With the onset of Internet of Things (IoT) technology, an enormous number of devices are now accessible via the Internet and are therefore vulnerable to cyberattack. Society is still adjusting to the fact that devices that people used to trust can now betray them in unexpected ways. Your television may expose your conversations, your printer may divulge your documents, and your fitness monitor may reveal your health information. All of these attacks become possible in the presence of IoT devices which are not designed with security in mind. System designers are trained to evaluate system design options in terms of their impact on system characteristics such as power, performance, and time-to-market, but security is a property which is less well understood. Designers of IoT devices need to have the ability to consider, both qualitatively and quantitatively, how design alternatives affect the security of the system. To do that, designers must understand the essential aspects of common cyberattacks.

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“We’re trying to study where there’s a trade-off between what you’re willing to share and what you get as a utility,” says computer science professor Sharad Mehrotra. “We want to know if there’s a way to build privacy protections on a layer in between the sensors and the end user.”

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Although they emphasized that they would not be comfortable handing over this level of control to an algorithm, several speakers at the CERN workshop discussed how deep learning could be applied to physics. Pierre Baldi, an AI researcher at the University of California, Irvine who has applied machine learning to various branches of science, described how he and his collaborators have done research suggesting that a deep-learning technique known as dark knowledge might aid — fittingly — in the search for dark matter.

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“Just like hostages wind up often getting passed around and sold like goods,” said Gene Tsudik, who heads the computer science department at UC Irvine. “This is really a complete takeover of one’s identity,” he said. … “Don’t over share,” Tsudik warned.

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Ramesh Jain got the start-up bug a couple of decades ago. While spending a year at Stanford University as a visiting professor of computer science, he was stunned by the whirlwind of entrepreneurial activity among his fellow professors. “You’re developing something people really can use,” he says. “And it makes you a better researcher.”

Now, Jain, 66, who is a professor at the Bren School of Information and Computer Sciences at the University of California in Irvine, is launching his seventh enterprise, one that, he says, “brings together many concepts and ideas I’ve been researching for the past 20 years.”

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The USA Freedom Act also curtails some mechanisms already ruled illegal by appellate court, including the direct collection of bulk call metadata directly by the NSA. However, it still leaves the data in the hands of the phone companies, and allows it to be queried by the NSA using targeted selectors.

This worries Gene Tsudik, a professor in the computer science department at the University of California, Irvine. “This stuff represents a treasure trove of information, and an attractive target for attacks,” he says. “I believe that if metadata has to be kept for some time, it is best to split it in a way that neither NSA nor the phone company can make sense of it, without cooperation.”

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