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Are machines ready to break down language barriers?
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INSIGHT Online translation services learn to bridge the language gap
of malware built with Zeus, another layer of cybercrime activity is devoted to finding ways to bypass those protections. To check whether a piece of malware is on the security companies’ blacklists, hackers can send their creations to websites such as virtest.com, which for just $1 will try the code out on more than 20 antivirus products. If the malware fails the test, would-be criminals can simply upload their malware to another site that will tweak it to render it unrecognisable. The online security industry is warning that this profileration of “malware as a service” products is likely to result in far more potent attacks. There is already anecdotal evidence that hackers are paying more attention to company rather than personal bank accounts, for example, and to breaching government computers, says Villeneuve. ■
translation research at Google. His team’s Translate service can currently operate between 52 different languages and he is aiming to add more, especially those previously ignored by machine translators. “A speaker of Bengali can only experience a tiny fraction of a per cent of the web,” says Och. Though translation algorithms have improved, some human intervention is still needed to provide a translation that reads well. Meedan’s news articles, for example, are machine translated and then tidied up by editors. Google’s Toolkit for professional translators produces a machine translation for them to tidy up, in the process providing feedback to the software to improve its translation capabilities. With the right help even someone that speaks only a single language could produce results as good as those of a professional, says Philipp Koehn of the University of Edinburgh, UK. His service, Caitra, outputs several possible phrases if it is uncertain which one is correct. This lets a monoglot user fix garbled phrases that would otherwise be unfathomable without reading the original. Tom Simonite ■ Can’t understand a word of it? Try getting it translated online CULTURA/GETTY
If it finds a way in, Fragus can be programmed to covertly send a piece of Zeus-created malware to the visitor’s computer. This allows hackers to sell malware installation as a service to less skilled criminals. Fragus also delivers feedback on which browsers it has cracked and where the users of those browsers are based. “That data can be used to target a particular country,” says Henry Stern, a colleague of Peterson’s at Cisco. Stern says he is currently aware of a few dozen websites infected by Fragus, and that it had previously been used to deliver malware to people accessing websites belonging to a widely read US newspaper. Zeus and Fragus can be reined in (see “Hitting back at hackers”), but even here the malware service industry is trying to stay one step ahead. So while many companies provide software that, for example, can detect the presence
EVEN in an era of global networks and cheap travel, international communication still faces one great barrier: we don’t all speak the same language. But that gap is narrowing as online translation services advance. Recently launched website Meedan translates Arabic-language news stories into English, and vice versa, and displays the two versions alongside each other. Comments in either language are instantly translated. A new site for bloggers, called Mojofiti, automatically makes posts available to readers in 27 languages. And Google now has a tool that will eventually allow anyone with a camera-phone to photograph, say, a German restaurant menu, send the image as a multimedia message to Google’s servers, and get an English translation sent back to them. All these services ultimately rely on a technique called statistical machine translation, in which software learns to translate by using brute mathematics to compare large collections of previously translated documents. It then uses the rules it has learned this way to determine the most likely translation in future. “Whenever there is a possibility of the language barrier preventing someone from doing something there should be the possibility to translate,” says Franz Och, who leads machine
20 March 2010 | NewScientist | 21
INSIGHT Online translation services learn to bridge the language gap
of malware built with Zeus, another layer of cybercrime activity is devoted to finding ways to bypass those protections. To check whether a piece of malware is on the security companies’ blacklists, hackers can send their creations to websites such as virtest.com, which for just $1 will try the code out on more than 20 antivirus products. If the malware fails the test, would-be criminals can simply upload their malware to another site that will tweak it to render it unrecognisable. The online security industry is warning that this profileration of “malware as a service” products is likely to result in far more potent attacks. There is already anecdotal evidence that hackers are paying more attention to company rather than personal bank accounts, for example, and to breaching government computers, says Villeneuve. ■
translation research at Google. His team’s Translate service can currently operate between 52 different languages and he is aiming to add more, especially those previously ignored by machine translators. “A speaker of Bengali can only experience a tiny fraction of a per cent of the web,” says Och. Though translation algorithms have improved, some human intervention is still needed to provide a translation that reads well. Meedan’s news articles, for example, are machine translated and then tidied up by editors. Google’s Toolkit for professional translators produces a machine translation for them to tidy up, in the process providing feedback to the software to improve its translation capabilities. With the right help even someone that speaks only a single language could produce results as good as those of a professional, says Philipp Koehn of the University of Edinburgh, UK. His service, Caitra, outputs several possible phrases if it is uncertain which one is correct. This lets a monoglot user fix garbled phrases that would otherwise be unfathomable without reading the original. Tom Simonite ■ Can’t understand a word of it? Try getting it translated online CULTURA/GETTY
If it finds a way in, Fragus can be programmed to covertly send a piece of Zeus-created malware to the visitor’s computer. This allows hackers to sell malware installation as a service to less skilled criminals. Fragus also delivers feedback on which browsers it has cracked and where the users of those browsers are based. “That data can be used to target a particular country,” says Henry Stern, a colleague of Peterson’s at Cisco. Stern says he is currently aware of a few dozen websites infected by Fragus, and that it had previously been used to deliver malware to people accessing websites belonging to a widely read US newspaper. Zeus and Fragus can be reined in (see “Hitting back at hackers”), but even here the malware service industry is trying to stay one step ahead. So while many companies provide software that, for example, can detect the presence
EVEN in an era of global networks and cheap travel, international communication still faces one great barrier: we don’t all speak the same language. But that gap is narrowing as online translation services advance. Recently launched website Meedan translates Arabic-language news stories into English, and vice versa, and displays the two versions alongside each other. Comments in either language are instantly translated. A new site for bloggers, called Mojofiti, automatically makes posts available to readers in 27 languages. And Google now has a tool that will eventually allow anyone with a camera-phone to photograph, say, a German restaurant menu, send the image as a multimedia message to Google’s servers, and get an English translation sent back to them. All these services ultimately rely on a technique called statistical machine translation, in which software learns to translate by using brute mathematics to compare large collections of previously translated documents. It then uses the rules it has learned this way to determine the most likely translation in future. “Whenever there is a possibility of the language barrier preventing someone from doing something there should be the possibility to translate,” says Franz Och, who leads machine
20 March 2010 | NewScientist | 21