We introduce GOTCHAs (Generating panOptic Turing Tests to Tell Computers and Humans Apart) as a way of preventing automated offline dictionary attacks against user selected passwords. A GOTCHA is a randomized puzzle generation protocol, which involves interaction between a computer and a human. Informally, a GOTCHA should satisfy two key properties: (1) The puzzles are easy for the human to solve. (2) The puzzles are hard for a computer to solve even if it has the random bits used by the computer to generate the final puzzle --- unlike a CAPTCHA [44]. Our main theorem demonstrates that GOTCHAs can be used to mitigate the threat of offline dictionary attacks against passwords by ensuring that a password cracker must receive constant feedback from a human being while mounting an attack. Finally, we provide a candidate construction of GOTCHAs based on Inkblot images. Our construction relies on the usability assumption that users can recognize the phrases that they originally used to describe each Inkblot image --- a much weaker usability assumption than previous password systems based on Inkblots which required users to recall their phrase exactly. We conduct a user study to evaluate the usability of our GOTCHA construction. We also generate a GOTCHA challenge where we encourage artificial intelligence and security researchers to try to crack several passwords protected with our scheme.
Users are often advised (or required) to follow strict guidelines when selecting their password (e.g., use a mix of upper lower case letters, include numbers and change the password frequently) @cite_32 . However, empirical studies show that user's are are often frustrated by restricting policies and commonly forget their passwords @cite_6 @cite_7 @cite_8 In fact the resulting passwords are sometimes more vulnerable to an offline attack! @cite_6 @cite_7 . Furthermore, the cost of these restrictive policies can be quite high. For example, a Gartner case study @cite_26 estimated that it cost over $17 per password-reset call. Florencio and Herley @cite_47 studied the economic factors that institutions consider before adopting password policies and found that they often value usability over security.
@cite_26 @cite_7 @cite_8 @cite_32 @cite_6 @cite_47
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We examine the password policies of 75 different websites. Our goal is understand the enormous diversity of requirements: some will accept simple six-character passwords, while others impose rules of great complexity on their users. We compare different features of the sites to find which characteristics are correlated with stronger policies. Our results are surprising: greater security demands do not appear to be a factor. The size of the site, the number of users, the value of the assets protected and the frequency of attacks show no correlation with strength. In fact we find the reverse: some of the largest, most attacked sites with greatest assets allow relatively weak passwords. Instead, we find that those sites that accept advertising, purchase sponsored links and where the user has a choice show strong inverse correlation with strength. We conclude that the sites with the most restrictive password policies do not have greater security concerns, they are simply better insulated from the consequences of poor usability. Online retailers and sites that sell advertising must compete vigorously for users and traffic. In contrast to government and university sites, poor usability is a luxury they cannot afford. This in turn suggests that much of the extra strength demanded by the more restrictive policies is superfluous: it causes considerable inconvenience for negligible security improvement. We report on the largest corpus of user-chosen passwords ever studied, consisting of anonymized password histograms representing almost 70 million Yahoo! users, mitigating privacy concerns while enabling analysis of dozens of subpopulations based on demographic factors and site usage characteristics. This large data set motivates a thorough statistical treatment of estimating guessing difficulty by sampling from a secret distribution. In place of previously used metrics such as Shannon entropy and guessing entropy, which cannot be estimated with any realistically sized sample, we develop partial guessing metrics including a new variant of guesswork parameterized by an attacker's desired success rate. Our new metric is comparatively easy to approximate and directly relevant for security engineering. By comparing password distributions with a uniform distribution which would provide equivalent security against different forms of guessing attack, we estimate that passwords provide fewer than 10 bits of security against an online, trawling attack, and only about 20 bits of security against an optimal offline dictionary attack. We find surprisingly little variation in guessing difficulty; every identifiable group of users generated a comparably weak password distribution. Security motivations such as the registration of a payment card have no greater impact than demographic factors such as age and nationality. Even proactive efforts to nudge users towards better password choices with graphical feedback make little difference. More surprisingly, even seemingly distant language communities choose the same weak passwords and an attacker never gains more than a factor of 2 efficiency gain by switching from the globally optimal dictionary to a population-specific lists. We present a usability study of two recent password manager proposals: PwdHash (, 2005) and Password Multiplier (, 2005). Both papers considered usability issues in greater than typical detail, the former briefly reporting on a small usability study; both also provided implementations for download. Our study involving 26 users found that both proposals suffer from major usability problems. Some of these are not "simply" usability issues, but rather lead directly to security exposures. Not surprisingly, we found the most significant problems arose from users having inaccurate or incomplete mental models of the software. Our study revealed many interesting misunderstandings D for example, users reporting a task as easy even when unsuccessful at completing that task; and believing their passwords were being strengthened when in fact they had failed to engage the appropriate protection mechanism. Our findings also suggested that ordinary users would be reluctant to optin to using these managers: users were uncomfortable with "relinquishing control" of their passwords to a manager, did not feel that they needed the password managers, or that the managers provided greater security. To encourage strong passwords, system administrators employ password-composition policies, such as a traditional policy requiring that passwords have at least 8 characters from 4 character classes and pass a dictionary check. Recent research has suggested, however, that policies requiring longer passwords with fewer additional requirements can be more usable and in some cases more secure than this traditional policy. To explore long passwords in more detail, we conducted an online experiment with 8,143 participants. Using a cracking algorithm modified for longer passwords, we evaluate eight policies across a variety of metrics for strength and usability. Among the longer policies, we discover new evidence for a security usability tradeoff, with none being strictly better than another on both dimensions. However, several policies are both more usable and more secure that the traditional policy we tested. Our analyses additionally reveal common patterns and strings found in cracked passwords. We discuss how system administrators can use these results to improve password-composition policies.