Littérature scientifique sur le sujet « Location- Privacy control »
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Articles de revues sur le sujet "Location- Privacy control"
Yunxiang, Zhang, et Wang Bin. « Stability Control of Position Flow Fuzzy Estimation in Swarm Intelligence Aware Privacy Protection ». Wireless Communications and Mobile Computing 2023 (30 janvier 2023) : 1–8. http://dx.doi.org/10.1155/2023/4792248.
Texte intégralPeng, Tao, Qin Liu et Guojun Wang. « Enhanced Location Privacy Preserving Scheme in Location-Based Services ». IEEE Systems Journal 11, no 1 (mars 2017) : 219–30. http://dx.doi.org/10.1109/jsyst.2014.2354235.
Texte intégralZhu, Liang, Xiaowei Liu, Zhiyong Jing, Liping Yu, Zengyu Cai et Jianwei Zhang. « Knowledge-Driven Location Privacy Preserving Scheme for Location-Based Social Networks ». Electronics 12, no 1 (24 décembre 2022) : 70. http://dx.doi.org/10.3390/electronics12010070.
Texte intégralYang, Guangcan, Shoushan Luo, Yang Xin, Hongliang Zhu, Jingkai Wang, Mingzhen Li et Yunfeng Wang. « A Search Efficient Privacy-Preserving Location-Sharing Scheme in Mobile Online Social Networks ». Applied Sciences 10, no 23 (25 novembre 2020) : 8402. http://dx.doi.org/10.3390/app10238402.
Texte intégralPerusco, Laura, et Katina Michael. « Control, trust, privacy, and security : evaluating location-based services ». IEEE Technology and Society Magazine 26, no 1 (2007) : 4–16. http://dx.doi.org/10.1109/mtas.2007.335564.
Texte intégralLuceri, Luca, Davide Andreoletti, Massimo Tornatore, Torsten Braun et Silvia Giordano. « Measurement and control of geo-location privacy on Twitter ». Online Social Networks and Media 17 (mai 2020) : 100078. http://dx.doi.org/10.1016/j.osnem.2020.100078.
Texte intégralChu, Xiang, Jun Liu, Daqing Gong et Rui Wang. « Preserving Location Privacy in Spatial Crowdsourcing Under Quality Control ». IEEE Access 7 (2019) : 155851–59. http://dx.doi.org/10.1109/access.2019.2949409.
Texte intégralQi He, Dapeng Wu et P. Khosla. « The quest for personal control over mobile location privacy ». IEEE Communications Magazine 42, no 5 (mai 2004) : 130–36. http://dx.doi.org/10.1109/mcom.2004.1299356.
Texte intégralGóes, Rômulo Meira, Blake C. Rawlings, Nicholas Recker, Gregory Willett et Stéphane Lafortune. « Demonstration of Indoor Location Privacy Enforcement using Obfuscation ». IFAC-PapersOnLine 51, no 7 (2018) : 145–51. http://dx.doi.org/10.1016/j.ifacol.2018.06.293.
Texte intégralXu, Chuan, Li Luo, Yingyi Ding, Guofeng Zhao et Shui Yu. « Personalized Location Privacy Protection for Location-Based Services in Vehicular Networks ». IEEE Wireless Communications Letters 9, no 10 (octobre 2020) : 1633–37. http://dx.doi.org/10.1109/lwc.2020.2999524.
Texte intégralThèses sur le sujet "Location- Privacy control"
Jedrzejczyk, Lukasz. « Supporting location privacy management through feedback and control ». Thesis, Open University, 2012. http://oro.open.ac.uk/36211/.
Texte intégralCerf, Sophie. « control theory for computing systems : application to big-data cloud services & ; location privacy protection ». Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAT024.
Texte intégralThis thesis presents an application of Control Theory for Computing Systems. It aims at investigating techniques to build and control efficient, dependable and privacy-preserving computing systems. Ad-hoc service configuration require a high level of expertise which could benefit from automation in many ways. A control algorithm can handle bigger and more complex systems, even when they are extremely sensitive to variations in their environment. However, applying control to computing systems raises several challenges, e.g. no physics governs the applications. On one hand, the mathematical framework provided by control theory can be used to improve automation and robustness of computing systems. Moreover, the control theory provides by definition mathematical guarantees that its objectives will be fulfilled. On the other hand, the specific challenges of such use cases enable to expand the control theory itself. The approach taken in this work is to use two application computing systems: location privacy and cloud control. Those two use-cases are complementary in the nature of their technologies and softwares, their scale and in their end-users.The widespread of mobile devices has fostered the broadcasting and collection of users’ location data. It could be for the user to benefit from a personalized service (e.g. weather forecast or route planning) or for the service provider or any other third party to derive useful information from the mobility databases (e.g. road usage frequency or popularity of places). Indeed, many information can be retrieved from location data, including highly sensitive personal data. To overcome this privacy breach, Location Privacy Protection Mechanisms (LPPMs) have been developed. They are algorithm that modify the user’s mobility data, hopefully to hide some sensitive information. However, those tools are not easily configurable by non experts and are static processes that do not adapt to the user’s mobility. We develop two tools, one for already collected databases and one for online usage, that, by tuning the LPPMs, guarantee to the users objective-driven levels of privacy protection and of service utility preservation. First, we present an automated tool able to choose and configure LPPMs to protect already collected databases while ensuring a trade-off between privacy protection and database processing quality. Second, we present the first formulation of the location privacy challenge in control theory terms (plant and control, disturbance and performance signals), and a feedback controller to serve as a proof of concept. In both cases, design, implementation and validation has been done through experiments using data of real users collected on the field.The surge in data generation of the last decades, the so-called bigdata, has lead to the development of frameworks able to analyze them, such as the well known MapReduce. Advances in computing practices has also settled the cloud paradigms (where low-level resources can be rented to allow the development of higher level application without dealing with consideration such as investment in hardware or maintenance) as premium solution for all kind of users. Ensuring the performances of MapReduce jobs running on clouds is thus a major concern for the big IT companies and their clients. In this work, we develop advanced monitoring techniques of the jobs execution time and the platform availability by tuning the resource cluster size and realizing admission control, in spite of the unpredictable client workload. In order to deal with the non linearities of the MapReduce system, a robust adaptive feedback controller has been designed. To reduce the cluster utilization (leading to massive financial and energetic costs), we present a new event-based triggering mechanism formulation combined with an optimal predictive controller. Evaluation is done on a MapReduce benchmark suite running on a large-scale cluster, and using real jobs workloads
Chini, Foroushan Amir Hossein. « Protecting Location-Data Against Inference Attacks Using Pre-Defined Personas ». Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-66792.
Texte intégralArdagna, C. A. « Privacy and security in distributed and pervasive systems ». Doctoral thesis, Università degli Studi di Milano, 2008. http://hdl.handle.net/2434/55664.
Texte intégralLin, Yousi. « Spectrum Management Issues in Centralized and Distributed Dynamic Spectrum Access ». Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/104362.
Texte intégralDoctor of Philosophy
Due to the rapid growth in wireless communication demands, the frequency spectrum is becoming increasingly crowded. Traditional spectrum allocation policy gives the unshared access of fixed bands to the licensed users, and there is little unlicensed spectrum left now to allocate to newly emerged communication demands. However, studies on spectrum occupancy show that many licensed users who own the license of certain bands are only active for a small percentage of time, which results in plenty of underutilized spectrum. Hence, a new spectrum sharing paradigm, called dynamic spectrum access (DSA), is proposed to mitigate this problem. DSA enables the spectrum sharing between different classes of users, generally, the unlicensed users in the DSA system can access the licensed spectrum opportunistically without interfering with the licensed users. Based on architecture design, DSA systems can be categorized as centralized and distributed. In centralized systems, a central controller will make decisions on spectrum usage for all unlicensed users. Whereas in distributed systems, unlicensed users can make decisions for themselves independently. To successfully enable DSA, both centralized and distributed DSA systems need to deal with spectrum management issues, such as resource allocation problems and user privacy issues, etc. The resource allocation problems include, for example, the problems to discover and allocate idle bands and the problems to control users' transmit power for successful coexistence. Privacy issues may also arise during the spectrum management process since certain information exchange is inevitable for global decision making. However, due to the Federal Communications Commission's (FCC) regulation, licensed users' privacy such as their location information must be protected in any case. As a result, dynamic and efficient spectrum management techniques are necessary for DSA users. In this dissertation, we investigate the above-mentioned spectrum management issues in both types of DSA systems, specifically, the spectrum sensing challenges with licensed user location privacy issues in centralized DSA, and the spectrum sharing problems in distributed DSA systems. In doing so, we propose novel schemes for solving each related spectrum management problem and demonstrate their efficacy through the results from extensive evaluations and simulations. We believe that this dissertation provides insightful advice for DSA users to solve different spectrum management issues for enabling DSA implementation, and hence helps in a wider adoption of dynamic spectrum sharing.
Chu, Yu-Shan, et 朱育姍. « How Private Benefit of Control Affects Emerging Market Enterprises FDI Location Choices ». Thesis, 2015. http://ndltd.ncl.edu.tw/handle/74300086758241454361.
Texte intégral輔仁大學
金融與國際企業學系金融碩士班
103
Most of previous research focused on location selectivity by analyzing environmental factors or competitive advantages, and majority of the sample are in developed countries. However, with the rise of emerging markets, most of the companies have one or more control shareholders who can lead the business decisions. Due to this reason, those companies will consider the other factors that differ from the companies in developed countries when they face overseas investment decisions. Therefore, this study focuses on the companies in emerging markets, and analyzes the view of private benefit of control, investigates the relationship between private benefits and oversea investment locations choices. Our samples period is from 2009 to 2013. We examine whether private benefit will affect the choice of oversea investment locations. We discuss it from three aspects: ownership structure, transaction and management. Empirical results show that there is a negative relation between divergence in control and cash flow rights, related party transaction and earnings management. This means control shareholders may try to influence corporate to invest in the region with weak institutions because they want to protect their private benefits, and avoid the monitoring mechanism reducing the scope of private benefits. However, there are no significant relations between cash holding and external environment institution. We believe that besides consideration for investment demand, there are other purposes of cash holding. As a result, when the companies of emerging market face oversea investment decisions, private benefit is also one of the factor that will affect the location choices.
Livres sur le sujet "Location- Privacy control"
Sushil, Jajodia, Samarati Pierangela, Wang X. Sean et SpringerLink (Online service), dir. Privacy in Location-Based Applications : Research Issues and Emerging Trends. Berlin, Heidelberg : Springer Berlin Heidelberg, 2009.
Trouver le texte intégralJordan, Frith, dir. Mobile interfaces in public spaces : Locational privacy, control, and urban sociability. New York, NY : Routledge, 2012.
Trouver le texte intégralInstitute of Medicine (U.S.). Committee on the Role of Institutional Review Boards in Health Services Research Data Privacy Protection. Protecting data privacy in health services research. Washington, D.C : National Academy Press, 2000.
Trouver le texte intégralFrith, Jordan, et Adriana de Souza e Silva. Mobile Interfaces in Public Spaces : Locational Privacy, Control, and Urban Sociability. Taylor & Francis Group, 2012.
Trouver le texte intégralFrith, Jordan, et Adriana de Souza e Silva. Mobile Interfaces in Public Spaces : Locational Privacy, Control, and Urban Sociability. Taylor & Francis Group, 2012.
Trouver le texte intégralMedicine, Institute of, Division of Health Care Services et Committee on the Role of Institutional Review Boards in Health Services Research Data Privacy Protection. Protecting Data Privacy in Health Services Research. National Academies Press, 2000.
Trouver le texte intégralChapitres de livres sur le sujet "Location- Privacy control"
Ardagna, Claudio A., Marco Cremonini, Sabrina De Capitani di Vimercati et Pierangela Samarati. « Access Control in Location-Based Services ». Dans Privacy in Location-Based Applications, 106–26. Berlin, Heidelberg : Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03511-1_5.
Texte intégralSolomon, Michael G., Vaidy Sunderam, Li Xiong et Ming Li. « Mutually Private Location Proximity Detection with Access Control ». Dans Data and Applications Security and Privacy XXXI, 164–84. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61176-1_9.
Texte intégralUlltveit-Moe, Nils, et Vladimir Oleshchuk. « Mobile Security with Location-Aware Role-Based Access Control ». Dans Security and Privacy in Mobile Information and Communication Systems, 172–83. Berlin, Heidelberg : Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30244-2_15.
Texte intégralSmith, Ian, Giovanni Iachello et Mika Raento. « Mobile HCI 2004 Workshop on Location Systems Privacy and Control ». Dans Mobile Human-Computer Interaction - MobileHCI 2004, 525–26. Berlin, Heidelberg : Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-28637-0_72.
Texte intégralPennekamp, Jan, Anastasiia Belova, Thomas Bergs, Matthias Bodenbenner, Andreas Bührig-Polaczek, Markus Dahlmanns, Ike Kunze et al. « Evolving the Digital Industrial Infrastructure for Production : Steps Taken and the Road Ahead ». Dans Internet of Production, 1–25. Cham : Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-98062-7_2-1.
Texte intégralVaidya, Tavish, et Micah Sherr. « Mind Your $$(R, \varPhi )$$ s : Location-Based Privacy Controls for Consumer Drones ». Dans Security Protocols XXIII, 80–90. Cham : Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26096-9_9.
Texte intégralVaidya, Tavish, et Micah Sherr. « Mind Your $$(R, \varPhi )$$ s : Location-Based Privacy Controls for Consumer Drones (Transcript of Discussion) ». Dans Security Protocols XXIII, 91–104. Cham : Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26096-9_10.
Texte intégralChen, Jiahang, et Jürgen Roßmann. « Integration of an IoT Communication Infrastructure in Distributed Production Systems in Industry 4.0 ». Dans Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2022, 367–77. Cham : Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-10071-0_30.
Texte intégralEldin, Amr Ali, et Zoran Stojanovic. « Privacy Control Requirements for Context-Aware Mobile Services ». Dans Ubiquitous and Pervasive Computing, 1465–80. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-960-1.ch091.
Texte intégralMagkos, Emmanouil. « Cryptographic Approaches for Privacy Preservation in Location-Based Services ». Dans Systems Approach Applications for Developments in Information Technology, 273–97. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-1562-5.ch019.
Texte intégralActes de conférences sur le sujet "Location- Privacy control"
Koufogiannis, Fragkiskos, et George J. Pappas. « Location-dependent privacy ». Dans 2016 IEEE 55th Conference on Decision and Control (CDC). IEEE, 2016. http://dx.doi.org/10.1109/cdc.2016.7799441.
Texte intégralHongxia Jin, Gokay Saldamli, Richard Chow et Bart P. Knijnenburg. « Recommendations-based location privacy control ». Dans 2013 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops 2013). IEEE, 2013. http://dx.doi.org/10.1109/percomw.2013.6529526.
Texte intégralHeng Liu, Tiejun Wang, Ming Sun, Zhen Liu et Mingtian Zhou. « Location privacy in sparse environment ». Dans 2010 2nd International Conference on Advanced Computer Control. IEEE, 2010. http://dx.doi.org/10.1109/icacc.2010.5486958.
Texte intégralRama Krishna, T. Siva, L. Venkateswara Kiran et P. Siva Prasad. « Privacy control on location and co-location in interdependent data ». Dans 2019 International Conference on Vision Towards Emerging Trends in Communication and Networking (ViTECoN). IEEE, 2019. http://dx.doi.org/10.1109/vitecon.2019.8899664.
Texte intégralYang, Tao, Cong Tang, Liangwen Yu, Wei Xin, Yong Deng, Jianbin Hu et Zhong Chen. « VLSP : Enabling Location Privacy in Vehicular Location Based Services ». Dans 2011 First International Conference on Instrumentation, Measurement, Computer, Communication and Control (IMCCC). IEEE, 2011. http://dx.doi.org/10.1109/imccc.2011.121.
Texte intégralZheng, Jiangyu, Xiaobin Tan, Cliff Zou, Yukun Niu et Jin Zhu. « A cloaking-based approach to protect location privacy in location-based services ». Dans 2014 33rd Chinese Control Conference (CCC). IEEE, 2014. http://dx.doi.org/10.1109/chicc.2014.6895872.
Texte intégralWang, Na, et Haiyang Yu. « Generating Perturbations with Hilbert Curves and Differential Privacy for Location Privacy ». Dans 2017 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2017). Paris, France : Atlantis Press, 2017. http://dx.doi.org/10.2991/mecae-17.2017.17.
Texte intégralTong, Wei, et Xi Feng. « Location Privacy Protection and Location Verification Mechanism of Vehicle in VANET ». Dans 2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC). IEEE, 2023. http://dx.doi.org/10.1109/itnec56291.2023.10082547.
Texte intégralLei, Zhang, Yu Lili, Li Jing et Meng Fanbo. « Location privacy protection algorithm based on correlation coefficient ». Dans 2018 4th International Conference on Control, Automation and Robotics (ICCAR). IEEE, 2018. http://dx.doi.org/10.1109/iccar.2018.8384695.
Texte intégralLakadkutta, Ahmed H. I., et R. V. Mante. « Location based privacy preserving access control for relational data ». Dans 2016 IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT). IEEE, 2016. http://dx.doi.org/10.1109/rteict.2016.7808206.
Texte intégralRapports d'organisations sur le sujet "Location- Privacy control"
Qi, Yan, Ryan Fries, Shambhu Saran Baral et Pranesh Biswas. Evaluating the Costs and Benefits of Snow Fences in Illinois : Phase 2. Illinois Center for Transportation, novembre 2020. http://dx.doi.org/10.36501/0197-9191/20-020.
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