More Cyberattacks or Just More Media Attention?

We've failed to take cybersecurity seriously. Now we're paying the piper

3 min read

This has been a banner year for high-profile cybersecurity disasters, with no letup in sight. So far, there have been 251 data breaches—a record-setting pace. Sony's PlayStation and Entertainment Networks have been repeatedly hacked, with more than 100 million of the company's user accounts compromised and its online gaming halted for several weeks. A security breach at the Internet marketing company Epsilon resulted in millions of customers' e-mail addresses being taken from about 100 major corporations, including Disney Destinations in the United States and Dell in Australia. A cyberintrusion at Nonghyup, South Korea's main agricultural cooperative, crashed its banking systems for a week and kept 30 million customers from accessing their accounts. Blackmailers broke into the financial systems of Hyundai Capital, accessed the personal details of 1.75 million customers, and then demanded US $460 000 to keep the purloined information from being made public.

Then there are the targeted attacks against security vendors like Comodo and RSA. A hacker fooled a Comodo group affiliate into issuing Internet SSL certificates to some of the world's largest websites, including Google, Microsoft, Mozilla, Skype, and Yahoo. A partially successful attack against RSA's two-factor authentication security product SecurID, which is used by 30 000 organizations around the world, has led to "significant and tenacious" attacks against a number of major U.S. defense contractors, including the world's largest, Lockheed Martin.

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The Future of Deep Learning Is Photonic

Computing with light could slash the energy needs of neural networks

10 min read
Image of a computer rendering.

This computer rendering depicts the pattern on a photonic chip that the author and his colleagues have devised for performing neural-network calculations using light.

Alexander Sludds

Think of the many tasks to which computers are being applied that in the not-so-distant past required human intuition. Computers routinely identify objects in images, transcribe speech, translate between languages, diagnose medical conditions, play complex games, and drive cars.

The technique that has empowered these stunning developments is called deep learning, a term that refers to mathematical models known as artificial neural networks. Deep learning is a subfield of machine learning, a branch of computer science based on fitting complex models to data.

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