arXiv subjects

Rolando Trujillo-Rasua

Publications and source records attributed to Rolando Trujillo-Rasua.

17 recordsLinked to original sources

arXiv2026

A Systematic Security Analysis for Path-based Traceability Systems in RFID-Enabled Supply Chains

Traceability systems have become prevalent in supply chains because of the rapid development of RFID and IoT technologies. These systems facilitate product recall and mitigate problems such as counterfeiting, tampering, and theft by tracking the manufacturing and distribution life-cycle of a product. Therefore, traceability systems are a defense mechanism against supply chain attacks and, consequently, have become a target for attackers to circumvent. For example, a counterfeiter may change the trace of a fake product for the trace of an authentic product, fooling the system into accepting a counterfeit product as legit and thereby giving a false sense of security. This systematic analysis starts with the observation that security requirements in existing traceability solutions are often unstructured or incomplete, leaving critical vulnerabilities unaddressed. We synthesized the properties of current state-of-the-art traceability solutions within a single security framework that allows us to analyze and compare their security claims. Using this framework, we objectively compared the security of $17$ traceability solutions and identified several weaknesses and vulnerabilities. This article reports on these flaws, the methodology we used to identify them, and the first security evaluation of traceability solutions on a large scale.

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arXiv2025

Empirical Evaluation of Memory-Erasure Protocols

Software-based memory-erasure protocols are two-party communication protocols where a verifier instructs a computational device to erase its memory and send a proof of erasure. They aim at guaranteeing that low-cost IoT devices are free of malware by putting them back into a safe state without requiring secure hardware or physical manipulation of the device. Several software-based memory-erasure protocols have been introduced and theoretically analysed. Yet, many of them have not been tested for their feasibility, performance and security on real devices, which hinders their industry adoption. This article reports on the first empirical analysis of software-based memory-erasure protocols with respect to their security, erasure guarantees, and performance. The experimental setup consists of 3 modern IoT devices with different computational capabilities, 7 protocols, 6 hash-function implementations, and various performance and security criteria. Our results indicate that existing software-based memory-erasure protocols are feasible, although slow devices may take several seconds to erase their memory and generate a proof of erasure. We found that no protocol dominates across all empirical settings, defined by the computational power and memory size of the device, the network speed, and the required level of security. Interestingly, network speed and hidden constants within the protocol specification played a more prominent role in the performance of these protocols than anticipated based on the related literature. We provide an evaluation framework that, given a desired level of security, determines which protocols offer the best trade-off between performance and erasure guarantees.

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arXiv2025

On the $(k,\ell)$-multiset anonymity measure for social graphs

The publication of social graphs must be preceded by a rigorous analysis of privacy threats against social graph users. When the threat comes from inside the social network itself, the threat is called an active attack, and the de-facto privacy measure used to quantify the resistance to such an attack is the $(k,\ell)$-anonymity. The original formulation of $(k,\ell)$-anonymity represents the adversary's knowledge as a vector of distances to the set of attacker nodes. In this article, we argue that such adversary is too strong when it comes to counteracting active attacks. We, instead, propose a new formulation where the adversary's knowledge is the multiset of distances to the set of attacker nodes. The goal of this article is to study the $(k,\ell)$-multiset anonymity from a graph theoretical point of view, while establishing its relationship to $(k,\ell)$-anonymity in one hand, and considering the $k$-multiset antiresolving sets as its theoretical frame, in a second one. That is, we prove properties of some graph families in relation to whether they contain a set of attacker nodes that breaks the $(k,\ell)$-multiset anonymity. From a practical point of view, we develop a linear programming formulation of the $k$-multiset antiresolving sets that allows us to calculate the resistance of social graphs against active attacks. This is useful for analysts who wish to know the level of privacy offered by a graph.

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arXiv2024

Software-Based Memory Erasure with relaxed isolation requirements: Extended Version

A Proof of Secure Erasure (PoSE) is a communication protocol where a verifier seeks evidence that a prover has erased its memory within the time frame of the protocol execution. Designers of PoSE protocols have long been aware that, if a prover can outsource the computation of the memory erasure proof to another device, then their protocols are trivially defeated. As a result, most software-based PoSE protocols in the literature assume that provers are isolated during the protocol execution, that is, provers cannot receive help from a network adversary. Our main contribution is to show that this assumption is not necessary. We introduce formal models for PoSE protocols playing against provers aided by external conspirators and develop three PoSE protocols that we prove secure in this context. We reduce the requirement of isolation to the more realistic requirement that the communication with the external conspirator is relatively slow. Software-based protocols with such relaxed isolation assumptions are especially pertinent for low-end devices, where it is too costly to deploy sophisticated protection methods.

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arXiv2021

Analysis of centrality measures under differential privacy models

This paper provides the first analysis of the differentially private computation of three centrality measures, namely eigenvector, Laplacian and closeness centralities, on arbitrary weighted graphs, using the smooth sensitivity approach. We do so by finding lower bounds on the amounts of noise that a randomised algorithm needs to add in order to make the output of each measure differentially private. Our results indicate that these computations are either infeasible, in the sense that there are large families of graphs for which smooth sensitivity is unbounded; or impractical, in the sense that even for the cases where smooth sensitivity is bounded, the required amounts of noise result in unacceptably large utility losses.

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arXiv2020

Preventing active re-identification attacks on social graphs via sybil subgraph obfuscation

This paper addresses active re-identification attacks in the context of privacy-preserving social graph publication. Active attacks are those where the adversary can leverage fake accounts, a.k.a. sybil nodes, to enforce structural patterns that can be used to re-identify their victims on anonymised graphs. In this paper we present a new probabilistic interpretation of this type of attacks. Unlike previous privacy properties, which model the protection from active adversaries as the task of making victim nodes indistinguishable in terms of their fingerprints with respect to all potential attackers, our new formulation introduces a more complete view, where the attack is countered by jointly preventing the attacker from retrieving the set of sybil nodes, and from using these sybil nodes for re-identifying the victims. Under the new formulation, we show that the privacy property $k$-symmetry, introduced in the context of passive attacks, provides a sufficient condition for the protection against active re-identification attacks leveraging an arbitrary number of sybil nodes. Moreover, we show that the algorithm K-Match, originally devised for efficiently enforcing the related notion of $k$-automorphism, also guarantees $k$-symmetry. Empirical results on several collections of synthetic graphs corroborate that our approach allows, for the first time, to publish anonymised social graphs (with formal privacy guarantees) that effectively resist the strongest active re-identification attack reported in the literature, even when it leverages a large number of sybil nodes.

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arXiv2019

Secure Memory Erasure in the Presence of Man-in-the-Middle Attackers

Memory erasure protocols serve to clean up a device's memory before the installation of new software. Although this task can be accomplished by direct hardware manipulation, remote software-based memory erasure protocols have emerged as a more efficient and cost-effective alternative. Existing remote memory erasure protocols, however, still rely on non-standard adversarial models to operate correctly, thereby requiring additional hardware to restrict the adversary's capabilities. In this work, we provide a formal definition of secure memory erasure within a symbolic security model that utilizes the standard Dolev-Yao adversary. Our main result consists of a restriction on the Dolev-Yao adversary that we prove necessary and sufficient to solve the problem of finding a protocol that satisfies secure memory erasure. We also provide a description of the resulting protocol using standard cryptographic notation, which we use to analyze the security and communication complexity trade-off commonly present in this type of protocols.

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arXiv2019

Distance-based vertex identification in graphs: the outer multiset dimension

Given a graph $G$ and a subset of vertices $S = \{w_1, \ldots, w_t\} \subseteq V(G)$, the multiset representation of a vertex $u\in V(G)$ with respect to $S$ is the multiset $m(u|S) = \{| d_G(u, w_1), \ldots, d_G(u, w_t) |\}$. A subset of vertices $S$ such that $m(u|S) = m(v|S) \iff u = v$ for every $u, v \in V(G) \setminus S$ is said to be a multiset resolving set, and the cardinality of the smallest such set is the outer multiset dimension. We study the general behaviour of the outer multiset dimension, and determine its exact value for several graph families. We also show that computing the outer multiset dimension of arbitrary graphs is NP-hard, and provide methods for efficiently handling particular cases.

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arXiv2019

Attribute Evaluation on Attack Trees with Incomplete Information

Attack trees are considered a useful tool for security modelling because they support qualitative as well as quantitative analysis. The quantitative approach is based on values associated to each node in the tree, expressing, for instance, the minimal cost or probability of an attack. Current quantitative methods for attack trees allow the analyst to, based on an initial assignment of values to the leaf nodes, derive the values of the higher nodes in the tree. In practice, however, it shows to be very difficult to obtain reliable values for all leaf nodes. The main reasons are that data is only available for some of the nodes, that data is available for intermediate nodes rather than for the leaf nodes, or even that the available data is inconsistent. We address these problems by developing a generalisation of the standard bottom-up calculation method in three ways. First, we allow initial attributions of non-leaf nodes. Second, we admit additional relations between attack steps beyond those provided by the underlying attack tree semantics. Third, we support the calculation of an approximative solution in case of inconsistencies. We illustrate our method, which is based on constraint programming, by a comprehensive case study.

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arXiv2018

Robust active attacks on social graphs

In order to prevent the disclosure of privacy-sensitive data, such as names and relations between users, social network graphs have to be anonymised before publication. Naive anonymisation of social network graphs often consists in deleting all identifying information of the users, while maintaining the original graph structure. Various types of attacks on naively anonymised graphs have been developed. Active attacks form a special type of such privacy attacks, in which the adversary enrols a number of fake users, often called sybils, to the social network, allowing the adversary to create unique structural patterns later used to re-identify the sybil nodes and other users after anonymisation. Several studies have shown that adding a small amount of noise to the published graph already suffices to mitigate such active attacks. Consequently, active attacks have been dubbed a negligible threat to privacy-preserving social graph publication. In this paper, we argue that these studies unveil shortcomings of specific attacks, rather than inherent problems of active attacks as a general strategy. In order to support this claim, we develop the notion of a robust active attack, which is an active attack that is resilient to small perturbations of the social network graph. We formulate the design of robust active attacks as an optimisation problem and we give definitions of robustness for different stages of the active attack strategy. Moreover, we introduce various heuristics to achieve these notions of robustness and experimentally show that the new robust attacks are considerably more resilient than the original ones, while remaining at the same level of feasibility.

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arXiv2017

Rethinking $(k,\ell)$-anonymity in social graphs: $(k,\ell)$-adjacency anonymity and $(k,\ell)$-(adjacency) anonymous transformations

This paper treats the privacy-preserving publication of social graphs in the presence of active adversaries, that is, adversaries with the ability to introduce sybil nodes in the graph prior to publication and leverage them to create unique fingerprints for a set of victim nodes and re-identify them after publication. Stemming from the notion of $(k,\ell)$-anonymity, we introduce $(k,\ell)$-anonymous transformations, characterising graph perturbation methods that ensure protection from active adversaries levaraging up to $\ell$ sybil nodes. Additionally, we introduce a new privacy property: $(k,\ell)$-adjacency anonymity, which relaxes the assumption made by $(k,\ell)$-anonymity that adversaries can control all distances between sybil nodes and the rest of the nodes in the graph. The new privacy property is in turn the basis for a new type of graph perturbation: $(k,\ell)$-adjacency anonymous transformations. We propose algorithms for obtaining $(k,1)$-adjacency anonymous transformations for arbitrary values of $k$, as well as $(2,\ell)$-adjacency anonymous transformations for small values of $\ell$.

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arXiv2015

k-Metric Antidimension: a Privacy Measure for Social Graphs

Let $G = (V, E)$ be a simple connected graph and $S = \{w_1, \cdots, w_t\} \subseteq V$ an ordered subset of vertices. The metric representation of a vertex $u\in V$ with respect to $S$ is the $t$-vector $r(u|S) = (d_G(u, w_1), \cdots, d_G(u, w_t))$, where $d_G(u, v)$ represents the length of a shortest $u-v$ path in $G$. The set $S$ is called a resolving set for $G$ if $r(u|S) = r(v|S)$ implies $u = v$ for every $u, v \in V$. The smallest cardinality of a resolving set is the metric dimension of $G$. In this article we propose, to the best of our knowledge, a new problem in Graph Theory that resembles to the aforementioned metric dimension problem. We call $S$ a $k$-antiresolving set if $k$ is the largest positive integer such that for every vertex $v \in V-S$ there exist other $k-1$ different vertices $v_1, \cdots, v_{k-1} \in V-S$ with $r(v|S) = r(v_1|S) = \cdots = r(v_{k-1}|S)$, \emph{i.e.}, $v$ and $v_1, \cdots, v_{k-1}$ have the same metric representation with respect to $S$. The $k$-metric antidimension of $G$ is the minimum cardinality among all the $k$-antiresolving sets for $G$. In this article, we introduce a novel privacy measure, named $(k, \ell)$-anonymity and based on the $k$-metric antidimension problem, aimed at evaluating the resistance of social graphs to active attacks. We, therefore, propose a true-biased algorithm for computing the $k$-metric antidimension of random graphs. The success rate of our algorithm, according to empirical results, is above $80 \%$ and $90 \%$ when looking for a $k$-antiresolving basis and a $k$-antiresolving set respectively. We also investigate theoretical properties of the $k$-antiresolving sets and the $k$-metric antidimension of graphs. In particular, we focus on paths, cycles, complete bipartite graphs and trees.

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arXiv2015

Comparing Distance Bounding Protocols: a Critical Mission Supported by Decision Theory

Distance bounding protocols are security countermeasures designed to thwart relay attacks. Such attacks consist in relaying messages exchanged between two parties, making them believe they communicate directly with each other. Although distance bounding protocols have existed since the early nineties, this research topic resurrected with the deployment of contactless systems, against which relay attacks are particularly impactful. Given the impressive number of distance bounding protocols that are designed every year, it becomes urgent to provide researchers and engineers with a methodology to fairly compare the protocols in spite of their various properties. This paper introduces such a methodology based on concepts from the decision making field. The methodology allows for a multi-criteria comparison of distance bounding protocols, thereby identifying the most appropriate protocols once the context is provided. As a side effect, this paper clearly identifies the protocols that should no longer be considered, regardless of the considered scenario.

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arXiv2015

Attack Trees with Sequential Conjunction

We provide the first formal foundation of SAND attack trees which are a popular extension of the well-known attack trees. The SAND attack tree formalism increases the expressivity of attack trees by introducing the sequential conjunctive operator SAND. This operator enables the modeling of ordered events. We give a semantics to SAND attack trees by interpreting them as sets of series-parallel graphs and propose a complete axiomatization of this semantics. We define normal forms for SAND attack trees and a term rewriting system which allows identification of semantically equivalent trees. Finally, we formalize how to quantitatively analyze SAND attack trees using attributes.

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arXiv2014

Complexity of distance fraud attacks in graph-based distance bounding

Distance bounding (DB) emerged as a countermeasure to the so-called \emph{relay attack}, which affects several technologies such as RFID, NFC, Bluetooth, and Ad-hoc networks. A prominent family of DB protocols are those based on graphs, which were introduced in 2010 to resist both mafia and distance frauds. The security analysis in terms of distance fraud is performed by considering an adversary that, given a vertex labeled graph $G = (V, E)$ and a vertex $v \in V$, is able to find the most frequent $n$-long sequence in $G$ starting from $v$ (MFS problem). However, to the best of our knowledge, it is still an open question whether the distance fraud security can be computed considering the aforementioned adversarial model. Our first contribution is a proof that the MFS problem is NP-Hard even when the graph is constrained to meet the requirements of a graph-based DB protocol. Although this result does not invalidate the model, it does suggest that a \emph{too-strong} adversary is perhaps being considered (i.e., in practice, graph-based DB protocols might resist distance fraud better than the security model suggests.) Our second contribution is an algorithm addressing the distance fraud security of the tree-based approach due to Avoine and Tchamkerten. The novel algorithm improves the computational complexity $O(2^{2^n+n})$ of the naive approach to $O(2^{2n}n)$ where $n$ is the number of rounds.

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arXiv2014

Distance-bounding facing both mafia and distance frauds: Technical report*

Contactless technologies such as RFID, NFC, and sensor networks are vulnerable to mafia and distance frauds. Both frauds aim at passing an authentication protocol by cheating on the actual distance between the prover and the verifier. To cope these security issues, distance-bounding protocols have been designed. However, none of the current proposals simultaneously resists to these two frauds without requiring additional memory and computation. The situation is even worse considering that just a few distance-bounding protocols are able to deal with the inherent background noise on the communication channels. This article introduces a noise-resilient distance-bounding protocol that resists to both mafia and distance frauds. The security of the protocol is analyzed with respect to these two frauds in both scenarios, namely noisy and noiseless channels. Analytical expressions for the adversary's success probabilities are provided, and are illustrated by experimental results. The analysis, performed in an already existing framework for fairness reasons, demonstrates the undeniable advantage of the introduced lightweight design over the previous proposals.

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arXiv2013

Privacy in RFID and mobile objects

Radio Frequency Identification (RFID) is a technology aimed at eficiently identifying and tracking goods and assets. Such identification may be performed without requiring line-of-sight alignment or physical contact between the RFID tag and the RFID reader, whilst tracking is naturally achieved due to the short interrogation field of RFID readers. That is why the reduction in price of the RFID tags has been accompanied with an increasing attention paid to this technology. However, since tags are resource-constrained devices sending identification data wirelessly, designing secure and private RFID identification protocols is a challenging task. This scenario is even more complex when scalability must be met by those protocols. Assuming the existence of a lightweight, secure, private and scalable RFID identification protocol, there exist other concerns surrounding the RFID technology. Some of them arise from the technology itself, such as distance checking, but others are related to the potential of RFID systems to gather huge amount of tracking data. Publishing and mining such moving objects data is essential to improve efficiency of supervisory control, assets management and localisation, transportation, etc. However, obvious privacy threats arise if an individual can be linked with some of those published trajectories. The present dissertation contributes to the design of algorithms and protocols aimed at dealing with the issues explained above. First, we propose a set of protocols and heuristics based on a distributed architecture that improve the efficiency of the identification process without compromising privacy or security. Moreover, we present a novel distance-bounding protocol based on graphs that is extremely low-resource consuming. Finally, we present two trajectory anonymisation methods aimed at preserving the individuals' privacy when their trajectories are released.

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