creation, but alongside this technology's benefits, it also has the potential two sow havoc, fear, and distrust via Social Networks. Just this week, Facebook disclosed a network of fake users it found, whose profile images were all deep faked. So, how can we identify deep fakes - even before they go online?
Over the past two years, the internet has been inundated with celebrity Deep Fake videos of all kinds: Obama, Putin, and Trump deliver speeches they never gave, Gal Gadot "stars” in a porn video, and professional comedians such as Bill Hader eerily turn into the people they impersonate, like Tom Cruise and Arnold Schwarzenegger.
What all of these videos have in common is that they were mostly created by amateur developers or small startups with tight budgets - but their quality is surprisingly good, and in some cases as good as what the biggest movie studios were able to produce with huge budgets just a few years ago.
So what happened in the last five years, that turned special effects from being the exclusive domain of industry experts - into something a 14-year-old can create more or less at the touch of a button? Like the top end of a floating glacier, Deep Fakes are by and large only the visible product of a fascinating - and much deeper - technological revolution in the field of artificial intelligence. As we shall soon see, this revolution has the potential to put some very powerful tools in the hands of both attackers and defenders in the world of cyber-security.
Sam Curry: The 2020 Crystal Ball
From the publisher's feed
Malicious Life by Cybereason tells the unknown stories of the history of cybersecurity, with comments and reflections by real hackers, security experts, journalists, and politicians.

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