Rumored for some time, Google’s purchase of a significant chunk of handset-maker HTC was announced today . The WSJ: Google said an HTC team that helped develop Google’s flagship Pixel smartphone will join the company. The Mountain View, Calif., company will also get a nonexclusive license to HTC intellectual property. HTC was hired by Google to be the contract manufacturer for the Pixel, a high-end smartphone that was launched last year, in part to better compete with Apple Inc. $1.1bn in cash is probably most of HTC. The company’s market share evaporated over the last half-decade but it remains a well-respected manufacturer. Alternative Betteridge headline: “Will Google buying HTC go better than Google buying Motorola?”
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Google buys $1.1bn piece of HTC
sciencehabit shares a report from Science Magazine: The Equifax breach is reason for concern, of course, but if a hacker wants to access your online data by simply guessing your password, you’re probably toast in less than an hour. Now, there’s more bad news: Scientists have harnessed the power of artificial intelligence (AI) to create a program that, combined with existing tools, figured more than a quarter of the passwords from a set of more than 43 million LinkedIn profiles. Researchers at Stevens Institute of Technology in Hoboken, New Jersey, started with a so-called generative adversarial network, or GAN, which comprises two artificial neural networks. A “generator” attempts to produce artificial outputs (like images) that resemble real examples (actual photos), while a “discriminator” tries to detect real from fake. They help refine each other until the generator becomes a skilled counterfeiter. The Stevens team created a GAN it called PassGAN and compared it with two versions of hashCat and one version of John the Ripper. The scientists fed each tool tens of millions of leaked passwords from a gaming site called RockYou, and asked them to generate hundreds of millions of new passwords on their own. Then they counted how many of these new passwords matched a set of leaked passwords from LinkedIn, as a measure of how successful they’d be at cracking them. On its own, PassGAN generated 12% of the passwords in the LinkedIn set, whereas its three competitors generated between 6% and 23%. But the best performance came from combining PassGAN and hashCat. Together, they were able to crack 27% of passwords in the LinkedIn set, the researchers reported this month in a draft paper posted on arXiv. Even failed passwords from PassGAN seemed pretty realistic: saddracula, santazone, coolarse18. Read more of this story at Slashdot.