24 research outputs found

    Lightweight mutual authentication and privacy preservation schemes for IOT systems.

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    Internet of Things (IoT) presents a holistic and transformative approach for providing services in different domains. IoT creates an atmosphere of interaction between humans and the surrounding physical world through various technologies such as sensors, actuators, and the cloud. Theoretically, when everything is connected, everything is at risk. The rapid growth of IoT with the heterogeneous devices that are connected to the Internet generates new challenges in protecting and preserving user’s privacy and ensuring the security of our lives. IoT systems face considerable challenges in deploying robust authentication protocols because some of the IoT devices are resource-constrained with limited computation and storage capabilities to implement the currently available authentication mechanism that employs computationally expensive functions. The limited capabilities of IoT devices raise significant security and privacy concerns, such as ensuring personal information confidentiality and integrity and establishing end-to-end authentication and secret key generation between the communicating device to guarantee secure communication among the communicating devices. The ubiquity nature of the IoT device provides adversaries more attack surfaces which can lead to tragic consequences that can negatively impact our everyday connected lives. According to [1], authentication and privacy protection are essential security requirements. Therefore, there is a critical need to address these rising security and privacy concerns to ensure IoT systems\u27 safety. This dissertation identifies gaps in the literature and presents new mutual authentication and privacy preservation schemes that fit the needs of resource-constrained devices to improve IoT security and privacy against common attacks. This research enhances IoT security and privacy by introducing lightweight mutual authentication and privacy preservation schemes for IoT based on hardware biometrics using PUF, Chained hash PUF, dynamic identities, and user’s static and continuous biometrics. The communicating parties can anonymously communicate and mutually authenticate each other and locally establish a session key using dynamic identities to ensure the user’s unlinkability and untraceability. Furthermore, virtual domain segregation is implemented to apply security policies between nodes. The chained-hash PUF mechanism technique is implemented as a way to verify the sender’s identity. At first, this dissertation presents a framework called “A Lightweight Mutual Authentication and Privacy-Preservation framework for IoT Systems” and this framework is considered the foundation of all presented schemes. The proposed framework integrates software and hardware-based security approaches that satisfy the NIST IoT security requirements for data protection and device identification. Also, this dissertation presents an architecture called “PUF Hierarchal Distributed Architecture” (PHDA), which is used to perform the device name resolution. Based on the proposed framework and PUF architecture, three lightweight privacy-preserving and mutual authentication schemes are presented. The Three different schemes are introduced to accommodate both stationary and mobile IoT devices as well as local and distributed nodes. The first scheme is designed for the smart homes domain, where the IoT devices are stationary, and the controller node is local. In this scheme, there is direct communication between the IoT nodes and the controller node. Establishing mutual authentication does not require the cloud service\u27s involvement to reduce the system latency and offload the cloud traffic. The second scheme is designed for the industrial IoT domain and used smart poultry farms as a use case of the Industrial IoT (IIoT) domain. In the second scheme, the IoT devices are stationary, and the controller nodes are hierarchical and distributed, supported by machine-to-machine (M2M) communication. The third scheme is designed for smart cities and used IoV fleet vehicles as a use case of the smart cities domain. During the roaming service, the mutual authentication process between a vehicle and the distributed controller nodes represented by the Roadside Units (RSUs) is completed through the cloud service that stores all vehicle\u27s security credentials. After that, when a vehicle moves to the proximity of a new RSU under the same administrative authority of the most recently visited RSU, the two RSUs can cooperate to verify the vehicle\u27s legitimacy. Also, the third scheme supports driver static and continuous authentication as a driver monitoring system for the sake of both road and driver safety. The security of the proposed schemes is evaluated and simulated using two different methods: security analysis and performance analysis. The security analysis is implemented through formal security analysis and informal security analysis. The formal analysis uses the Burrows–Abadi–Needham logic (BAN) and model-checking using the automated validation of Internet security protocols and applications (AVISPA) toolkit. The informal security analysis is completed by: (1) investigating the robustness of the proposed schemes against the well-known security attacks and analyze its satisfaction with the main security properties; and (2) comparing the proposed schemes with the other existing authentication schemes considering their resistance to the well-known attacks and their satisfaction with the main security requirements. Both the formal and informal security analyses complement each other. The performance evaluation is conducted by analyzing and comparing the overhead and efficiency of the proposed schemes with other related schemes from the literature. The results showed that the proposed schemes achieve all security goals and, simultaneously, efficiently and satisfy the needs of the resource-constrained IoT devices

    Cryptographic Protection of Digital Identity

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    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.

    Privacy Preservation and Mutual Authentication in RFID Systems

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    Identification and tracking of devices and objects has always been helpful in many fields like transportation, tele-medicine, business and supply chain etc. Radio Frequency Identification (RFID) tags are petite, wireless devices attached to objects for the purpose of identification and information exchange. RFID systems is composed of tags, readers and an application system. These tags can be identified by a reader and are useful for tracking and monitoring. RFID tags uses Radio Frequency (RF) for wireless communication which renders these tags vulnerable to wireless security attacks. Implementation of RFID systems faces huge challenges regarding privacy as these tags can be uniquely identified and thereby are subject to tracking by an adversary. In this project a new privacy and mutual authentication scheme has been discussed that uses cryptographic algorithms and can be used in RFID systems to overcome the issues with privacy

    Identity Management in Information Age Government: Exploring Concepts, Definitions, Approaches and Solutions

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    Our research question is the following: What could be a useful working definition of Identity Management in government at present? a) What are conceptualisations, definitions and approaches of IDM in government according to academic literature? b) Which e-authentication solutions have been developed in other jurisdictions

    Efficient cryptographic primitives: Secure comparison, binary decomposition and proxy re-encryption

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    ”Data outsourcing becomes an essential paradigm for an organization to reduce operation costs on supporting and managing its IT infrastructure. When sensitive data are outsourced to a remote server, the data generally need to be encrypted before outsourcing. To preserve the confidentiality of the data, any computations performed by the server should only be on the encrypted data. In other words, the encrypted data should not be decrypted during any stage of the computation. This kind of task is commonly termed as query processing over encrypted data (QPED). One natural solution to solve the QPED problem is to utilize fully homomorphic encryption. However, fully homomorphic encryption is yet to be practical. The second solution is to adopt multi-server setting. However, the existing work is not efficient. Their implementations adopt costly primitives, such as secure comparison, binary decomposition among others, which reduce the efficiency of the whole protocols. Therefore, the improvement of these primitives results in high efficiency of the protocols. To have a well-defined scope, the following types of computations are considered: secure comparison (CMP), secure binary decomposition (SBD) and proxy re-encryption (PRE). We adopt the secret sharing scheme and paillier public key encryption as building blocks, and all computations can be done on the encrypted data by utilizing multiple servers. We analyze the security and the complexity of our proposed protocols, and their efficiencies are evaluated by comparing with the existing solutions.”--Abstract, page iii

    Analysis and Design of Privacy-Enhancing Information Sharing Systems

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    Recent technological advancements have enabled the collection of large amounts of personal data of individuals at an ever-increasing rate. Service providers, organisations and governments can collect or otherwise acquire rich information about individuals’ everyday lives and habits from big data-silos, enabling profiling and micro-targeting such as in political elections. Therefore, it is important to analyse systems that allow the collection and information sharing between users and to design secure and privacy enhancing solutions. This thesis contains two parts. The aim of the first part is to investigate in detail the effects of the collateral information collection of third-party applications on Facebook. The aim of the second part is to analyse in detail the security and privacy issues of car sharing systems and to design a secure and privacy-preserving solution. In the first part, we present a detailed multi-faceted study on the collateral information collection privacy issues of Facebook applications; providers of third-party applications on Facebook exploit the interdependency between users and their friends. The goal is to (i) study the existence of the problem, (ii) investigate whether Facebook users are concerned about the issue, quantify its (iii) likelihood and (iv) impact of collateral information collection affecting users, (v) identify whether collateral information collection is an issue for the protection of the personal data of Facebook users under the legal framework, and (vi) we propose solutions that aim to solve the problem of collateral information collection. In order to investigate the views of the users, we designed a questionnaire and collected the responses of participants. Employing real data from the Facebook third-party applications ecosystem, we compute the likelihood of collateral information collection affecting users and quantify its significance evaluating the amount of attributes collected by such applications. To investigate whether collateral information collection is an issue in terms of users’ privacy we analysed the legal framework in light of the General Data Protection Regulation. To provide countermeasures, we propose a privacy dashboard extension that implements privacy scoring computations to enhance transparency towards collateral information collection

    Security and privacy in RFID systems

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    Vu que les tags RFID sont actuellement en phase de large déploiement dans le cadre de plusieurs applications (comme les paiements automatiques, le contrôle d'accès à distance, et la gestion des chaînes d approvisionnement), il est important de concevoir des protocoles de sécurité garantissant la protection de la vie privée des détenteurs de tags RFID. Or, la conception de ces protocoles est régie par les limitations en termes de puissance et de calcul de la technologie RFID, et par les modèles de sécurité qui sont à notre avis trop forts pour des systèmes aussi contraints que les tags RFID. De ce fait, on limite dans cette thèse le modèle de sécurité; en particulier, un adversaire ne peut pas observer toutes les interactions entre tags et lecteurs. Cette restriction est réaliste notamment dans le contexte de la gestion des chaînes d approvisionnement qui est l application cible de ce travail. Sous cette hypothèse, on présente quatre protocoles cryptographiques assurant une meilleure collaboration entre les différents partenaires de la chaîne d approvisionnement. D abord, on propose un protocole de transfert de propriété des tags RFID, qui garantit l authentification des tags en temps constant alors que les tags implémentent uniquement des algorithmes symétriques, et qui permet de vérifier l'authenticité de l origine des tags. Ensuite, on aborde le problème d'authenticité des produits en introduisant deux protocoles de sécurité qui permettent à un ensemble de vérificateurs de vérifier que des tags sans capacité de calcul ont emprunté des chemins valides dans la chaîne d approvisionnement. Le dernier résultat présenté dans cette thèse est un protocole d appariement d objets utilisant des tags sans capacité de calcul , qui vise l automatisation des inspections de sécurité dans la chaîne d approvisionnement lors du transport des produits dangereux. Les protocoles introduits dans cette thèse utilisent les courbes elliptiques et les couplages bilinéaires qui permettent la construction des algorithmes de signature et de chiffrement efficaces, et qui minimisent donc le stockage et le calcul dans les systèmes RFID. De plus, la sécurité de ces protocoles est démontrée sous des modèles formels bien définis qui prennent en compte les limitations et les contraintes des tags RFID, et les exigences strictes en termes de sécurité et de la protection de la vie privée des chaines d approvisionnement.While RFID systems are one of the key enablers helping the prototype of pervasive computer applications, the deployment of RFID technologies also comes with new privacy and security concerns ranging from people tracking and industrial espionage to produ ct cloning and denial of service. Cryptographic solutions to tackle these issues were in general challenged by the limited resources of RFID tags, and by the formalizations of RFID privacy that are believed to be too strong for such constrained devices. It follows that most of the existing RFID-based cryptographic schemes failed at ensuring tag privacy without sacrificing RFID scalability or RFID cost effectiveness. In this thesis, we therefore relax the existing definitions of tag privacy to bridge the gap between RFID privacy in theory and RFID privacy in practice, by assuming that an adversary cannot continuously monitor tags. Under this assumption, we are able to design sec ure and privacy preserving multi-party protocols for RFID-enabled supply chains. Namely, we propose a protocol for tag ownership transfer that features constant-time authentication while tags are only required to compute hash functions. Then, we tackle the problem of product genuineness verification by introducing two protocols for product tracking in the supply chain that rely on storage only tags. Finally, we present a solution for item matching that uses storage only tags and aims at the automation of safety inspections in the supply chain.The protocols presented in this manuscript rely on operations performed in subgroups of elliptic curves that allow for the construction of short encryptions and signatures, resulting in minimal storage requirements for RFID tags. Moreover, the privacy and the security of these protocols are proven under well defined formal models that take into account the computational limitations of RFID technology and the stringent privacy and security requirements of each targeted supply chain application.PARIS-Télécom ParisTech (751132302) / SudocSudocFranceF

    Big Data and Artificial Intelligence in Digital Finance

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    This open access book presents how cutting-edge digital technologies like Big Data, Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector. The book illustrates how recent advances in these technologies facilitate banks, FinTech, and financial institutions to collect, process, analyze, and fully leverage the very large amounts of data that are nowadays produced and exchanged in the sector. To this end, the book also describes some more the most popular Big Data, AI and Blockchain applications in the sector, including novel applications in the areas of Know Your Customer (KYC), Personalized Wealth Management and Asset Management, Portfolio Risk Assessment, as well as variety of novel Usage-based Insurance applications based on Internet-of-Things data. Most of the presented applications have been developed, deployed and validated in real-life digital finance settings in the context of the European Commission funded INFINITECH project, which is a flagship innovation initiative for Big Data and AI in digital finance. This book is ideal for researchers and practitioners in Big Data, AI, banking and digital finance

    Big Data and Artificial Intelligence in Digital Finance

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    This open access book presents how cutting-edge digital technologies like Big Data, Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector. The book illustrates how recent advances in these technologies facilitate banks, FinTech, and financial institutions to collect, process, analyze, and fully leverage the very large amounts of data that are nowadays produced and exchanged in the sector. To this end, the book also describes some more the most popular Big Data, AI and Blockchain applications in the sector, including novel applications in the areas of Know Your Customer (KYC), Personalized Wealth Management and Asset Management, Portfolio Risk Assessment, as well as variety of novel Usage-based Insurance applications based on Internet-of-Things data. Most of the presented applications have been developed, deployed and validated in real-life digital finance settings in the context of the European Commission funded INFINITECH project, which is a flagship innovation initiative for Big Data and AI in digital finance. This book is ideal for researchers and practitioners in Big Data, AI, banking and digital finance
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