2,125 research outputs found
Naturally Rehearsing Passwords
We introduce quantitative usability and security models to guide the design
of password management schemes --- systematic strategies to help users create
and remember multiple passwords. In the same way that security proofs in
cryptography are based on complexity-theoretic assumptions (e.g., hardness of
factoring and discrete logarithm), we quantify usability by introducing
usability assumptions. In particular, password management relies on assumptions
about human memory, e.g., that a user who follows a particular rehearsal
schedule will successfully maintain the corresponding memory. These assumptions
are informed by research in cognitive science and validated through empirical
studies. Given rehearsal requirements and a user's visitation schedule for each
account, we use the total number of extra rehearsals that the user would have
to do to remember all of his passwords as a measure of the usability of the
password scheme. Our usability model leads us to a key observation: password
reuse benefits users not only by reducing the number of passwords that the user
has to memorize, but more importantly by increasing the natural rehearsal rate
for each password. We also present a security model which accounts for the
complexity of password management with multiple accounts and associated
threats, including online, offline, and plaintext password leak attacks.
Observing that current password management schemes are either insecure or
unusable, we present Shared Cues--- a new scheme in which the underlying secret
is strategically shared across accounts to ensure that most rehearsal
requirements are satisfied naturally while simultaneously providing strong
security. The construction uses the Chinese Remainder Theorem to achieve these
competing goals
Towards Human Computable Passwords
An interesting challenge for the cryptography community is to design
authentication protocols that are so simple that a human can execute them
without relying on a fully trusted computer. We propose several candidate
authentication protocols for a setting in which the human user can only receive
assistance from a semi-trusted computer --- a computer that stores information
and performs computations correctly but does not provide confidentiality. Our
schemes use a semi-trusted computer to store and display public challenges
. The human user memorizes a random secret mapping
and authenticates by computing responses
to a sequence of public challenges where
is a function that is easy for the
human to evaluate. We prove that any statistical adversary needs to sample
challenge-response pairs to recover , for
a security parameter that depends on two key properties of . To
obtain our results, we apply the general hypercontractivity theorem to lower
bound the statistical dimension of the distribution over challenge-response
pairs induced by and . Our lower bounds apply to arbitrary
functions (not just to functions that are easy for a human to evaluate),
and generalize recent results of Feldman et al. As an application, we propose a
family of human computable password functions in which the user
needs to perform primitive operations (e.g., adding two digits or
remembering ), and we show that .
For these schemes, we prove that forging passwords is equivalent to recovering
the secret mapping. Thus, our human computable password schemes can maintain
strong security guarantees even after an adversary has observed the user login
to many different accounts.Comment: Fixed bug in definition of Q^{f,j} and modified proofs accordingl
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MobileTrust: Secure Knowledge Integration in VANETs
Vehicular Ad hoc NETworks (VANET) are becoming popular due to the emergence of the Internet of Things and ambient intelligence applications. In such networks, secure resource sharing functionality is accomplished by incorporating trust schemes. Current solutions adopt peer-to-peer technologies that can cover the large operational area. However, these systems fail to capture some inherent properties of VANETs, such as fast and ephemeral interaction, making robust trust evaluation of crowdsourcing challenging. In this article, we propose MobileTrust—a hybrid trust-based system for secure resource sharing in VANETs. The proposal is a breakthrough in centralized trust computing that utilizes cloud and upcoming 5G technologies to provide robust trust establishment with global scalability. The ad hoc communication is energy-efficient and protects the system against threats that are not countered by the current settings. To evaluate its performance and effectiveness, MobileTrust is modelled in the SUMO simulator and tested on the traffic features of the small-size German city of Eichstatt. Similar schemes are implemented in the same platform to provide a fair comparison. Moreover, MobileTrust is deployed on a typical embedded system platform and applied on a real smart car installation for monitoring traffic and road-state parameters of an urban application. The proposed system is developed under the EU-founded THREAT-ARREST project, to provide security, privacy, and trust in an intelligent and energy-aware transportation scenario, bringing closer the vision of sustainable circular economy
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