35,451 research outputs found
Improved Anonymity for Key-Trees
Randomized hash-lock protocols for Radio Frequency IDentification (RFID) tags offer forward untraceability, but incur heavy search on the server. Key trees have been proposed as a way to reduce
search times, but because partial keys in such trees are shared, key compromise affects several tags. Buttyän et al. have quantified the resulting loss of anonymity in the system, and proposed specific tree properties in an attempt to minimize this loss. We will further improve upon these results, and provide a proof of optimality. Finally, our proposals are compared to existing results by means of simulation
AnonPri: A Secure Anonymous Private Authentication Protocol for RFID Systems
Privacy preservation in RFID systems is a very important issue in modern day world. Privacy activists have been worried about the invasion of user privacy while using various RFID systems and services. Hence, significant efforts have been made to design RFID systems that preserve users\u27 privacy. Majority of the privacy preserving protocols for RFID systems require the reader to search all tags in the system in order to identify a single RFID tag which not efficient for large scale systems. In order to achieve high-speed authentication in large-scale RFID systems, researchers propose tree-based approaches, in which any pair of tags share a number of key components. Another technique is to perform group-based authentication that improves the tradeoff between scalability and privacy by dividing the tags into a number of groups. This novel authentication scheme ensures privacy of the tags. However, the level of privacy provided by the scheme decreases as more and more tags are compromised. To address this issue, in this paper, we propose a group based anonymous private authentication protocol (AnonPri) that provides higher level of privacy than the above mentioned group based scheme and achieves better efficiency (in terms of providing privacy) than the approaches that prompt the reader to perform an exhaustive search. Our protocol guarantees that the adversary cannot link the tag responses even if she can learn the identifier of the tags. Our evaluation results demonstrates that the level of privacy provided by AnonPri is higher than that of the group based authentication technique
AnonPri: A Secure Anonymous Private Authentication Protocol for RFID Systems
Privacy preservation in RFID systems is a very important issue in modern day world. Privacy activists have been worried about the invasion of user privacy while using various RFID systems and services. Hence, significant efforts have been made to design RFID systems that preserve users\u27 privacy. Majority of the privacy preserving protocols for RFID systems require the reader to search all tags in the system in order to identify a single RFID tag which not efficient for large scale systems. In order to achieve high-speed authentication in large-scale RFID systems, researchers propose tree-based approaches, in which any pair of tags share a number of key components. Another technique is to perform group-based authentication that improves the tradeoff between scalability and privacy by dividing the tags into a number of groups. This novel authentication scheme ensures privacy of the tags. However, the level of privacy provided by the scheme decreases as more and more tags are compromised. To address this issue, in this paper, we propose a group based anonymous private authentication protocol (AnonPri) that provides higher level of privacy than the above mentioned group based scheme and achieves better efficiency (in terms of providing privacy) than the approaches that prompt the reader to perform an exhaustive search. Our protocol guarantees that the adversary cannot link the tag responses even if she can learn the identifier of the tags. Our evaluation results demonstrates that the level of privacy provided by AnonPri is higher than that of the group based authentication technique
Lattice-Based Group Signatures: Achieving Full Dynamicity (and Deniability) with Ease
In this work, we provide the first lattice-based group signature that offers
full dynamicity (i.e., users have the flexibility in joining and leaving the
group), and thus, resolve a prominent open problem posed by previous works.
Moreover, we achieve this non-trivial feat in a relatively simple manner.
Starting with Libert et al.'s fully static construction (Eurocrypt 2016) -
which is arguably the most efficient lattice-based group signature to date, we
introduce simple-but-insightful tweaks that allow to upgrade it directly into
the fully dynamic setting. More startlingly, our scheme even produces slightly
shorter signatures than the former, thanks to an adaptation of a technique
proposed by Ling et al. (PKC 2013), allowing to prove inequalities in
zero-knowledge. Our design approach consists of upgrading Libert et al.'s
static construction (EUROCRYPT 2016) - which is arguably the most efficient
lattice-based group signature to date - into the fully dynamic setting.
Somewhat surprisingly, our scheme produces slightly shorter signatures than the
former, thanks to a new technique for proving inequality in zero-knowledge
without relying on any inequality check. The scheme satisfies the strong
security requirements of Bootle et al.'s model (ACNS 2016), under the Short
Integer Solution (SIS) and the Learning With Errors (LWE) assumptions.
Furthermore, we demonstrate how to equip the obtained group signature scheme
with the deniability functionality in a simple way. This attractive
functionality, put forward by Ishida et al. (CANS 2016), enables the tracing
authority to provide an evidence that a given user is not the owner of a
signature in question. In the process, we design a zero-knowledge protocol for
proving that a given LWE ciphertext does not decrypt to a particular message
Routes for breaching and protecting genetic privacy
We are entering the era of ubiquitous genetic information for research,
clinical care, and personal curiosity. Sharing these datasets is vital for
rapid progress in understanding the genetic basis of human diseases. However,
one growing concern is the ability to protect the genetic privacy of the data
originators. Here, we technically map threats to genetic privacy and discuss
potential mitigation strategies for privacy-preserving dissemination of genetic
data.Comment: Draft for comment
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