703 research outputs found
Formal Computational Unlinkability Proofs of RFID Protocols
We set up a framework for the formal proofs of RFID protocols in the
computational model. We rely on the so-called computationally complete symbolic
attacker model. Our contributions are: i) To design (and prove sound) axioms
reflecting the properties of hash functions (Collision-Resistance, PRF); ii) To
formalize computational unlinkability in the model; iii) To illustrate the
method, providing the first formal proofs of unlinkability of RFID protocols,
in the computational model
Probabilistic yoking proofs for large scale IoT systems
Yoking (or grouping) proofs were introduced in 2004 as a security construction for RFID applications in which it is needed to build an evidence that several objects have been scanned simultaneously or, at least, within a short time. Such protocols were designed for scenarios where only a few tags (typically just two) are involved, so issues such as preventing an object from abandoning the proof right after being interrogated simply do not make sense. The idea, however, is very interesting for many Internet of Things (IoT) applications where a potentially large population of objects must be grouped together. In this paper we address this issue by presenting the notion of Probabilistic Yoking Proofs (PYP) and introducing three main criteria to assess their performance: cost, security, and fairness. Our proposal combines the message structure found in classical grouping proof constructions with an iterative Poisson sampling process where the probability of each object being sampled varies over time. We introduce a number of mechanisms to apply fluctuations to each object's sampling probability and present different sampling strategies. Our experimental results confirm that most strategies achieve good security and fairness levels while keeping the overall protocol cost down. (C) 2015 Elsevier B.V. All rights reserved.This work was supported by the MINECO Grant TIN2013 46469 R (SPINY: Security and Privacy in the Internet of You)
Survey on Lightweight Primitives and Protocols for RFID in Wireless Sensor Networks
The use of radio frequency identification (RFID) technologies is becoming widespread in all kind of wireless network-based applications. As expected, applications based on sensor networks, ad-hoc or mobile ad hoc networks (MANETs) can be highly benefited from the adoption of RFID solutions. There is a strong need to employ lightweight cryptographic primitives for many security applications because of the tight cost and constrained resource requirement of sensor based networks. This paper mainly focuses on the security analysis of lightweight protocols and algorithms proposed for the security of RFID systems. A large number of research solutions have been proposed to implement lightweight cryptographic primitives and protocols in sensor and RFID integration based resource constraint networks. In this work, an overview of the currently discussed lightweight primitives and their attributes has been done. These primitives and protocols have been compared based on gate equivalents (GEs), power, technology, strengths, weaknesses and attacks. Further, an integration of primitives and protocols is compared with the possibilities of their applications in practical scenarios
Stability Analysis of Frame Slotted Aloha Protocol
Frame Slotted Aloha (FSA) protocol has been widely applied in Radio Frequency
Identification (RFID) systems as the de facto standard in tag identification.
However, very limited work has been done on the stability of FSA despite its
fundamental importance both on the theoretical characterisation of FSA
performance and its effective operation in practical systems. In order to
bridge this gap, we devote this paper to investigating the stability properties
of FSA by focusing on two physical layer models of practical importance, the
models with single packet reception and multipacket reception capabilities.
Technically, we model the FSA system backlog as a Markov chain with its states
being backlog size at the beginning of each frame. The objective is to analyze
the ergodicity of the Markov chain and demonstrate its properties in different
regions, particularly the instability region. By employing drift analysis, we
obtain the closed-form conditions for the stability of FSA and show that the
stability region is maximised when the frame length equals the backlog size in
the single packet reception model and when the ratio of the backlog size to
frame length equals in order of magnitude the maximum multipacket reception
capacity in the multipacket reception model. Furthermore, to characterise
system behavior in the instability region, we mathematically demonstrate the
existence of transience of the backlog Markov chain.Comment: 14 pages, submitted to IEEE Transaction on Information Theor
Attack Resilience and Recovery using Physical Challenge Response Authentication for Active Sensors Under Integrity Attacks
Embedded sensing systems are pervasively used in life- and security-critical
systems such as those found in airplanes, automobiles, and healthcare.
Traditional security mechanisms for these sensors focus on data encryption and
other post-processing techniques, but the sensors themselves often remain
vulnerable to attacks in the physical/analog domain. If an adversary
manipulates a physical/analog signal prior to digitization, no amount of
digital security mechanisms after the fact can help. Fortunately, nature
imposes fundamental constraints on how these analog signals can behave. This
work presents PyCRA, a physical challenge-response authentication scheme
designed to protect active sensing systems against physical attacks occurring
in the analog domain. PyCRA provides security for active sensors by continually
challenging the surrounding environment via random but deliberate physical
probes. By analyzing the responses to these probes, and by using the fact that
the adversary cannot change the underlying laws of physics, we provide an
authentication mechanism that not only detects malicious attacks but provides
resilience against them. We demonstrate the effectiveness of PyCRA through
several case studies using two sensing systems: (1) magnetic sensors like those
found wheel speed sensors in robotics and automotive, and (2) commercial RFID
tags used in many security-critical applications. Finally, we outline methods
and theoretical proofs for further enhancing the resilience of PyCRA to active
attacks by means of a confusion phase---a period of low signal to noise ratio
that makes it more difficult for an attacker to correctly identify and respond
to PyCRA's physical challenges. In doing so, we evaluate both the robustness
and the limitations of PyCRA, concluding by outlining practical considerations
as well as further applications for the proposed authentication mechanism.Comment: Shorter version appeared in ACM ACM Conference on Computer and
Communications (CCS) 201
Distributed Wireless Algorithms for RFID Systems: Grouping Proofs and Cardinality Estimation
The breadth and depth of the use of Radio Frequency Identification (RFID) are becoming more substantial. RFID is a technology useful for identifying unique items through radio waves. We design algorithms on RFID-based systems for the Grouping Proof and Cardinality Estimation problems.
A grouping-proof protocol is evidence that a reader simultaneously scanned the RFID tags in a group. In many practical scenarios, grouping-proofs greatly expand the potential of RFID-based systems such as supply chain applications, simultaneous scanning of multiple forms of IDs in banks or airports, and government paperwork. The design of RFID grouping-proofs that provide optimal security, privacy, and efficiency is largely an open area, with challenging problems including robust privacy mechanisms, addressing completeness and incompleteness (missing tags), and allowing dynamic groups definitions. In this work we present three variations of grouping-proof protocols that implement our mechanisms to overcome these challenges.
Cardinality estimation is for the reader to determine the number of tags in its communication range. Speed and accuracy are important goals. Many practical applications need an accurate and anonymous estimation of the number of tagged objects. Examples include intelligent transportation and stadium management. We provide an optimal estimation algorithm template for cardinality estimation that works for a {0,1,e} channel, which extends to most estimators and ,possibly, a high resolution {0,1,...,k-1,e} channel
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