In recent times, we are witnessing an increasing concern by governments and intelligence agencies to deploy mass-surveillance systems that help them fight terrorism. In this paper, we conduct a formal analysis of the overall cost of such surveillance systems. Our analysis starts with a fairly-known result in statistics, namely, the false-positive paradox. We propose a quantitative measure of the total cost of a monitoring program, and study a detection system that is designed to minimize it, subject to a constraint in the number of terrorists the agency wishes to capture. In the absence of real, accurate behavioral models, we perform our analysis on the basis of several simple but insightful examples. With these examples, we illustrate the different parameters involved in the design of the detection system, and provide some indicative and representative figures of the cost of the monitoring program.
In recent times, we are witnessing an increasing concern by governments and intelligence agencies to deploy mass-surveillance systems that help them fight terrorism. In this paper, we conduct a formal analysis of the overall cost of such surveillance systems. Our analysis starts with a fairly-known result in statistics, namely, the false-positive paradox. We propose a quantitative measure of the total cost of a monitoring program, and study a detection system that is designed to minimize it, subject to a constraint in the number of terrorists the agency wishes to capture. In the absence of real, accurate behavioral models, we perform our analysis on the basis of several simple but insightful examples. With these examples, we illustrate the different parameters involved in the design of the detection system, and provide some indicative and representative figures of the cost of the monitoring program.
In the scenario of social bookmarking, a user browsing the Web bookmarks web pages and assigns free-text labels (i.e., tags) to them according to their personal preferences. The benefits of social tagging are clear – tags enhance Web content browsing and search. However, since these tags may be publicly available to any Internet user, a privacy attacker may collect this information and extract an accurate snapshot of users' interests or user profiles, containing sensitive information, such as health-related information, political preferences, salary or religion. In order to hinder attackers in their efforts to profile users, this report focuses on the practical aspects of capturing user interests from their tagging activity. More accurately, we study how to categorise a collection of tags posted by users in one of the most popular bookmarking services, Delicious (http://delicious.com). ; Preprint
In the scenario of social bookmarking, a user browsing the Web bookmarks web pages and assigns free-text labels (i.e., tags) to them according to their personal preferences. The benefits of social tagging are clear – tags enhance Web content browsing and search. However, since these tags may be publicly available to any Internet user, a privacy attacker may collect this information and extract an accurate snapshot of users' interests or user profiles, containing sensitive information, such as health-related information, political preferences, salary or religion. In order to hinder attackers in their efforts to profile users, this report focuses on the practical aspects of capturing user interests from their tagging activity. More accurately, we study how to categorise a collection of tags posted by users in one of the most popular bookmarking services, Delicious (http://delicious.com). ; Preprint
This research work is part of J. Estrada-Jiménez's Ph.D. thesis ; The ability of the online marketing industry to track and pro le users' Web-browsing activity is what enables effective, tailored-made advertising services. The intrusiveness of these practices and the increasing invasiveness of digital advertising, however, have raised serious concerns regarding user privacy. Although the level of ubiquity of tracking and advertising has been investigated in top-world sites based in North America and Western Europe, the extent to which those practices are carried out in territories with less or no legal coverage in terms of data protection has not been studied so far. In this work, we present the rst detailed measurement of online tracking and advertising conducted to date in one of those regions, namely, Ibero-America, by analyzing local websites (e.g., education and government sites). In doing so, our measurement study aims to nd out how user location as well as the type of publisher may impact on tracking and advertising and thus user privacy. Lastly, our thorough, extensive analysis also explores whether differences are appreciated between Latin America and the EU with regard to the third-party tracking conducted from and towards the corresponding countries. ; This work was supported by the Spanish Ministerio de Economía y Competitividad (MINECO) through the project ``Secure SMArt Grid using Open Source Intelligence. Data Privacy and Reliable Communications (MAGOS)'', ref. TEC2017-84197-C4-3-R. The research was also supported by the La Caixa Foundation under Grant ID 100010434, in part by the European Union's Horizon 2020 Research and Innovation Programme through the Marie Sklodowska-Curie under Grant 847648, and in part by the Fellowship under Grant LCF/BQ/PR20/11770009. ; Peer Reviewed ; Postprint (published version)
