452 research outputs found
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
A Privacy Preserving Framework for RFID Based Healthcare Systems
RFID (Radio Frequency IDentification) is anticipated to be a core technology that will be used in many practical applications of our life in near future. It has received considerable attention within the healthcare for almost a decade now. The technology’s promise to efficiently track hospital supplies, medical equipment, medications and patients is an attractive proposition to the healthcare industry. However, the prospect of wide spread use of RFID tags in the healthcare area has also triggered discussions regarding privacy, particularly because RFID data in transit may easily be intercepted and can be send to track its user (owner). In a nutshell, this technology has not really seen its true potential in healthcare industry since privacy concerns raised by the tag bearers are not properly addressed by existing identification techniques. There are two major types of privacy preservation techniques that are required in an RFID based healthcare system—(1) a privacy preserving authentication protocol is required while sensing RFID tags for different identification and monitoring purposes, and (2) a privacy preserving access control mechanism is required to restrict unauthorized access of private information while providing healthcare services using the tag ID. In this paper, we propose a framework (PriSens-HSAC) that makes an effort to address the above mentioned two privacy issues. To the best of our knowledge, it is the first framework to provide increased privacy in RFID based healthcare systems, using RFID authentication along with access control technique
Data Minimisation in Communication Protocols: A Formal Analysis Framework and Application to Identity Management
With the growing amount of personal information exchanged over the Internet,
privacy is becoming more and more a concern for users. One of the key
principles in protecting privacy is data minimisation. This principle requires
that only the minimum amount of information necessary to accomplish a certain
goal is collected and processed. "Privacy-enhancing" communication protocols
have been proposed to guarantee data minimisation in a wide range of
applications. However, currently there is no satisfactory way to assess and
compare the privacy they offer in a precise way: existing analyses are either
too informal and high-level, or specific for one particular system. In this
work, we propose a general formal framework to analyse and compare
communication protocols with respect to privacy by data minimisation. Privacy
requirements are formalised independent of a particular protocol in terms of
the knowledge of (coalitions of) actors in a three-layer model of personal
information. These requirements are then verified automatically for particular
protocols by computing this knowledge from a description of their
communication. We validate our framework in an identity management (IdM) case
study. As IdM systems are used more and more to satisfy the increasing need for
reliable on-line identification and authentication, privacy is becoming an
increasingly critical issue. We use our framework to analyse and compare four
identity management systems. Finally, we discuss the completeness and
(re)usability of the proposed framework
Systematizing Decentralization and Privacy: Lessons from 15 Years of Research and Deployments
Decentralized systems are a subset of distributed systems where multiple
authorities control different components and no authority is fully trusted by
all. This implies that any component in a decentralized system is potentially
adversarial. We revise fifteen years of research on decentralization and
privacy, and provide an overview of key systems, as well as key insights for
designers of future systems. We show that decentralized designs can enhance
privacy, integrity, and availability but also require careful trade-offs in
terms of system complexity, properties provided, and degree of
decentralization. These trade-offs need to be understood and navigated by
designers. We argue that a combination of insights from cryptography,
distributed systems, and mechanism design, aligned with the development of
adequate incentives, are necessary to build scalable and successful
privacy-preserving decentralized systems
Technical Privacy Metrics: a Systematic Survey
The file attached to this record is the author's final peer reviewed versionThe goal of privacy metrics is to measure the degree of privacy enjoyed by users in a system and the amount of protection offered by privacy-enhancing technologies. In this way, privacy metrics contribute to improving user privacy in the digital world. The diversity and complexity of privacy metrics in the literature makes an informed choice of metrics challenging. As a result, instead of using existing metrics, new metrics are proposed frequently, and privacy studies are often incomparable. In this survey we alleviate these problems by structuring the landscape of privacy metrics. To this end, we explain and discuss a selection of over eighty privacy metrics and introduce categorizations based on the aspect of privacy they measure, their required inputs, and the type of data that needs protection. In addition, we present a method on how to choose privacy metrics based on nine questions that help identify the right privacy metrics for a given scenario, and highlight topics where additional work on privacy metrics is needed. Our survey spans multiple privacy domains and can be understood as a general framework for privacy measurement
Who clicks there!: Anonymizing the photographer in a camera saturated society
In recent years, social media has played an increasingly important role in
reporting world events. The publication of crowd-sourced photographs and videos
in near real-time is one of the reasons behind the high impact. However, the
use of a camera can draw the photographer into a situation of conflict.
Examples include the use of cameras by regulators collecting evidence of Mafia
operations; citizens collecting evidence of corruption at a public service
outlet; and political dissidents protesting at public rallies. In all these
cases, the published images contain fairly unambiguous clues about the location
of the photographer (scene viewpoint information). In the presence of adversary
operated cameras, it can be easy to identify the photographer by also combining
leaked information from the photographs themselves. We call this the camera
location detection attack. We propose and review defense techniques against
such attacks. Defenses such as image obfuscation techniques do not protect
camera-location information; current anonymous publication technologies do not
help either. However, the use of view synthesis algorithms could be a promising
step in the direction of providing probabilistic privacy guarantees
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