127,917 research outputs found
Towards trajectory anonymization: a generalization-based approach
Trajectory datasets are becoming popular due to the massive usage of GPS and locationbased services. In this paper, we address privacy issues regarding the identification of individuals in static trajectory datasets. We first adopt the notion of k-anonymity to trajectories and propose a novel generalization-based approach for anonymization of trajectories. We further show that releasing
anonymized trajectories may still have some privacy leaks. Therefore we propose a randomization based reconstruction algorithm for releasing anonymized trajectory data and also present how the underlying techniques can be adapted to other anonymity standards. The experimental results on real and synthetic trajectory datasets show the effectiveness of the proposed techniques
BlockTag: Design and applications of a tagging system for blockchain analysis
Annotating blockchains with auxiliary data is useful for many applications.
For example, e-crime investigations of illegal Tor hidden services, such as
Silk Road, often involve linking Bitcoin addresses, from which money is sent or
received, to user accounts and related online activities. We present BlockTag,
an open-source tagging system for blockchains that facilitates such tasks. We
describe BlockTag's design and present three analyses that illustrate its
capabilities in the context of privacy research and law enforcement
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MobileTrust: Secure Knowledge Integration in VANETs
Vehicular Ad hoc NETworks (VANET) are becoming popular due to the emergence of the Internet of Things and ambient intelligence applications. In such networks, secure resource sharing functionality is accomplished by incorporating trust schemes. Current solutions adopt peer-to-peer technologies that can cover the large operational area. However, these systems fail to capture some inherent properties of VANETs, such as fast and ephemeral interaction, making robust trust evaluation of crowdsourcing challenging. In this article, we propose MobileTrust—a hybrid trust-based system for secure resource sharing in VANETs. The proposal is a breakthrough in centralized trust computing that utilizes cloud and upcoming 5G technologies to provide robust trust establishment with global scalability. The ad hoc communication is energy-efficient and protects the system against threats that are not countered by the current settings. To evaluate its performance and effectiveness, MobileTrust is modelled in the SUMO simulator and tested on the traffic features of the small-size German city of Eichstatt. Similar schemes are implemented in the same platform to provide a fair comparison. Moreover, MobileTrust is deployed on a typical embedded system platform and applied on a real smart car installation for monitoring traffic and road-state parameters of an urban application. The proposed system is developed under the EU-founded THREAT-ARREST project, to provide security, privacy, and trust in an intelligent and energy-aware transportation scenario, bringing closer the vision of sustainable circular economy
Tracing Transactions Across Cryptocurrency Ledgers
One of the defining features of a cryptocurrency is that its ledger,
containing all transactions that have evertaken place, is globally visible. As
one consequenceof this degree of transparency, a long line of recent re-search
has demonstrated that even in cryptocurrenciesthat are specifically designed to
improve anonymity it is often possible to track money as it changes hands,and
in some cases to de-anonymize users entirely. With the recent proliferation of
alternative cryptocurrencies, however, it becomes relevant to ask not only
whether ornot money can be traced as it moves within the ledgerof a single
cryptocurrency, but if it can in fact be tracedas it moves across ledgers. This
is especially pertinent given the rise in popularity of automated trading
platforms such as ShapeShift, which make it effortless to carry out such
cross-currency trades. In this paper, weuse data scraped from ShapeShift over a
thirteen-monthperiod and the data from eight different blockchains to explore
this question. Beyond developing new heuristics and creating new types of links
across cryptocurrency ledgers, we also identify various patterns of
cross-currency trades and of the general usage of these platforms, with the
ultimate goal of understanding whetherthey serve a criminal or a profit-driven
agenda.Comment: 14 pages, 13 tables, 6 figure
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