A Privacy-Friendly Loyalty System Based on Discrete Logarithms over Elliptic Curves

Abstract. Systems for the support of customer relationship management are be-coming increasingly attractive for vendors. Loyalty systems provide an interest-ing possibility for vendors in customer relationship management. This holds for both real world and online vendors. However, beside some potential benefits of a loyalty system, customers may also fear an invasion into their privacy, and may thus refuse to participate in such programs. In this paper, we present a privacy-friendly loyalty system to be used by online vendors to issue loyalty points. The system prevents vendors from exploiting data for the creation of customer profiles by providing unconditional unlinkability of loyalty points with regard to purchases. In the proposed system, we apply the difficulty for the computa-tion of discrete logarithms in a group of prime order to construct a secure and privacy-friendly counter. More precisely, all computations are carried out over special cryptographic groups based on elliptic curves where the decisional Diffie-Hellman problems can be solved easily while the computational Diffie-Hellman is believed to be hard.

Algebraic Curves and Cryptographic Protocols for the e-society

Amb l'augment permanent de l'adopció de sistemes intel·ligents de tot tipus en la societat actual apareixen nous reptes. Avui en dia quasi tothom en la societat moderna porta a sobre almenys un telèfon intel·ligent, si no és que porta encara més dispositius capaços d'obtenir dades personals, com podria ser un smartwatch per exemple. De manera similar, pràcticament totes les cases tindran un comptador intel·ligent en el futur pròxim per a fer un seguiment del consum d'energia. També s'espera que molts més dispositius del Internet de les Coses siguin instal·lats de manera ubiqua, recol·lectant informació dels seus voltants i/o realitzant accions, com per exemple en sistemes d'automatització de la llar, estacions meteorològiques o dispositius per la ciutat intel·ligent en general. Tots aquests dispositius i sistemes necessiten enviar dades de manera segura i confidencial, les quals poden contindre informació sensible o de caire privat. A més a més, donat el seu ràpid creixement, amb més de nou mil milions de dispositius en tot el món actualment, s'ha de tenir en compte la quantitat de dades que cal transmetre. En aquesta tesi mostrem la utilitat de les corbes algebraiques sobre cossos finits en criptosistemes de clau pública, en particular la de les corbes de gènere 2, ja que ofereixen la mida de clau més petita per a un nivell de seguretat donat i això redueix de manera significativa el cost total de comunicacions d'un sistema, a la vegada que manté un rendiment raonable. Analitzem com la valoració 2-àdica del cardinal de la Jacobiana augmenta en successives extensions quadràtiques, considerant corbes de gènere 2 en cossos de característica senar, incloent les supersingulars. A més, millorem els algoritmes actuals per a computar la meitat d'un divisor d'una corba de gènere 2 sobre un cos binari, cosa que pot ser útil en la multiplicació escalar, que és l'operació principal en criptografia de clau pública amb corbes. Pel que fa a la privacitat, presentem un sistema de pagament d'aparcament per mòbil que permet als conductors pagar per aparcar mantenint la seva privacitat, i per tant impedint que el proveïdor del servei o un atacant obtinguin un perfil de conducta d'aparcament. Finalment, oferim protocols de smart metering millorats, especialment pel que fa a la privacitat i evitant l'ús de terceres parts de confiança.Con el aumento permanente de la adopción de sistemas inteligentes de todo tipo en la sociedad actual aparecen nuevos retos. Hoy en día prácticamente todos en la sociedad moderna llevamos encima al menos un teléfono inteligente, si no es que llevamos más dispositivos capaces de obtener datos personales, como podría ser un smartwatch por ejemplo. De manera similar, en el futuro cercano la mayoría de las casas tendrán un contador inteligente para hacer un seguimiento del consumo de energía. También se espera que muchos más dispositivos del Internet de las Cosas sean instalados de manera ubicua, recolectando información de sus alrededores y/o realizando acciones, como por ejemplo en sistemas de automatización del hogar, estaciones meteorológicas o dispositivos para la ciudad inteligente en general. Todos estos dispositivos y sistemas necesitan enviar datos de manera segura y confidencial, los cuales pueden contener información sensible o de ámbito personal. Además, dado su rápido crecimiento, con más de nueve mil millones de dispositivos en todo el mundo actualmente, hay que tener en cuenta la cantidad de datos a transmitir. En esta tesis mostreamos la utilidad de las curvas algebraicas sobre cuerpos finitos en criptosistemas de clave pública, en particular la de las curvas de género 2, ya que ofrecen el tamaño de clave más pequeño para un nivel de seguridad dado y esto disminuye de manera significativa el coste total de comunicaciones del sistema, a la vez que mantiene un rendimiento razonable. Analizamos como la valoración 2-ádica del cardinal de la Jacobiana aumenta en sucesivas extensiones cuadráticas, considerando curvas de género 2 en cuerpos de característica importa, incluyendo las supersingulares. Además, mejoramos los algoritmos actuales para computar la mitad de un divisor de una curva de género 2 sobre un cuerpo binario, lo cual puede ser útil en la multiplicación escalar, que es la operación principal en criptografía de clave pública con curvas. Respecto a la privacidad, presentamos un sistema de pago de aparcamiento por móvil que permite a los conductores pagar para aparcar manteniendo su privacidad, y por lo tanto impidiendo que el proveedor del servicio o un atacante obtengan un perfil de conducta de aparcamiento. Finalmente, ofrecemos protocolos de smart metering mejorados, especialmente en lo relativo a la privacidad y evitando el uso de terceras partes de confianza.With the ever increasing adoption of smart systems of every kind throughout society, new challenges arise. Nowadays, almost everyone in modern societies carries a smartphone at least, if not even more devices than can also gather personal data, like a smartwatch or a fitness wristband for example. Similarly, practically all homes will have a smart meter in the near future for billing and energy consumption monitoring, and many other Internet of Things devices are expected to be installed ubiquitously, obtaining information of their surroundings and/or performing some action, like for example, home automation systems, weather detection stations or devices for the smart city in general. All these devices and systems need to securely and privately transmit some data, which can be sensitive and personal information. Moreover, with a rapid increase of their number, with already more than nine billion devices worldwide, the amount of data to be transmitted has to be considered. In this thesis we show the utility of algebraic curves over finite fields in public key cryptosystems, specially genus 2 curves, since they offer the minimum key size for a given security level and that significantly reduces the total communication costs of a system, while maintaining a reasonable performance. We analyze how the 2-adic valuation of the cardinality of the Jacobian increases in successive quadratic extensions, considering genus 2 curves with odd characteristic fields, including supersingular curves. In addition, we improve the current algorithms for computing the halving of a divisor of a genus 2 curve over binary fields, which can be useful in scalar multiplication, the main operation in public key cryptography using curves. As regards to privacy, we present a pay-by-phone parking system which enables drivers to pay for public parking while preserving their privacy, and thus impeding the service provider or an attacker to obtain a profile of parking behaviors. Finally, we offer better protocols for smart metering, especially regarding privacy and the avoidance of trusted third parties

Fast Privacy-Preserving Punch Cards

Loyalty programs in the form of punch cards that can be redeemed for benefits have long been a ubiquitous element of the consumer landscape. However, their increasingly popular digital equivalents, while providing more convenience and better bookkeeping, pose a considerable privacy risk. This paper introduces a privacy-preserving punch card protocol that allows firms to digitize their loyalty programs without forcing customers to submit to corporate surveillance. We also present a number of extensions that allow our scheme to provide other privacy-preserving customer loyalty features. Compared to the best prior work, we achieve a $14\times$ reduction in the computation and a $11\times$ reduction in the communication required to perform a "hole punch," a $55\times$ reduction in the communication required to redeem a punch card, and a $128\times$ reduction in the computation time required to redeem a card. Much of our performance improvement can be attributed to removing the reliance on pairings or range proofs present in prior work, which has only addressed this problem in the context of more general loyalty systems. By tailoring our scheme to punch cards and related loyalty systems, we demonstrate that we can reduce communication and computation costs by orders of magnitude

Cryptographic Protection of Digital Identity

Dizertační práce se zabývá kryptografickými schématy zvyšující ochranu soukromí uživatelů v systémech řízení přístupu a sběru dat. V současnosti jsou systémy fyzického řízení přístupu na bázi čipových karet využívány téměř dennodenně většinou z nás, například v zaměstnání, ve veřejné dopravě a v hotelech. Tyto systémy však stále neposkytují dostatečnou kryptografickou ochranu a tedy bezpečnost. Uživatelské identifikátory a klíče lze snadno odposlechnout a padělat. Funkce, které by zajišťovaly ochranu soukromí uživatele, téměř vždy chybí. Proto je zde reálné riziko možného sledovaní lidí, jejich pohybu a chovaní. Poskytovatelé služeb nebo případní útočníci, kteří odposlouchávají komunikaci, mohou vytvářet profily uživatelů, ví, co dělají, kde se pohybují a o co se zajímají. Za účelem zlepšení tohoto stavu jsme navrhli čtyři nová kryptografická schémata založená na efektivních důkazech s nulovou znalostí a kryptografii eliptických křivek. Konkrétně dizertační práce prezentuje tři nová autentizační schémata pro využití v systémech řízení přístupu a jedno nové schéma pro využití v systémech sběru dat. První schéma využívá distribuovaný autentizační přístup vyžadující spolupráci více RFID prvků v autentizačním procesu. Tato vlastnost je výhodná zvláště v případech řízení přístupu do nebezpečných prostor, kdy pro povolení přístupu uživatele je nezbytné, aby byl uživatel vybaven ochrannými pomůckami (se zabudovanými RFID prvky). Další dvě schémata jsou založena na atributovém způsobu ověření, tj. schémata umožňují anonymně prokázat vlastnictví atributů uživatele, jako je věk, občanství a pohlaví. Zatím co jedno schéma implementuje efektivní revokační a identifikační mechanismy, druhé schéma poskytuje nejrychlejší verifikaci držení uživatelských atributů ze všech současných řešení. Poslední, čtvrté schéma reprezentuje schéma krátkého skupinového podpisu pro scénář sběru dat. Schémata sběru dat se používají pro bezpečný a spolehlivý přenos dat ze vzdálených uzlů do řídící jednotky. S rostoucím významem chytrých měřičů v energetice, inteligentních zařízení v domácnostech a rozličných senzorových sítí, se potřeba bezpečných systémů sběru dat stává velmi naléhavou. Tato schémata musí podporovat nejen standardní bezpečnostní funkce, jako je důvěrnost a autentičnost přenášených dat, ale také funkce nové, jako je silná ochrana soukromí a identity uživatele či identifikace škodlivých uživatelů. Navržená schémata jsou prokazatelně bezpečná a nabízí celou řadu funkcí rozšiřující ochranu soukromí a identity uživatele, jmenovitě se pak jedná o zajištění anonymity, nesledovatelnosti a nespojitelnosti jednotlivých relací uživatele. Kromě úplné kryptografické specifikace a bezpečnostní analýzy navržených schémat, obsahuje tato práce také výsledky měření implementací jednotlivých schémat na v současnosti nejpoužívanějších zařízeních v oblasti řízení přístupu a sběru dat.The doctoral thesis deals with privacy-preserving cryptographic schemes in access control and data collection areas. Currently, card-based physical access control systems are used by most people on a daily basis, for example, at work, in public transportation and at hotels. However, these systems have often very poor cryptographic protection. For instance, user identifiers and keys can be easily eavesdropped and counterfeited. Furthermore, privacy-preserving features are almost missing and, therefore, user’s movement and behavior can by easily tracked. Service providers (and even eavesdroppers) can profile users, know what they do, where they go, and what they are interested in. In order to improve this state, we propose four novel cryptographic schemes based on efficient zero-knowledge proofs and elliptic curve cryptography. In particular, the thesis presents three novel privacy-friendly authentication schemes for access control and one for data collection application scenarios. The first scheme supports distributed multi-device authentication with multiple Radio-Frequency IDentification (RFID) user’s devices. This feature is particularly important in applications for controlling access to dangerous areas where the presence of protective equipment is checked during each access control session. The other two presented schemes use attribute-based approach to protect user’s privacy, i.e. these schemes allow users to anonymously prove the ownership of their attributes, such as age, citizenship, and gender. While one of our scheme brings efficient revocation and identification mechanisms, the other one provides the fastest authentication phase among the current state of the art solutions. The last (fourth) proposed scheme is a novel short group signature scheme for data collection scenarios. Data collection schemes are used for secure and reliable data transfer from multiple remote nodes to a central unit. With the increasing importance of smart meters in energy distribution, smart house installations and various sensor networks, the need for secure data collection schemes becomes very urgent. Such schemes must provide standard security features, such as confidentiality and authenticity of transferred data, as well as novel features, such as strong protection of user’s privacy and identification of malicious users. The proposed schemes are provably secure and provide the full set of privacy-enhancing features, namely anonymity, untraceability and unlinkability of users. Besides the full cryptographic specification and security analysis, we also show the results of our implementations on devices commonly used in access control and data collection applications.

Conception de protocoles cryptographiques préservant la vie privée pour les services mobiles sans contact

The increasing number of worldwide mobile platforms and the emergence of new technologies such as the NFC (Near Field Communication) lead to a growing tendency to build a user's life depending on mobile phones. This context brings also new security and privacy challenges. In this thesis, we pay further attention to privacy issues in NFC services as well as the security of the mobile applications private data and credentials namely in Trusted Execution Environments (TEE). We first provide two solutions for public transport use case: an m-pass (transport subscription card) and a m-ticketing validation protocols. Our solutions ensure users' privacy while respecting functional requirements of transport operators. To this end, we propose new variants of group signatures and the first practical set-membership proof that do not require pairing computations at the prover's side. These novelties significantly reduce the execution time of such schemes when implemented in resource constrained environments. We implemented the m-pass and m-ticketing protocols in a standard SIM card: the validation phase occurs in less than 300ms whilst using strong security parameters. Our solutions also work even when the mobile is switched off or the battery is flat. When these applications are implemented in TEE, we introduce a new TEE migration protocol that ensures the privacy and integrity of the TEE credentials and user's private data. We construct our protocol based on a proxy re-encryption scheme and a new TEE model. Finally, we formally prove the security of our protocols using either game-based experiments in the random oracle model or automated model checker of security protocols.Avec l'émergence de nouvelles technologies telles que le NFC (Communication à champ proche) et l'accroissement du nombre de plates-formes mobiles, les téléphones mobiles vont devenir de plus en plus indispensables dans notre vie quotidienne. Ce contexte introduit de nouveaux défis en termes de sécurité et de respect de la vie privée. Dans cette thèse, nous nous focalisons sur les problématiques liées au respect de la vie privée dans les services NFC ainsi qu’à la protection des données privées et secrets des applications mobiles dans les environnements d'exécution de confiance (TEE). Nous fournissons deux solutions pour le transport public: une solution utilisant des cartes d'abonnement (m-pass) et une autre à base de tickets électroniques (m-ticketing). Nos solutions préservent la vie privée des utilisateurs tout en respectant les exigences fonctionnelles établies par les opérateurs de transport. À cette fin, nous proposons de nouvelles variantes de signatures de groupe ainsi que la première preuve pratique d’appartenance à un ensemble, à apport nul de connaissance, et qui ne nécessite pas de calculs de couplages du côté du prouveur. Ces améliorations permettent de réduire considérablement le temps d'exécution de ces schémas lorsqu’ils sont implémentés dans des environnements contraints par exemple sur carte à puce. Nous avons développé les protocoles de m-passe et de m-ticketing dans une carte SIM standard : la validation d'un ticket ou d'un m-pass s'effectue en moins de 300ms et ce tout en utilisant des tailles de clés adéquates. Nos solutions fonctionnent également lorsque le mobile est éteint ou lorsque sa batterie est déchargée. Si les applications s'exécutent dans un TEE, nous introduisons un nouveau protocole de migration de données privées, d'un TEE à un autre, qui assure la confidentialité et l'intégrité de ces données. Notre protocole est fondé sur l’utilisation d’un schéma de proxy de rechiffrement ainsi que sur un nouveau modèle d’architecture du TEE. Enfin, nous prouvons formellement la sécurité de nos protocoles soit dans le modèle calculatoire pour les protocoles de m-pass et de ticketing soit dans le modèle symbolique pour le protocole de migration de données entre TEE

Käyttäjien jäljittäminen ja kannusteiden hallinta älykkäissä liikennejärjestelmissä

A system for offering incentives for ecological modes of transport is presented. The main focus is on the verification of claims of having taken a trip on such a mode of transport. Three components are presented for the task of travel mode identification: A system to select features, a means to measure a GPS (Global Positioning System) trace's similarity to a bus route, and finally a machine-learning approach to the actual identification. Feature selection is carried out by sorting the features according to statistical significance, and eliminating correlating features. The novel features considered are skewnesses, kurtoses, auto- and cross correlations, and spectral components of speed and acceleration. Of these, only spectral components are found to be particularly useful in classification. Bus route similarity is measured by using a novel indexing structure called MBR-tree, short for "Multiple Bounding Rectangle", to find the most similar bus traces. The MBR-tree is an expansion of the R-tree for sequences of bounding rectangles, based on an estimation method for longest common subsequence that uses such sequences. A second option of decomposing traces to sequences of direction-distance-duration-triples and indexing them in an M-tree using edit distance with real penalty is considered but shown to perform poorly. For machine learning, the methods considered are Bayes classification, random forest, and feedforward neural networks with and without autoencoders. Autoencoder neural networks are shown to perform perplexingly poorly, but the other methods perform close to the state-of-the-art. Methods for obfuscating the user's location, and constructing secure electronic coupons, are also discussed

Anonymous Point Collection - Improved Models and Security Definitions

This work is a comprehensive, formal treatment of anonymous point collection. The proposed definition does not only provide a strong notion of security and privacy, but also covers features which are important for practical use. An efficient realization is presented and proven to fulfill the proposed definition. The resulting building block is the first one that allows for anonymous two-way transactions, has semi-offline capabilities, yields constant storage size, and is provably secure

Anonymous Point Collection - Improved Models and Security Definitions

This work is a comprehensive, formal treatment of anonymous point collection. The proposed definition does not only provide a strong notion of security and privacy, but also covers features which are important for practical use. An efficient realization is presented and proven to fulfill the proposed definition. The resulting building block is the first one that allows for anonymous two-way transactions, has semi-offline capabilities, yields constant storage size, and is provably secure

Information Leakage Attacks and Countermeasures

The scientific community has been consistently working on the pervasive problem of information leakage, uncovering numerous attack vectors, and proposing various countermeasures. Despite these efforts, leakage incidents remain prevalent, as the complexity of systems and protocols increases, and sophisticated modeling methods become more accessible to adversaries. This work studies how information leakages manifest in and impact interconnected systems and their users. We first focus on online communications and investigate leakages in the Transport Layer Security protocol (TLS). Using modern machine learning models, we show that an eavesdropping adversary can efficiently exploit meta-information (e.g., packet size) not protected by the TLS’ encryption to launch fingerprinting attacks at an unprecedented scale even under non-optimal conditions. We then turn our attention to ultrasonic communications, and discuss their security shortcomings and how adversaries could exploit them to compromise anonymity network users (even though they aim to offer a greater level of privacy compared to TLS). Following up on these, we delve into physical layer leakages that concern a wide array of (networked) systems such as servers, embedded nodes, Tor relays, and hardware cryptocurrency wallets. We revisit location-based side-channel attacks and develop an exploitation neural network. Our model demonstrates the capabilities of a modern adversary but also presents an inexpensive tool to be used by auditors for detecting such leakages early on during the development cycle. Subsequently, we investigate techniques that further minimize the impact of leakages found in production components. Our proposed system design distributes both the custody of secrets and the cryptographic operation execution across several components, thus making the exploitation of leaks difficult