History Stealing: It’s All Shades of Grey

March 9, 2010 at 7:33 am 4 comments

Previous articles in this series showed that ‘Ubercookies’ can enable websites to learn the identity of any visitor by exploiting the ‘history stealing’ bug in web browsers, and presented different types of de-anonymization attacks. This article is all about the question, “but who is the adversary?”

Good and evil. It is tempting for security researchers to think of the world in terms of good guys and bad guys — white hats and black hats. It is a view of the world that is probably hardwired into our brains, reflected everywhere from religious beliefs to Hollywood plots. But reality is more complex. Heroes are flawed, and the bad guys are not really evil. But enough with the moral lecture, let’s see how this pertains to history stealing and identity stealing.

Black hat. I don’t need to say very much to convince you of the black-hat uses of learning your identity. I’ve already talked about how a phishing site that knows who you are can deliver a customized page that is dramatically more effective. Or imagine the potential for surveillance — with the cooperation of a single ad network, a Government can put a de-anonymization script on millions of websites and keep tabs on every click anyone makes. In fact, you only need to be de-anonymized once; regular tracking scripts will do the job after that.

Grey hat. But I want to argue here that the grey hat use case is far more likely/common than the black hat. For example, here’s an article arguing that websites should sniff their visitors’ history for a “better user experience.” The nonchalant way in which the author talks about exploiting a nasty bug and the lack of mention of any privacy concerns is both scary and amusing. In the comments section of that article you can find links to implementations. In fact there’s even a website selling history sniffing code that website owners can drop into their site.

Shades of grey. Consider a thought experiment. Suppose a website delivered a “better user experience” by sniffing your history, but didn’t send that information back to the server. Whatever web page customization happens is done purely in the browser using Javascript. Is that unethical? If you think it’s unethical, what about if the site popped up a box to get the user’s consent before doing so? Remember that 80% of users are going to click OK without understanding what the box says. At this point it’s looking pretty close to Adnostic, a paper/project I’ve been working on as a privacy enhancing tool.

My point here is not to defend history stealing. Rather, I hope I’ve convinced you that there’s a gentle gradient between white and black hat, at least in terms of intent, and that it’s hard to condemn someone unequivocally.

Incentive. For the most part, people who are using history sniffing “in the wild” are just trying to make an extra buck on their website through advertising. This is an extremely powerful incentive. You may not know how terrible ad targeting currently is on the web. You can find any number of horror stories like this one from Stack Overflow that says a million pageviews a day aren’t enough to pay one person part time. Anything that improves ad rates directly impacts the bottom line.

Now consider this:

The future of Internet ad targeting may lie in combining online and offline behavioral data. Several Web networks have already formed relationships with, or purchased, offline database companies. AdForce has a relationship with Experion, which has an offline database of about 120 million households in North America; likewise, DoubleClick purchased Abacus Direct, a shared catalog database with information on over 90 million U.S. households. 24/7 Media has also formed an alliance to link online and offline data.

Linking online and offline data means one thing: being able to not only track users online but also identify them. Hundreds of millions of dollars say this is going to happen one way or the other.

Some grey hat use cases. The “improved user experience” article linked above advocates history stealing for picking the right third party service providers to direct the user to by detecting which one they are already using – the right RSS reader, social bookmarking site, federated identity provider, mapping service, etc. But let’s talk about identity stealing instead of just history stealing.

Ad targeting, which I’ve already mentioned, can be improved not just by combining online with offline data but also by combining social network profile data with click tracking data. This may already be happening on some social networking sites, but identity stealing makes it possible to grab the user’s social network profile information no matter which site they’re on.

As I pointed out earlier, users are more likely to fall for phishing when the site addresses them by name. But this effect is not in any way specific to phishing. Any new site that wants to get users to try their service or to stick around longer can benefit from this technique to improve trust. Marketers have long absorbed Dale Carnegie’s wisdom that the sweetest word you can say to a person is their own name.

Grey hat is more worrisome than black hat. There are two reasons to worry about grey hat more than black hat. Every website that doesn’t have a reputation to lose is a potential user of grey hat techniques, whether history stealing or anything else. Second, grey hats are typically not using it for anything illegal (unlike phishers), which means you can’t use the law to shut them down.

This is a general thought that I want to leave computer security researchers. We are used to thinking of adversaries as malicious agents; this thinking has been reinforced by the fact that in the last decade or two, hacking went from harmless pranks to organized crime. But the nature of the adversary who exploits privacy flaws is very different from the case of data security breaches. It is important to keep this distinction in mind to be able to develop effective responses.

The role of the browser. In the next article, I will take a broader look at identity and anonymity on the Web, and discuss the role that browsers are going to play in dictating the default level of identity in the years to come.

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Data Privacy: The Story of a Paradigm Shift An open letter to Netflix from the authors of the de-anonymization paper

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About 33bits.org

I’m an associate professor of computer science at Princeton. I research (and teach) information privacy and security, and moonlight in technology policy.

This is a blog about my research on breaking data anonymization, and more broadly about information privacy, law and policy.

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