9,110 research outputs found

    Trust models in ubiquitous computing

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    We recapture some of the arguments for trust-based technologies in ubiquitous computing, followed by a brief survey of some of the models of trust that have been introduced in this respect. Based on this, we argue for the need of more formal and foundational trust models

    Beyond the Hype: On Using Blockchains in Trust Management for Authentication

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    Trust Management (TM) systems for authentication are vital to the security of online interactions, which are ubiquitous in our everyday lives. Various systems, like the Web PKI (X.509) and PGP's Web of Trust are used to manage trust in this setting. In recent years, blockchain technology has been introduced as a panacea to our security problems, including that of authentication, without sufficient reasoning, as to its merits.In this work, we investigate the merits of using open distributed ledgers (ODLs), such as the one implemented by blockchain technology, for securing TM systems for authentication. We formally model such systems, and explore how blockchain can help mitigate attacks against them. After formal argumentation, we conclude that in the context of Trust Management for authentication, blockchain technology, and ODLs in general, can offer considerable advantages compared to previous approaches. Our analysis is, to the best of our knowledge, the first to formally model and argue about the security of TM systems for authentication, based on blockchain technology. To achieve this result, we first provide an abstract model for TM systems for authentication. Then, we show how this model can be conceptually encoded in a blockchain, by expressing it as a series of state transitions. As a next step, we examine five prevalent attacks on TM systems, and provide evidence that blockchain-based solutions can be beneficial to the security of such systems, by mitigating, or completely negating such attacks.Comment: A version of this paper was published in IEEE Trustcom. http://ieeexplore.ieee.org/document/8029486

    Probabilistic Estimation of Peers’ Quality and Behaviors for Subjective Trust Evaluation

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    The management of trust and quality in decentralized systems has been recognized as a key research area over recent years. In this paper, we propose a probabilistic computational approach to enable a peer in the system to model and estimate the quality and behaviors of the others subjectively according to its own preferences. Our solution is based on the use of graphical models to represent the dependencies among different QoS parameters of a service provided by a peer, the associated contextual factors, the innate behaviors of the reporters and their feedback on quality of the peer being evaluated. We apply the EM algorithm to learn the conditional probabilities of the introduced variables and perform necessary probabilistic inferences on the constructed model to estimate peer's quality and behaviors. Interestingly, our proposed framework can be shown as the generalization of many existing trust computational approaches in the literature with several additional advantages: first, it works well given few and sparse feedback data from the reporting peers; second, it also considers the dependencies among the QoS attributes of a peer, related contextual factors, and underlying behavioral models of reporters to produce more reliable estimations; third, the model gives outputs with well-defined semantics and useful meanings which can be used for many purposes, for example, it computes the probability that a peer is trustworthy in sharing its experiences or in providing a service with high quality level under certain environmental conditions

    Byzantine Attack and Defense in Cognitive Radio Networks: A Survey

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    The Byzantine attack in cooperative spectrum sensing (CSS), also known as the spectrum sensing data falsification (SSDF) attack in the literature, is one of the key adversaries to the success of cognitive radio networks (CRNs). In the past couple of years, the research on the Byzantine attack and defense strategies has gained worldwide increasing attention. In this paper, we provide a comprehensive survey and tutorial on the recent advances in the Byzantine attack and defense for CSS in CRNs. Specifically, we first briefly present the preliminaries of CSS for general readers, including signal detection techniques, hypothesis testing, and data fusion. Second, we analyze the spear and shield relation between Byzantine attack and defense from three aspects: the vulnerability of CSS to attack, the obstacles in CSS to defense, and the games between attack and defense. Then, we propose a taxonomy of the existing Byzantine attack behaviors and elaborate on the corresponding attack parameters, which determine where, who, how, and when to launch attacks. Next, from the perspectives of homogeneous or heterogeneous scenarios, we classify the existing defense algorithms, and provide an in-depth tutorial on the state-of-the-art Byzantine defense schemes, commonly known as robust or secure CSS in the literature. Furthermore, we highlight the unsolved research challenges and depict the future research directions.Comment: Accepted by IEEE Communications Surveys and Tutoiral

    TRIDEnT: Building Decentralized Incentives for Collaborative Security

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    Sophisticated mass attacks, especially when exploiting zero-day vulnerabilities, have the potential to cause destructive damage to organizations and critical infrastructure. To timely detect and contain such attacks, collaboration among the defenders is critical. By correlating real-time detection information (alerts) from multiple sources (collaborative intrusion detection), defenders can detect attacks and take the appropriate defensive measures in time. However, although the technical tools to facilitate collaboration exist, real-world adoption of such collaborative security mechanisms is still underwhelming. This is largely due to a lack of trust and participation incentives for companies and organizations. This paper proposes TRIDEnT, a novel collaborative platform that aims to enable and incentivize parties to exchange network alert data, thus increasing their overall detection capabilities. TRIDEnT allows parties that may be in a competitive relationship, to selectively advertise, sell and acquire security alerts in the form of (near) real-time peer-to-peer streams. To validate the basic principles behind TRIDEnT, we present an intuitive game-theoretic model of alert sharing, that is of independent interest, and show that collaboration is bound to take place infinitely often. Furthermore, to demonstrate the feasibility of our approach, we instantiate our design in a decentralized manner using Ethereum smart contracts and provide a fully functional prototype.Comment: 28 page

    A Voice for the Voiceless: Peer-to-peer Mobile Phone Networks for a Community Radio Service

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    We propose a new application for mobile ad-hoc networks (MANETs) – community radio. We argue how MANETS help overcome important limitations in how community radio is currently operationalized. We identify critical design elements for a MANET based community radio service and propose a broad architecture for the same. We then investigate a most critical issue– the choice of the network wide broadcast protocol for the audio content. We identify desired characteristics of a community radio broadcasting service. We choose and evaluate eight popular broadcasting protocols on these characteristics, to find the protocols most suited for our application.
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