The underlying issues relating to the usability and security of multiple passwords are largely unexplored. However, we know that people generally have difficulty remembering multiple passwords. This reduces security since users reuse the same password for different systems or reveal other passwords as they try to log in. We report on a laboratory study comparing recall of multiple text passwords with recall of multiple click-based graphical passwords. In a one-hour session (short-term), we found that participants in the graphical password condition coped significantly better than those in the text password condition. In particular, they made fewer errors when recalling their passwords, did not resort to creating passwords directly related to account names, and did not use similar passwords across multiple accounts. After two weeks, participants in the two conditions had recall success rates that were not statistically different from each other, but those with text passwords made more recall errors than participants with graphical passwords. In our study, click-based graphical passwords were significantly less susceptible to multiple password interference in the short-term, while having comparable usability to text passwords in most other respects.
Human-memorable passwords are a mainstay of computer security. To decrease vulnerability of passwords to brute-force dictionary attacks, many organizations enforce complicated password-creation rules and require that passwords include numerals and special characters. We demonstrate that as long as passwords remain human-memorable, they are vulnerable to "smart-dictionary" attacks even when the space of potential passwords is large.Our first insight is that the distribution of letters in easy-to-remember passwords is likely to be similar to the distribution of letters in the users' native language. Using standard Markov modeling techniques from natural language processing, this can be used to dramatically reduce the size of the password space to be searched. Our second contribution is an algorithm for efficient enumeration of the remaining password space. This allows application of time-space tradeoff techniques, limiting memory accesses to a relatively small table of "partial dictionary" sizes and enabling a very fast dictionary attack.We evaluated our method on a database of real-world user password hashes. Our algorithm successfully recovered 67.6% of the passwords using a 2 x 109 search space. This is a much higher percentage than Oechslin's "rainbow" attack, which is the fastest currently known technique for searching large keyspaces. These results call into question viability of human-memorable character-sequence passwords as an authentication mechanism.
Text-based passwords are the most common mechanism for authenticating humans to computer systems. To prevent users from picking passwords that are too easy for an adversary to guess, system administrators adopt password-composition policies (e.g., requiring passwords to contain symbols and numbers). Unfortunately, little is known about the relationship between password-composition policies and the strength of the resulting passwords, or about the behavior of users (e.g., writing down passwords) in response to different policies. We present a large-scale study that investigates password strength, user behavior, and user sentiment across four password-composition policies. We characterize the predictability of passwords by calculating their entropy, and find that a number of commonly held beliefs about password composition and strength are inaccurate. We correlate our results with user behavior and sentiment to produce several recommendations for password-composition policies that result in strong passwords without unduly burdening users.
The most common computer authentication method is to use alphanumerical usernames and passwords. This method has been shown to have significant drawbacks. For example, users tend to pick passwords that can be easily guessed. On the other hand, if a password is hard to guess, then it is often hard to remember. To address this problem, some researchers have developed authentication methods that use pictures as passwords. In this paper, we conduct a comprehensive survey of the existing graphical password techniques. We classify these techniques into two categories: recognition-based and recall-based approaches. We discuss the strengths and limitations of each method and point out the future research directions in this area. We also try to answer two important questions: "Are graphical passwords as secure as text-based passwords?"; "What are the major design and implementation issues for graphical passwords?" This survey will be useful for information security researchers and practitioners who are interested in finding an alternative to text-based authentication methods
Abstract A survey evaluating the generation and use of passwords revealed that students have 8.18 password uses. With 4.45 different passwords to cover these functions, the average password has 1.84 applications. Two thirds of passwords are designed around one's personal characteristics, with most of the remainder relating to relatives, friends or lovers. Proper names and birthdays are the primary information used in constructing passwords, accounting for about half of all password constructions. Almost all respondents reuse passwords, and about two thirds of password uses are duplications. Passwords have been forgotten by a third of respondents, and over half keep a written record of them. We found empirical confirmation of some ‘bad password practices’ discussed in the literature, and provide suggestions for password construction and use. Copyright © 2004 John Wiley & Sons, Ltd.
We evaluate two decades of proposals to replace text passwords for general-purpose user authentication on the web using a broad set of twenty-five usability, deployability and security benefits that an ideal scheme might provide. The scope of proposals we survey is also extensive, including password management software, federated login protocols, graphical password schemes, cognitive authentication schemes, one-time passwords, hardware tokens, phone-aided schemes and biometrics. Our comprehensive approach leads to key insights about the difficulty of replacing passwords. Not only does no known scheme come close to providing all desired benefits: none even retains the full set of benefits that legacy passwords already provide. In particular, there is a wide range from schemes offering minor security benefits beyond legacy passwords, to those offering significant security benefits in return for being more costly to deploy or more difficult to use. We conclude that many academic proposals have failed to gain traction because researchers rarely consider a sufficiently wide range of real-world constraints. Beyond our analysis of current schemes, our framework provides an evaluation methodology and benchmark for future web authentication proposals.
Despite three decades of intensive research efforts, it remains an open question as to what is the underlying distribution of user-generated passwords. In this paper, we make a substantial step forward toward understanding this foundational question. By introducing a number of computational statistical techniques and based on 14 large-scale data sets, which consist of 113.3 million real-world passwords, we, for the first time, propose two Zipf-like models (i.e., PDF-Zipf and CDF-Zipf) to characterize the distribution of passwords. More specifically, our PDF-Zipf model can well fit the popular passwords and obtain a coefficient of determination larger than 0.97; our CDF-Zipf model can well fit the entire password data set, with the maximum cumulative distribution function (CDF) deviation between the empirical distribution and the fitted theoretical model being 0.49%~4.59% (on an average 1.85%). With the concrete knowledge of password distributions, we suggest a new metric for measuring the strength of password data sets. Extensive experimental results show the effectiveness and general applicability of the proposed Zipf-like models and security metric.
Despite countless attempts and near-universal desire to replace them, passwords are more widely used and firmly entrenched than ever. The authors' exploration leads them to argue that no silver bullet will meet all requirements-not only will passwords be with us for some time, but in many instances, they're the solution that best fits the scenario of use. Among broad authentication research directions to follow, they first suggest better means to concretely identify actual requirements (surprisingly overlooked to date) and weight their relative importance in target scenarios. Second, for scenarios where passwords appear to be the best-fit solution, they suggest designing better means to support them. The authors also highlight the need for more systematic research and how the premature conclusion that passwords are dead has led to the neglect of important research questions.
In this paper we propose and evaluate new graphical password schemes that exploit features of graphical input displays to achieve better security than text-based passwords. Graphical input devices enable the user to decouple the position of inputs from the temporal order in which those inputs occur, and we show that this decoupling can be used to generate password schemes with substantially larger #memorable# password spaces. In order to evaluate the security of one of our schemes, we devise a novel way to capture a subset of the #memorable" passwords that, we believe, is itself a contribution. In this work we are primarily motivated by devices such as personal digital assistants #PDAs# that o#er graphical input capabilities via a stylus, and we describe our prototype implementation of one of our password schemes on suchaPDA, namely the Palm Pilot TM . 1 Introduction For the vast majority of computer systems, passwords are the method of choice for authenticating users. It ...
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.
In this paper we attempt to determine the effectiveness of using entropy, as defined in NIST SP800-63, as a measurement of the security provided by various password creation policies. This is accomplished by modeling the success rate of current password cracking techniques against real user passwords. These data sets were collected from several different websites, the largest one containing over 32 million passwords. This focus on actual attack methodologies and real user passwords quite possibly makes this one of the largest studies on password security to date. In addition we examine what these results mean for standard password creation policies, such as minimum password length, and character set requirements.
The use of passwords is a major point of vulnerability in computer security, as passwords are often easy to guess by automated programs running dictionary attacks. Passwords remain the most widely used authentication method despite their well-known security weaknesses. User authentication is clearly a practical problem. From the perspective of a service provider this problem needs to be solved within real-world constraints such as the available hardware and software infrastructures. From a user's perspective user-friendliness is a key requirement.In this paper we suggest a novel authentication scheme that preserves the advantages of conventional password authentication, while simultaneously raising the costs of online dictionary attacks by orders of magnitude. The proposed scheme is easy to implement and overcomes some of the difficulties of previously suggested methods of improving the security of user authentication schemes.Our key idea is to efficiently combine traditional password authentication with a challenge that is very easy to answer by human users, but is (almost) infeasible for automated programs attempting to run dictionary attacks. This is done without affecting the usability of the system. The proposed scheme also provides better protection against denial of service attacks against user accounts.
For decades, the password has been the standard means for user authentication on computers. However, as users are required to remember more, longer, and changing passwords, it is evident that a more convenient and secure solution to user authentication is necessary. This paper examines passwords, security tokens, and biometrics-which we collectively call authenticators-and compares these authenticators and their combinations. We examine their effectiveness against several attacks and suitability for particular security specifications such as compromise detection and nonrepudiation. Examples of authenticator combinations and protocols are described to show tradeoffs and solutions that meet chosen, practical requirements. The paper endeavors to offer a comprehensive picture of user authentication solutions for the purposes of evaluating options for use and identifying deficiencies requiring further research.
Graphical passwords are an alternative to alphanumeric passwords in which users click on images to authenticate themselves rather than type alphanumeric strings. We have developed one such system, called PassPoints, and evaluated it with human users. The results of the evaluation were promising with respect to rmemorability of the graphical password. In this study we expand our human factors testing by studying two issues: the effect of tolerance, or margin of error, in clicking on the password points and the effect of the image used in the password system. In our tolerance study, results show that accurate memory for the password is strongly reduced when using a small tolerance (10 x 10 pixels) around the user's password points. This may occur because users fail to encode the password points in memory in the precise manner that is necessary to remember the password over a lapse of time. In our image study we compared user performance on four everyday images. The results indicate that there were few significant differences in performance of the images. This preliminary result suggests that many images may support memorability in graphical password systems.
Starting around 1999, a great many graphical password schemes have been proposed as alternatives to text-based password authentication. We provide a comprehensive overview of published research in the area, covering both usability and security aspects as well as system evaluation. The article first catalogues existing approaches, highlighting novel features of selected schemes and identifying key usability or security advantages. We then review usability requirements for knowledge-based authentication as they apply to graphical passwords, identify security threats that such systems must address and review known attacks, discuss methodological issues related to empirical evaluation, and identify areas for further research and improved methodology.
Theory on passwords has lagged practice, where large providers use back-end smarts to survive with imperfect technology.
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Given the widespread use of password authentication in online correspondence, subscription services, and shopping, there is growing concern about identity theft. When people reuse their passwords across multiple accounts, they increase their vulnerability; compromising one password can help an attacker take over several accounts. Our study of 49 undergraduates quantifies how many passwords they had and how often they reused these passwords. The majority of users had three or fewer passwords and passwords were reused twice. Furthermore, over time, password reuse rates increased because people accumulated more accounts but did not create more passwords. Users justified their habits. While they wanted to protect financial data and personal communication, reusing passwords made passwords easier to manage. Users visualized threats from human attackers, particularly viewing those close to them as the most motivated and able attackers; however, participants did not separate the human attackers from their potentially automated tools. They sometimes failed to realize that personalized passwords such as phone numbers can be cracked given a large enough dictionary and enough tries. We discuss how current systems support poor password practices. We also present potential changes in website authentication systems and password managers.
Text-based passwords remain the dominant authentication method in computer systems, despite significant advancement in attackers' capabilities to perform password cracking. In response to this threat, password composition policies have grown increasingly complex. However, there is insufficient research defining metrics to characterize password strength and using them to evaluate password-composition policies. In this paper, we analyze 12,000 passwords collected under seven composition policies via an online study. We develop an efficient distributed method for calculating how effectively several heuristic password-guessing algorithms guess passwords. Leveraging this method, we investigate (a) the resistance of passwords created under different conditions to guessing, (b) the performance of guessing algorithms under different training sets, (c) the relationship between passwords explicitly created under a given composition policy and other passwords that happen to meet the same requirements, and (d) the relationship between guess ability, as measured with password-cracking algorithms, and entropy estimates. Our findings advance understanding of both password-composition policies and metrics for quantifying password security.