3,627 research outputs found

    A LINDDUN-based framework for privacy threat analysis on identification and authentication processes

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    © . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Identification and authentication (IA) are security procedures that are ubiquitous in our online life, and that constantly require disclosing personal, sensitive information to non-fully trusted service providers, or to fully trusted providers that unintentionally may fail to protect such information. Although user IA processes are extensively supported by heterogeneous software and hardware, the simultaneous protection of user privacy is an open problem. From a legal point of view, the European Union legislation requires protecting the processing of personal data and evaluating its impact on privacy throughout the whole IA procedure. Privacy Threat Analysis (PTA) is one of the pillars for the required Privacy Impact Assessment (PIA). Among the few existing approaches for conducting a PTA, LINDDUN is a very promising framework, although generic, in the sense that it has not been specifically conceived for IA. In this work, we investigate an extension of LINDDUN that allows performing a reliable and systematically-reproducible PTA of user IA processes, thereby contributing to one of the cornerstones of PIA. Specifically, we propose a high-level description of the IA verification process, which we illustrate with an UML use case. Then, we design an identification and authentication modelling framework, propose an extension of two critical steps of the LINDDUN scheme, and adapt and tailor the trust boundary concept applied in the original framework. Finally, we propose a systematic methodology aimed to help auditors apply the proposed improvements to the LINDDUN framework.The authors are thankful for the support through the research project “INRISCO”, ref. TEC2014-54335-C4-1-R, “MAGOS”, TEC2017-84197-C4-3-R, and the project “Sec-MCloud”, ref. TIN2016-80250-R. J. Parra-Arnau is the recipient of a Juan de la Cierva postdoctoral fellowship, IJCI-2016–28239, from the Spanish Ministry of Economy and Competitiveness. J. Parra-Arnau is with the UNESCO Chair in Data Privacy, but the views in this paper are his own and are not necessarily shared by UNESCO.Peer ReviewedPostprint (author's final draft

    Zero-Knowledge Proof-of-Identity: Sybil-Resistant, Anonymous Authentication on Permissionless Blockchains and Incentive Compatible, Strictly Dominant Cryptocurrencies

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    Zero-Knowledge Proof-of-Identity from trusted public certificates (e.g., national identity cards and/or ePassports; eSIM) is introduced here to permissionless blockchains in order to remove the inefficiencies of Sybil-resistant mechanisms such as Proof-of-Work (i.e., high energy and environmental costs) and Proof-of-Stake (i.e., capital hoarding and lower transaction volume). The proposed solution effectively limits the number of mining nodes a single individual would be able to run while keeping membership open to everyone, circumventing the impossibility of full decentralization and the blockchain scalability trilemma when instantiated on a blockchain with a consensus protocol based on the cryptographic random selection of nodes. Resistance to collusion is also considered. Solving one of the most pressing problems in blockchains, a zk-PoI cryptocurrency is proved to have the following advantageous properties: - an incentive-compatible protocol for the issuing of cryptocurrency rewards based on a unique Nash equilibrium - strict domination of mining over all other PoW/PoS cryptocurrencies, thus the zk-PoI cryptocurrency becoming the preferred choice by miners is proved to be a Nash equilibrium and the Evolutionarily Stable Strategy - PoW/PoS cryptocurrencies are condemned to pay the Price of Crypto-Anarchy, redeemed by the optimal efficiency of zk-PoI as it implements the social optimum - the circulation of a zk-PoI cryptocurrency Pareto dominates other PoW/PoS cryptocurrencies - the network effects arising from the social networks inherent to national identity cards and ePassports dominate PoW/PoS cryptocurrencies - the lower costs of its infrastructure imply the existence of a unique equilibrium where it dominates other forms of paymentComment: 2.1: Proof-of-Personhood Considered Harmful (and Illegal); 4.1.5: Absence of Active Authentication; 4.2.6: Absence of Active Authentication; 4.2.7: Removing Single-Points of Failure; 4.3.2: Combining with Non-Zero-Knowledge Authentication; 4.4: Circumventing the Impossibility of Full Decentralizatio

    Gesture recognition implemented on a personal limited device

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    Biometric security on body sensor networks

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    Modeling and Analysis of Data Trading on Blockchain-based Market in IoT Networks

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    Mobile devices with embedded sensors for data collection and environmental sensing create a basis for a cost-effective approach for data trading. For example, these data can be related to pollution and gas emissions, which can be used to check the compliance with national and international regulations. The current approach for IoT data trading relies on a centralized third-party entity to negotiate between data consumers and data providers, which is inefficient and insecure on a large scale. In comparison, a decentralized approach based on distributed ledger technologies (DLT) enables data trading while ensuring trust, security, and privacy. However, due to the lack of understanding of the communication efficiency between sellers and buyers, there is still a significant gap in benchmarking the data trading protocols in IoT environments. Motivated by this knowledge gap, we introduce a model for DLT-based IoT data trading over the Narrowband Internet of Things (NB-IoT) system, intended to support massive environmental sensing. We characterize the communication efficiency of three basic DLT-based IoT data trading protocols via NB-IoT connectivity in terms of latency and energy consumption. The model and analyses of these protocols provide a benchmark for IoT data trading applications.Comment: 10 pages, 8 figures, Accepted at IEEE Internet of Things Journa

    Modeling and Analysis of Data Trading on Blockchain-based Market in IoT Networks

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