5,136 research outputs found

    Nudging folks towards stronger password choices:providing certainty is the key

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    Persuading people to choose strong passwords is challenging. One way to influence password strength, as and when people are making the choice, is to tweak the choice architecture to encourage stronger choice. A variety of choice architecture manipulations i.e. “nudges”, have been trialled by researchers with a view to strengthening the overall password profile. None has made much of a difference so far. Here we report on our design of an influential behavioural intervention tailored to the password choice context: a hybrid nudge that significantly prompted stronger passwords.We carried out three longitudinal studies to analyse the efficacy of a range of “nudges” by manipulating the password choice architecture of an actual university web application. The first and second studies tested the efficacy of several simple visual framing “nudges”. Password strength did not budge. The third study tested expiration dates directly linked to password strength. This manipulation delivered a positive result: significantly longer and stronger passwords. Our main conclusion was that the final successful nudge provided participants with absolute certainty as to the benefit of a stronger password, and that it was this certainty that made the difference

    Gamification techniques for raising cyber security awareness

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    Due to the prevalence of online services in modern society, such as internet banking and social media, it is important for users to have an understanding of basic security measures in order to keep themselves safe online. However, users often do not know how to make their online interactions secure, which demonstrates an educational need in this area. Gamification has grown in popularity in recent years and has been used to teach people about a range of subjects. This paper presents an exploratory study investigating the use of gamification techniques to educate average users about password security, with the aim of raising overall security awareness. To explore the impact of such techniques, a role-playing quiz application (RPG) was developed for the Android platform to educate users about password security. Results gained from the work highlightedthat users enjoyed learning via the use of the password application, and felt they benefitted from the inclusion of gamification techniques. Future work seeks to expand the prototype into a full solution, covering a range of security awareness issues

    Guidelines for ethical nudging in password authentication

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    Nudging has been adopted by many disciplines in the last decade in order to achieve behavioural change. Information security is no exception. A number of attempts have been made to nudge end-users towards stronger passwords. Here we report on our deployment of an enriched nudge displayed to participants on the system enrolment page, when a password has to be chosen. The enriched nudge was successful in that participants chose significantly longer and stronger passwords. One thing that struck us as we designed and tested this nudge was that we were unable to find any nudge-specific ethical guidelines to inform our experimentation in this context. This led us to reflect on the ethical implications of nudge testing, specifically in the password authentication context. We mined the nudge literature and derived a number of core principles of ethical nudging. We tailored these to the password authentication context, and then show how they can be applied by assessing the ethics of our own nudge. We conclude with a set of preliminary guidelines derived from our study to inform other researchers planning to deploy nudge-related techniques in this context

    Case study:exploring children’s password knowledge and practices

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    Children use technology from a very young age, and often have to authenticate themselves. Yet very little attention has been paid to designing authentication specifically for this particular target group. The usual practice is to deploy the ubiquitous password, and this might well be a suboptimal choice. Designing authentication for children requires acknowledgement of child-specific developmental challenges related to literacy, cognitive abilities and differing developmental stages. Understanding the current state of play is essential, to deliver insights that can inform the development of child-centred authentication mechanisms and processes. We carried out a systematic literature review of all research related to children and authentication since 2000. A distinct research gap emerged from the analysis. Thus, we designed and administered a survey to school children in the United States (US), so as to gain insights into their current password usage and behaviors. This paper reports preliminary results from a case study of 189 children (part of a much larger research effort). The findings highlight age-related differences in children’s password understanding and practices. We also discovered that children confuse concepts of safety and security. We conclude by suggesting directions for future research. This paper reports on work in progress.<br/

    Ethical guidelines for nudging in information security &amp; privacy

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    There has recently been an upsurge of interest in the deployment of behavioural economics techniques in the information security and privacy domain. In this paper, we consider first the nature of one particular intervention, the nudge, and the way it exercises its influence. We contemplate the ethical ramifications of nudging, in its broadest sense, deriving general principles for ethical nudging from the literature. We extrapolate these principles to the deployment of nudging in information security and privacy. We explain how researchers can use these guidelines to ensure that they satisfy the ethical requirements during nudge trials in information security and privacy. Our guidelines also provide guidance to ethics review boards that are required to evaluate nudge-related research

    Universal Neural-Cracking-Machines: Self-Configurable Password Models from Auxiliary Data

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    We develop the first universal password model -- a password model that, once pre-trained, can automatically adapt to any password distribution. To achieve this result, the model does not need to access any plaintext passwords from the target set. Instead, it exploits users' auxiliary information, such as email addresses, as a proxy signal to predict the underlying target password distribution. The model uses deep learning to capture the correlation between the auxiliary data of a group of users (e.g., users of a web application) and their passwords. It then exploits those patterns to create a tailored password model for the target community at inference time. No further training steps, targeted data collection, or prior knowledge of the community's password distribution is required. Besides defining a new state-of-the-art for password strength estimation, our model enables any end-user (e.g., system administrators) to autonomously generate tailored password models for their systems without the often unworkable requirement of collecting suitable training data and fitting the underlying password model. Ultimately, our framework enables the democratization of well-calibrated password models to the community, addressing a major challenge in the deployment of password security solutions on a large scale.Comment: v0.0

    A Survey on Password Guessing

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    Text password has served as the most popular method for user authentication so far, and is not likely to be totally replaced in foreseeable future. Password authentication offers several desirable properties (e.g., low-cost, highly available, easy-to-implement, reusable). However, it suffers from a critical security issue mainly caused by the inability to memorize complicated strings of humans. Users tend to choose easy-to-remember passwords which are not uniformly distributed in the key space. Thus, user-selected passwords are susceptible to guessing attacks. In order to encourage and support users to use strong passwords, it is necessary to simulate automated password guessing methods to determine the passwords' strength and identify weak passwords. A large number of password guessing models have been proposed in the literature. However, little attention was paid to the task of providing a systematic survey which is necessary to review the state-of-the-art approaches, identify gaps, and avoid duplicate studies. Motivated by that, we conduct a comprehensive survey on all password guessing studies presented in the literature from 1979 to 2022. We propose a generic methodology map to present an overview of existing methods. Then, we explain each representative approach in detail. The experimental procedures and available datasets used to evaluate password guessing models are summarized, and the reported performances of representative studies are compared. Finally, the current limitations and the open problems as future research directions are discussed. We believe that this survey is helpful to both experts and newcomers who are interested in password securityComment: 35 pages, 5 figures, 5 table
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