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NRand‐K : Minimizing the impact of location obfuscation in spatial analysis / Mayra Zurbaran in Transactions in GIS, vol 22 n° 5 (October 2018)
[article]
Titre : NRand‐K : Minimizing the impact of location obfuscation in spatial analysis Type de document : Article/Communication Auteurs : Mayra Zurbaran, Auteur ; Pedro Wightman, Auteur ; Maria Antonia Brovelli, Auteur ; Daniele Oxoli, Auteur Année de publication : 2018 Article en page(s) : pp 1257 - 1274 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse comparative
[Termes IGN] anonymisation
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] exploration de données géographiques
[Termes IGN] protection de la vie privéeRésumé : (Auteur) Location privacy, or geoprivacy, is critical to secure users’ privacy in context‐aware applications. Location‐based services pose privacy risks for users, due to the inferences that could be made about them from their location information and the potential misuse of this data by service providers or third‐party companies. A common solution is to apply masking or location obfuscation, which degrades location information quality while keeping a geographic coordinate structure. However, there is a trade‐off between privacy, quality of service, and quality of information, the last one being a valuable asset for companies. NRand is a location privacy mechanism with obfuscation capabilities and resistance against filtering attacks. In order to minimize the impact on location information quality, NRand‐K has been introduced. This algorithm is designed for use when releasing location information to third parties or as open data with privacy concerns. To assess the impact of location obfuscation on exploratory spatial data analysis (ESDA), a comparison is performed between obfuscated data with NRand, NRand‐K, and unaltered data. For the experiments, geolocated tweets collected during the Central Italy 2016 earthquake are used. Results show that NRand‐K reduces the impact on ESDA, where inferences were similar to those obtained with the unaltered data. Numéro de notice : A2018-573 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12462 Date de publication en ligne : 11/10/2018 En ligne : https://doi.org/10.1111/tgis.12462 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92298
in Transactions in GIS > vol 22 n° 5 (October 2018) . - pp 1257 - 1274[article]Efficient task assignment in spatial crowdsourcing with worker and task privacy protection / An Liu in Geoinformatica, vol 22 n° 2 (April 2018)
[article]
Titre : Efficient task assignment in spatial crowdsourcing with worker and task privacy protection Type de document : Article/Communication Auteurs : An Liu, Auteur ; Weiqi Wang, Auteur ; Shuo Shang, Auteur ; Qing Li, Auteur ; Xiangliang Zhang, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] cryptage
[Termes IGN] données localisées des bénévoles
[Termes IGN] géolocalisation
[Termes IGN] production participative
[Termes IGN] protection de la vie privéeRésumé : (Auteur) Spatial crowdsourcing (SC) outsources tasks to a set of workers who are required to physically move to specified locations and accomplish tasks. Recently, it is emerging as a promising tool for emergency management, as it enables efficient and cost-effective collection of critical information in emergency such as earthquakes, when search and rescue survivors in potential ares are required. However in current SC systems, task locations and worker locations are all exposed in public without any privacy protection. SC systems if attacked thus have penitential risk of privacy leakage. In this paper, we propose a protocol for protecting the privacy for both workers and task requesters while maintaining the functionality of SC systems. The proposed protocol is built on partially homomorphic encryption schemes, and can efficiently realize complex operations required during task assignment over encrypted data through a well-designed computation strategy. We prove that the proposed protocol is privacy-preserving against semi-honest adversaries. Simulation on two real-world datasets shows that the proposed protocol is more effective than existing solutions and can achieve mutual privacy-preserving with acceptable computation and communication cost. Numéro de notice : A2018-367 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-017-0305-2 En ligne : https://doi.org/10.1007/s10707-017-0305-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90732
in Geoinformatica > vol 22 n° 2 (April 2018)[article]Trois catégories de détenteurs de droits / Elizabeth Botrel in Géomètre, n° 2156 (mars 2018)
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Titre : Trois catégories de détenteurs de droits Type de document : Article/Communication Auteurs : Elizabeth Botrel, Auteur Année de publication : 2018 Article en page(s) : pp 34 - 35 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] droit d'exploitation
[Termes IGN] espace public
[Termes IGN] propriété intellectuelle
[Termes IGN] protection de la vie privée
[Termes IGN] semis de pointsRésumé : (Auteur) L'exploitation des images dans des lieux publics ou privés se généralise dans les cabinets de géomètres-experts. Rappel d'un certain nombre de règles du droit pour sécuriser leur acquisition et leur utilisation dans un cadre professionnel. Numéro de notice : A2018-075 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89435
in Géomètre > n° 2156 (mars 2018) . - pp 34 - 35[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 063-2018031 RAB Revue Centre de documentation En réserve L003 Disponible EPLA : efficient personal location anonymity / Dapeng Zhao in Geoinformatica, vol 22 n° 1 (January 2018)
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Titre : EPLA : efficient personal location anonymity Type de document : Article/Communication Auteurs : Dapeng Zhao, Auteur ; Yuanyuan Jin, Auteur ; Kai Zhang, Auteur ; Xiaoling Wang, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 29 - 47 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] anonymisation
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] estimation par noyau
[Termes IGN] protection de la vie privée
[Termes IGN] service fondé sur la position
[Termes IGN] traitement de données localiséesRésumé : (auteur) A lot of researchers utilize side-information, such as the map which is likely to be exploited by some attackers, to protect users’ location privacy in location-based service (LBS). However, current technologies universally model the side-information for all users and don’t distinguish different users. We argue that the side-information is personal for every user. In this paper, we propose an efficient method, namely EPLA, to protect the users’ privacy using visit probability. We select the dummy locations to achieve k-anonymity according to personal visit probability for users’ queries. In EPLA, we use AKDE(Approximate Kernel Density Estimate), which greatly reduces the computational complexity compared with KDE approach. We conduct the comprehensive experimental study on the two real Gowalla and Foursqure data sets and the experimental results show that EPLA obtains fine privacy performance and low computation complexity. Numéro de notice : A2018-022 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1007/s10707-017-0303-4 En ligne : https://doi.org/10.1007/s10707-017-0303-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89170
in Geoinformatica > vol 22 n° 1 (January 2018) . - pp 29 - 47[article]Privacy-preserving detection of anomalous phenomena in crowdsourced environmental sensing using fine-grained weighted voting / Mihai Maruseac in Geoinformatica, vol 21 n° 4 (October - December 2017)
[article]
Titre : Privacy-preserving detection of anomalous phenomena in crowdsourced environmental sensing using fine-grained weighted voting Type de document : Article/Communication Auteurs : Mihai Maruseac, Auteur ; Gabriel Ghinita, Auteur ; Goce Trajcevski, Auteur ; Peter Scheuermann, Auteur Année de publication : 2017 Article en page(s) : pp 733 - 762 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] modèle sémantique de données
[Termes IGN] production participative
[Termes IGN] protection civile
[Termes IGN] protection de la vie privée
[Termes IGN] source de donnéesRésumé : (Auteur) This article addresses the problem of preserving privacy of individuals who participate in collaborative environmental sensing. We observe that in many applications of societal importance, one is interested in constructing a map of the spatial distribution of a given phenomenon (e.g., temperature, CO2 concentration, water polluting agents, etc.) and mobile users can contribute with providing measurements data. However, contributing data may leak sensitive private details, as an adversary could infer the presence of a person in a certain location at a given time. This, in turn, may reveal information about other contexts (e.g., health, lifestyle choices), and may even impact an individual’s physical safety. We introduce a technique for privacy-preserving detection of anomalous phenomena, where the privacy of the individuals participating in collaborative environmental sensing is protected according to the powerful semantic model of differential privacy. We propose a differentially-private index structure to address the specific needs of anomalous phenomenon detection and derive privacy preserving query strategies that judiciously allocate the privacy budget to maintain high data accuracy. In addition, we construct an analytical model to characterize the sensed value inaccuracy introduced by the differentially-private noise injection, derive error bounds, and perform a statistical analysis that allows us to improve accuracy by using custom weights for measurements in each cell of the index structure. Extensive experimental results show that the proposed approach achieves high precision in identifying anomalies, and incurs low computational overhead. Numéro de notice : A2017-602 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-017-0304-3 En ligne : https://doi.org/10.1007/s10707-017-0304-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86910
in Geoinformatica > vol 21 n° 4 (October - December 2017) . - pp 733 - 762[article]Geospatial big data and archaeology: Prospects and problems too great to ignore / Mark D. McCoy in Journal of archaeological science, vol 84 (August 2017)PermalinkMapping and the citizen sensor, ch 6. Considerations of privacy, ethics and legal issues in volunteered geographic information / Peter Mooney (2017)PermalinkThe location swapping method for geomasking / Su Zhang in Cartography and Geographic Information Science, Vol 44 n° 1 (January 2017)PermalinkLocation-based anonymization: comparison and evaluation of the Voronoi-based aggregation system / William Lee Croft in International journal of geographical information science IJGIS, vol 30 n° 11-12 (November - December 2016)PermalinkLocation K-anonymity in indoor spaces / Joon-Seok Kim in Geoinformatica, vol 20 n° 3 (July - September 2016)PermalinkAdaptive areal elimination (AAE): A transparent way of disclosing protected spatial datasets / Ourania Kounadi in Computers, Environment and Urban Systems, vol 57 (May 2016)PermalinkDasymetric mapping for an improved modeling of diseases / Gianluca Boo in Géomatique suisse, vol 114 n° 4 (avril 2016)PermalinkUn protocole basé sur des mobiles sécurisés pour une collecte participative de données spatiales en mobilité réellement anonyme / Dai Hai Ton That in Revue internationale de géomatique, vol 26 n° 2 (avril - juin 2016)PermalinkScalable and privacy-respectful interactive discovery of place semantics from human mobility traces / Natalia Andrienko in Information visualization, vol 15 n° 2 (April 2016)PermalinkPrivacy and spatial pattern preservation in masked GPS trajectory data / Dara E. Seidl in International journal of geographical information science IJGIS, vol 30 n° 3-4 (March - April 2016)Permalink