Academic literature on the topic 'Privacy Calculus'

Relationship building through social network sites (SNSs) requires privacy disclosure that involves a calculus of potential benefits against privacy risks. Tie formation (e.g., friending, following, or connecting) on SNSs is one of the most significant forms of privacy disclosure that not only communicate one’s willingness to disclose but can also reveal past activity history and invite future interactions. Based on the communication privacy management theory, the current study examines how users consider the privacy calculus and tie-formation affordances of the SNSs to manage ties across multiple SNSs. Using an online survey of 630 Facebook and/or Instagram users, the study revealed that individuals with higher privacy concerns strategically manage their privacy by connecting with different relationship ties through different SNSs as a way to construct sociotechnical boundaries between networks. The findings have implications for understanding privacy management online and provide a potential explanation for the privacy paradox.

Using privacy-protecting tools and reducing self-disclosure can decrease the likelihood of experiencing privacy violations. Whereas previous studies found people’s online self-disclosure being the result of privacy risk and benefit perceptions, the present study extended this so-called privacy calculus approach by additionally focusing on privacy protection by means of a tool. Furthermore, it is important to understand contextual differences in privacy behaviors as well as characteristics of privacy-protecting tools that may affect usage intention. Results of an online experiment (N = 511) supported the basic notion of the privacy calculus and revealed that perceived privacy risks were strongly related to participants’ desired privacy protection which, in turn, was positively related to the willingness to use a privacy-protecting tool. Self-disclosure was found to be context dependent, whereas privacy protection was not. Moreover, participants would rather forgo using a tool that records their data, although this was described to enhance privacy protection.

The “privacy calculus” approach to studying online privacy implies that willingness to engage in disclosures on social network sites (SNSs) depends on evaluation of the resulting risks and benefits. In this article, we propose that cultural factors influence the perception of privacy risks and social gratifications. Based on survey data collected from participants from five countries (Germany [ n = 740], the Netherlands [ n = 89], the United Kingdom [ n = 67], the United States [ n = 489], and China [ n = 165]), we successfully replicated the privacy calculus. Furthermore, we found that culture plays an important role: As expected, people from cultures ranking high in individualism found it less important to generate social gratifications on SNSs as compared to people from collectivist-oriented countries. However, the latter placed greater emphasis on privacy risks—presumably to safeguard the collective. Furthermore, we identified uncertainty avoidance to be a cultural dimension crucially influencing the perception of SNS risks and benefits. As expected, people from cultures ranking high in uncertainty avoidance found privacy risks to be more important when making privacy-related disclosure decisions. At the same time, these participants ascribed lower importance to social gratifications—possibly because social encounters are perceived to be less controllable in the social media environment.

Web of Linked Data introduces common format and principles for publishing and linking data on the Web. Such a network of linked data is publicly available and easily consumable. This paper introduces a calculus for modelling networks of linked data with encoded privacy preferences.In that calculus, a network is a parallel composition of users, where each user is named and consists of data, representing the user's profile, and a process. Data is a parallel composition of triples with names (resources) as components. Associated with each name and each triple of names are their privacy protection policies, that are represented by queries. A data triple is accessible to a user if the user's data satisfies the query assigned to that triple.The main contribution of this model lies in the type system which together with the introduced query order ensures that static type-checking prevents privacy violations. We say that a network is well behaved if —access to a triple is more restrictive than access to its components and less restrictive than access to the user name it is enclosed with,—each user can completely access their own profile,—each user can update or partly delete profiles that they own (can access the whole profiles), and—each user can update the privacy preference policy of data of another profile that they own or write data to another profile only if the newly obtained profile stays fully accessible to their owner.We prove that any well-typed network is well behaved.

Individuals are increasingly using personal Internet of Things (IoT) devices that digitize their day-to-day lives. Those devices, however, often require substantial personal information to generate their intended benefits. For example, fitness technologies collect health, sleep, personal, and a vast array of other information ubiquitously, creating possible privacy issues for the users when fitness technology platform providers store or share their information, whether users know this or not. To explore the role of privacy perceptions in the context of continued use of fitness technologies, this study collected data from 212 fitness tracker users. We find empirical support for the importance of privacy perceptions in a user's intention to continue to use their fitness tracker. More specifically, consistent with privacy calculus research, privacy concern is negatively related to willingness to disclose information while perceived benefit is positively related to it. As an extension to calculus variables, users' expectations towards the data sharing practices of organizations also influences their willingness to disclose information. Importantly, willingness to disclose information has a direct effect on continued use intentions but also moderates the relationship between perceived benefit and users' intentions to continue using a fitness tracker. We discuss the implications of these findings for research and practice.

The aim of this research was to identify the role of brand reputation in encouraging consumer willingness to provide personal data online, for the benefits of personalisation. This study extends on Malhotra, Kim and Agarwal’s (2004) Internet Users Information Privacy Concerns Model, and uses the theoretical underpinning of Social Contract Theory to assess how brand reputation moderates the relationship between trusting beliefs and perceived value (Privacy Calculus framework) with willingness to give personal information. The research is highly relevant as most privacy research undertaken to date focuses on consumer related concerns. Very little research exists examining the role of brand reputation and online privacy. Practical implications of this research include gaining knowledge as to how to minimise online privacy concerns; improve brand reputation; and provide insight on how to reduce consumer resistance to the collection of personal information and encourage consumer opt-in.

Advances in information technology have amplified issues related to privacy and the disclosure of personal information. New technologies have enabled an explosion in the amount and variety of information created, stored, and potentially shared about people, and there has been a corresponding explosion in privacy-related concerns and conversations in academic and non-academic forums. This dissertation contributes to one such conversation, adding to our understanding of the mechanisms that shape individuals' privacy concerns in the context of disclosure of personal information. Individuals must overcome their information privacy concerns in order for personal information disclosure to take place, but the mechanisms surrounding this process are highly dependent on the context of disclosure. Accordingly, this research seeks to build understanding around the ways in which privacy concerns are mitigated or counterbalanced in three different disclosure contexts. Essay 1, positioned in the e-commerce context, contributes uniquely to an emerging stream of disclosure research that considers irrationality within the privacy disclosure decision process. Essay 2 is focused on a less frequently examined disclosure context - online social networks - and examines the tension between individuals' privacy concerns and their desire for social benefits and personal expression, focusing especially on the social network technology's ability to support impression management behavior. Finally, Essay 3 examines the mitigation of privacy concerns in the context of involuntary disclosure - increasingly common in the modern online environment - wherein the primary goal is to reduce concerns or anxiety regarding the information already disclosed. In comparing disclosure processes across these contexts, this research provides insights regarding consistencies and distinctions among the different domains. Insights gained, both within and across these contexts, are valuable to both privacy researchers and professional stakeholders.

The privacy paradox is a phenomenon whereby individuals continue to disclose their personal information, contrary to their claim of concerns for the privacy of their personal information. This study investigated the privacy paradox to better understand individuals' decisions to disclose or withhold their personal information. The study argued that individuals’ decisions are based on a cognitive disposition, which involves both rational and emotional mental processes. While the extended privacy calculus model was used as the theoretical basis for the study, the findings of cognitive neuroscience was applied to it to address its limitation in assuming individuals are purely rational decision-makers. Three within-subjects experiments were conducted whereby each subject participated in all three experiments as if it were one. Experiment 1 captured the neural correlates of mental processes involved in privacy-related decisions, while experiment 2 and 3 were factorial-design experiments used for testing the relationship of neural correlates in predicting privacy concerns and personal information disclosure. The findings of this study indicated that at least one neural correlate of every mental process involved in privacy-related decisions significantly influenced personal information disclosure, except for uncertainty. However, there were no significant relationships between mental processes and privacy concerns, except Brodmann’s Area 13, a neural correlate of distrust. This relationship, however, had a positive relationship with privacy concerns, opposite to what was hypothesized. Furthermore, interaction effects indicated that individuals put more emphasis on negative perceptions in privacy-related situations. This study contributed to the information privacy field by supporting the argument that individuals’ privacy-related decisions are both rational and emotional. Specifically, the privacy paradox cannot be explained through solely rational cost-benefit analysis or through an examination of individuals’ emotions alone.

[EN] Nowadays, online social networks (OSNs) have become a mainstream cultural phenomenon for millions of Internet users. Social networks are an ideal environment for generating all kinds of social benefits for users. Users share experiences, keep in touch with their family, friends and acquaintances, and earn economic benefits from the power of their influence (which is translated into new job opportunities). However, the use of social networks and the action of sharing information imply the loss of the users’ privacy. Recently, a great interest in protecting the privacy of users has emerged. This situation has been due to documented cases of regrets in users’ actions, company scandals produced by misuse of personal information, and the biases introduced by privacy mechanisms. Social network providers have included improvements in their systems to reduce users’ privacy risks; for example, restricting privacy policies by default, adding new privacy settings, and designing quick and easy shortcuts to configure user privacy settings. In the privacy researcher area, new advances are proposed to improve privacy mechanisms, most of them focused on automation, fine-grained systems, and the usage of features extracted from the user’s profile information and interactions to recommend the best privacy policy for the user. Despite these advances, many studies have shown that users’ concern for privacy does not match the decisions they ultimately make in social networks. This misalignment in the users’ behavior might be due to the complexity of the privacy concept itself. This drawback causes users to disregard privacy risks, or perceive them as temporarily distant. Another cause of users’ behavior misalignment might be due to the complexity of the privacy decision-making process. This is because users should consider all possible scenarios and the factors involved (e.g., the number of friends, the relationship type, the context of the information, etc.) to make an appropriate privacy decision. The main contributions of this thesis are the development of metrics to assess privacy risks, and the proposal of explainable privacy mechanisms (using the developed metrics) to assist and raise awareness among users during the privacy decision process. Based on the definition of the concept of privacy, the dimensions of information scope and information sensitivity have been considered in this thesis to assess privacy risks. For explainable privacy mechanisms, soft paternalism techniques and gamification elements that make use of the proposed metrics have been designed. These mechanisms have been integrated into the social network PESEDIA and evaluated in experiments with real users. PESEDIA is a social network developed in the framework of the Master’s thesis of the Ph.D. student [15], this thesis, and the national projects “Privacy in Social Educational Environments during Childhood and Adolescence” (TIN2014-55206- R) and “Intelligent Agents for Privacy Advice in Social Networks” (TIN2017-89156-R). The findings confirm the validity of the proposed metrics for computing the users’ scope and the sensitivity of social network publications. For the scope metric, the results also showed the possibility of estimating it through local and social centrality metrics for scenarios with limited information access. For the sensitivity metric, the results also remarked the users’ misalignment for some information types and the consensus for a majority of them. The usage of these metrics as part of messages about potential consequences of privacy policy choices and information sharing actions to users showed positive effects on users’ behavior regarding privacy. Furthermore, the findings of exploring the users’ trade-off between costs and benefits during disclosure actions of personal information showed significant relationships with the usual social circles (family members, friends, coworkers, and unknown users) and their properties. This allowed designing better privacy mechanisms that appropriately restrict access to information and reduce regrets. Finally, gamification elements applied to social networks and users’ privacy showed a positive effect on the users’ behavior towards privacy and safe practices in social networks.
[ES] En la actualidad, las redes sociales se han convertido en un fenómeno cultural dominante para millones de usuarios de Internet. Las redes sociales son un entorno ideal para la generación de todo tipo de beneficios sociales para los usuarios. Los usuarios comparten experiencias, mantienen el contacto con sus familiares, amigos y conocidos, y obtienen beneficios económicos gracias al poder de su influencia (lo que se traduce en nuevas oportunidades de trabajo). Sin embargo, el uso de las redes sociales y la acción de compartir información implica la perdida de la privacidad de los usuarios. Recientemente ha emergido un gran interés en proteger la privacidad de los usuarios. Esta situación se ha debido a los casos de arrepentimientos documentados en las acciones de los usuarios, escándalos empresariales producidos por usos indebidos de la información personal, y a los sesgos que introducen los mecanismos de privacidad. Los proveedores de redes sociales han incluido mejoras en sus sistemas para reducir los riesgos en privacidad de los usuarios; por ejemplo, restringiendo las políticas de privacidad por defecto, añadiendo nuevos elementos de configuración de la privacidad, y diseñando accesos fáciles y directos para configurar la privacidad de los usuarios. En el campo de la investigación de la privacidad, nuevos avances se proponen para mejorar los mecanismos de privacidad la mayoría centrados en la automatización, selección de grano fino, y uso de características extraídas de la información y sus interacciones para recomendar la mejor política de privacidad para el usuario. A pesar de estos avances, muchos estudios han demostrado que la preocupación de los usuarios por la privacidad no se corresponde con las decisiones que finalmente toman en las redes sociales. Este desajuste en el comportamiento de los usuarios podría deberse a la complejidad del propio concepto de privacidad. Este inconveniente hace que los usuarios ignoren los riesgos de privacidad, o los perciban como temporalmente distantes. Otra causa del desajuste en el comportamiento de los usuarios podría deberse a la complejidad del proceso de toma de decisiones sobre la privacidad. Esto se debe a que los usuarios deben considerar todos los escenarios posibles y los factores involucrados (por ejemplo, el número de amigos, el tipo de relación, el contexto de la información, etc.) para tomar una decisión apropiada sobre la privacidad. Las principales contribuciones de esta tesis son el desarrollo de métricas para evaluar los riesgos de privacidad, y la propuesta de mecanismos de privacidad explicables (haciendo uso de las métricas desarrolladas) para asistir y concienciar a los usuarios durante el proceso de decisión sobre la privacidad. Atendiendo a la definición del concepto de la privacidad, las dimensiones del alcance de la información y la sensibilidad de la información se han considerado en esta tesis para evaluar los riesgos de privacidad. En cuanto a los mecanismos de privacidad explicables, se han diseñado utilizando técnicas de paternalismo blando y elementos de gamificación que hacen uso de las métricas propuestas. Estos mecanismos se han integrado en la red social PESEDIA y evaluado en experimentos con usuarios reales. PESEDIA es una red social desarrollada en el marco de la tesina de Master del doctorando [15], esta tesis y los proyectos nacionales “Privacidad en Entornos Sociales Educativos durante la Infancia y la Adolescencia” (TIN2014-55206-R) y “Agentes inteligentes para asesorar en privacidad en redes sociales” (TIN2017-89156-R). Los resultados confirman la validez de las métricas propuestas para calcular el alcance de los usuarios y la sensibilidad de las publicaciones de las redes sociales. En cuanto a la métrica del alcance, los resultados también mostraron la posibilidad de estimarla mediante métricas de centralidad local y social para escenarios con acceso limitado a la información. En cuanto a la métrica de sensibilidad, los resultados también pusieron de manifiesto la falta de concordancia de los usuarios en el caso de algunos tipos de información y el consenso en el caso de la mayoría de ellos. El uso de estas métricas como parte de los mensajes sobre las posibles consecuencias de las opciones de política de privacidad y las acciones de intercambio de información a los usuarios mostró efectos positivos en el comportamiento de los usuarios con respecto a la privacidad. Además, los resultados de la exploración de la compensación de los usuarios entre los costos y los beneficios durante las acciones de divulgación de información personal mostraron relaciones significativas con los círculos sociales habituales (familiares, amigos, compañeros de trabajo y usuarios desconocidos) y sus propiedades. Esto permitió diseñar mejores mecanismos de privacidad que restringen adecuadamente el acceso a la información y reducen los arrepentimientos. Por último, los elementos de gamificación aplicados a las redes sociales y a la privacidad de los usuarios mostraron un efecto positivo en el comportamiento de los usuarios hacia la privacidad y las prácticas seguras en las redes sociales.
[CA] En l’actualitat, les xarxes socials s’han convertit en un fenomen cultural dominant per a milions d’usuaris d’Internet. Les xarxes socials són un entorn ideal per a la generació de tota mena de beneficis socials per als usuaris. Els usuaris comparteixen experiències, mantenen el contacte amb els seus familiars, amics i coneguts, i obtenen beneficis econòmics gràcies al poder de la seva influència (el que es tradueix en noves oportunitats de treball). No obstant això, l’ús de les xarxes socials i l’acció de compartir informació implica la perduda de la privacitat dels usuaris. Recentment ha emergit un gran interès per protegir la privacitat dels usuaris. Aquesta situació s’ha degut als casos de penediments documentats en les accions dels usuaris, escàndols empresarials produïts per usos indeguts de la informació personal, i als caires que introdueixen els mecanismes de privacitat. Els proveïdors de xarxes socials han inclòs millores en els seus sistemes per a reduir els riscos en privacitat dels usuaris; per exemple, restringint les polítiques de privacitat per defecte, afegint nous elements de configuració de la privacitat, i dissenyant accessos fàcils i directes per a configurar la privacitat dels usuaris. En el camp de la recerca de la privacitat, nous avanços es proposen per a millorar els mecanismes de privacitat la majoria centrats en l’automatització, selecció de gra fi, i ús de característiques extretes de la informació i les seues interaccions per a recomanar la millor política de privacitat per a l’usuari. Malgrat aquests avanços, molts estudis han demostrat que la preocupació dels usuaris per la privacitat no es correspon amb les decisions que finalment prenen en les xarxes socials. Aquesta desalineació en el comportament dels usuaris podria deure’s a la complexitat del propi concepte de privacitat. Aquest inconvenient fa que els usuaris ignorin els riscos de privacitat, o els percebin com temporalment distants. Una altra causa de la desalineació en el comportament dels usuaris podria deure’s a la complexitat del procés de presa de decisions sobre la privacitat. Això es deu al fet que els usuaris han de considerar tots els escenaris possibles i els factors involucrats (per exemple, el nombre d’amics, el tipus de relació, el context de la informació, etc.) per a prendre una decisió apropiada sobre la privacitat. Les principals contribucions d’aquesta tesi són el desenvolupament de mètriques per a avaluar els riscos de privacitat, i la proposta de mecanismes de privacitat explicables (fent ús de les mètriques desenvolupades) per a assistir i conscienciar als usuaris durant el procés de decisió sobre la privacitat. Atesa la definició del concepte de la privacitat, les dimensions de l’abast de la informació i la sensibilitat de la informació s’han considerat en aquesta tesi per a avaluar els riscos de privacitat. Respecte als mecanismes de privacitat explicables, aquests s’han dissenyat utilitzant tècniques de paternalisme bla i elements de gamificació que fan ús de les mètriques propostes. Aquests mecanismes s’han integrat en la xarxa social PESEDIA i avaluat en experiments amb usuaris reals. PESEDIA és una xarxa social desenvolupada en el marc de la tesina de Màster del doctorant [15], aquesta tesi i els projectes nacionals “Privacitat en Entorns Socials Educatius durant la Infància i l’Adolescència” (TIN2014-55206-R) i “Agents Intel·ligents per a assessorar en Privacitat en xarxes socials” (TIN2017-89156-R). Els resultats confirmen la validesa de les mètriques propostes per a calcular l’abast de les accions dels usuaris i la sensibilitat de les publicacions de les xarxes socials. Respecte a la mètrica de l’abast, els resultats també van mostrar la possibilitat d’estimarla mitjançant mètriques de centralitat local i social per a escenaris amb accés limitat a la informació. Respecte a la mètrica de sensibilitat, els resultats també van posar de manifest la falta de concordança dels usuaris en el cas d’alguns tipus d’informació i el consens en el cas de la majoria d’ells. L’ús d’aquestes mètriques com a part dels missatges sobre les possibles conseqüències de les opcions de política de privacitat i les accions d’intercanvi d’informació als usuaris va mostrar efectes positius en el comportament dels usuaris respecte a la privacitat. A més, els resultats de l’exploració de la compensació dels usuaris entre els costos i els beneficis durant les accions de divulgació d’informació personal van mostrar relacions significatives amb els cercles socials habituals (familiars, amics, companys de treball i usuaris desconeguts) i les seves propietats. Això ha permés dissenyar millors mecanismes de privacitat que restringeixen adequadament l’accés a la informació i redueixen els penediments. Finalment, els elements de gamificació aplicats a les xarxes socials i a la privacitat dels usuaris van mostrar un efecte positiu en el comportament dels usuaris cap a la privacitat i les pràctiques segures en les xarxes socials.
Alemany Bordera, J. (2020). Measures of Privacy Protection on Social Environments [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/151456
TESIS

The Internet of Things (IoT) has been acknowledged as one of the most innovative forms of technology since the computer, because of the influence it can have on multiple sectors of physical and virtual environments. The growth of IoT is expected to continue, by 2020 the number of connected devices is estimated to reach 50 billion. Recent developments in IoT provide an unprecedented opportunity for personalised services and other benefits. To exploit these potential benefits as best as possible, individuals are willing to provide their personal information despite potential privacy breaches. Therefore, this paper examines factors that influence the willingness to disclose personal information in the use of IoT in South Africa (SA) with the use of the privacy calculus as the theoretical underpinnings of this research. The privacy calculus accentuates that a risk-benefit trade off occurs when an individual decides to disclose their personal information, however, it is assumed that there are more factors than perceived risks and perceived benefits that influence information disclosure. After analysing previous literature, this study identified the following factors; information sensitivity, privacy concerns, social influence, perceived benefits, (perceived) privacy risks and privacy knowledge as possible key tenants in relation to willingness to disclose personal information. This research took on an objective ontological view, with the underlying epistemological stance being positivistic. The research incorporated a deductive approach, employing the use of a conceptual model which was constructed from a combination of studies orientated around privacy, the privacy calculus and the privacy paradox. Data for this research was collected using the quantitative research approach, through the use of an anonymous online questionnaire, where the targeted population was narrowed down to the general public residing within SA that make use of IoT devices and/or services. Data was collected using Qualtrics and analysed using SmartPLS 3. SmartPLS 3 was used to test for correlations between the factors which influence information disclosure in the use of IoT by utilising the complete bootstrapping method. A key finding was that the privacy paradox is apparent within SA, where individuals pursue enjoyment and predominantly use IoT for leisure purposes, while individuals are more likely to adopt self-withdrawal tendencies when faced with heightened privacy concerns or potential risks.

Facebook is an integral part of today’s social landscape, but Facebook use involves compromising one’s privacy in relation to both other users and to the Facebook corporation and its affiliated businesses. This analysis explores respondents’ reasons for using Facebook together with their Facebook-related privacy concerns, and how these factors influence self-disclosures and privacy management strategies on the site. Also explored are respondents’ perceptions both of what the Facebook corporation ‘knows’ about them and with whom it shares their data. The research is based on the concepts of user-user and user-corporate privacy concerns versus the social needs of self-portrayal and belonging. Self-portrayal (inspired by Friedlander, 2011) is explored in the contexts of both strategic self-presentation and expression of the true self, and belonging is explored in the contexts of both intimacy and affiliation. These concepts have been drawn from a combination of psychological theories together with existing research on privacy concerns and social needs on social networking sites. Respondents completed an online questionnaire over a six week period from late August to early October 2014, and a focus group was held in November 2014. The questionnaire was largely quantitative but allowed for qualitative input via text boxes. There were 404 completed and valid responses, and of the demographic factors tested, gender was most strongly associated with Facebook-related privacy concerns and age was most strongly associated with reasons for using Facebook. Respondents indicated a clash between fulfilling their social needs on Facebook and their privacy concerns on the site. However, these concerns did not, for the most part, stop them using Facebook, although in certain instances respondents employed tactics to minimise their privacy concerns. This thesis argues that, when using Facebook, respondents resolved the privacy paradox to the best of their ability. It is anticipated that the findings of this thesis will contribute to the ongoing dialogue surrounding the benefits and drawbacks of social media use.

Cette thèse est consacrée à une exploration des schémas de preuve de connaissance succincts, les SNARKs. S’inscrivant dans un contexte marqué par le développement du Cloud et des technologies Blockchain, les SNARKs sont des primitives cryptographiques permettant la vérification de l’intégrité des calculs. Dans un modèle de type client-serveur, où un client à faible puissance de calcul délègue une tache à un serveur à forte puissance de calcul, les SNARKs lui permettent de verifier efficacement si le serveur a bien exécuté la tache demandée. Notre attention se porte en particulier sur des sujets comme la sécurité post-quantique des SNARKs, la propriété d'extractabilité, qui fait du SNARK un outil si puissant dans des protocoles cryptographiques, la composition de ces preuves avec d'autres primitives cryptographiques et la construction d'un protocole cryptographique basé sur des preuves SNARKs qui garantit non seulement l'intégrité du résultat, mais aussi la confidentialité des données représentant l'entrée du calcul à vérifier
The contributions detailed in this thesis focus on the design and the analysis of Succinct non-interactive arguments of knowledge, known as SNARKs. SNARKs enable a party with large computational resources to prove to a weaker party that a particular statement is true in an efficient way without further interaction and under a minimal communication requirement. Our results deal with three different aspects of SNARK protocols: the postquantum security of SNARKs, the composability of SNARKs with other cryptographic primitives and the confidentiality of the inputs in the computations verified by SNARKs. First, we propose a new framework that allows the instantiation of a quantumresilient SNARK scheme from lattice assumptions. We also study the notion of extractability that is part of the soundness definition for SNARKs. We remark some limitations of this definition and we address this problem, by introducing and studying a new notion, O-SNARKs. Finally, to achieve data privacy in delegated computation, we study the possibility of constructing SNARKs that enables verification of computations over encrypted data

This chapter describes the role of international market mechanisms in reducing pollution and the costs of doing so. It looks into two mechanisms established by economists John H. Dales and Arthur Cecil Pigou. Dales propounded the mechanism of ‘pollution permit-trading’ which, instead of regulating pollution on a source-by-source or emitter class-by-emitter class basis, a regulatory agency from the beginning would limit the overall amount of pollution allowed. Firms could then trade amongst themselves, effectively using the market to determine which of them should be able to pollute, how much, and when. The other market mechanism is the Pigouvian tax, which is the tax levied per unit of pollution emitted. By pricing these external costs and forcing polluters to consider them in their private calculus, Pigouvian taxes force polluters to balance the social costs and their private economic benefits of polluting.

Chapter 3 examines the evolution of the fiscal system, with a view to setting up a backdrop for the analysis of its implications for privatization in subsequent chapters. What the chapter illustrates is that the post-Mao fiscal structure was path dependent in that it continued to bear some essential features of the old system while seeking to address some of its main problems through decentralization and with the incorporation of a contractual element in fiscal relations. These features and changes had profound impact on the economic strategies of local governments concerning public and private enterprises. Unintended consequences of earlier reforms led to a major fiscal restructuring in the mid-1990s. It redefined the self-interest calculus of local political actors, whose responses hastened the decline of public enterprises.

The introductory chapter outlines an established consensus that the United States’ shift from a policy of nuclear superiority over the Soviet Union to a policy that emphasized arms control, mutual assured destruction, and nuclear parity was the result of nuclear-strategic calculus. It then shows how declassified records of Nixon’s conversations with his advisors on the Strategic Arms Limitation Talks (SALT) disprove that thesis. It goes on to outline how Kennedy and Johnson administration officials also acted in ways that contradicted their private comments. Through brief summaries of the subsequent chapters, it then explicates the central argument of the book: that all three presidents were engaged in a double game to reconcile their personal doubts regarding the utility of nuclear weapons with the prevailing public and congressional mood during their administrations. It concludes by suggesting this dynamic is of enduring relevance to the formulation of American nuclear strategy.

The U.S. Supreme Court thought that protecting private property was necessary to protecting political autonomy. In Lochner v. New York, the Court expanded its concept of property rights to include liberty, not just from having one’s property physically taken, but also liberty from having one’s property regulated. The Court viewed its federalism and liberty of contract jurisprudence analogously as both areas protected individual liberty by limiting the power of government. During the 1930s, Court decisions invalidated key portions of President Franklin Roosevelt’s New Deal. Against the backdrop of the Great Depression, these decisions precipitated a constitutional crisis. United States v. Carolene Products was a blueprint for the way forward. Protecting economic liberty was reconceptualized as a multifaceted calculus that necessitated the careful balancing of competing interests in a highly complex, modern economic milieu. Beyond protecting against outright takings of property, the elected branches seemed better structured and staffed for this task.

AbstractThis paper shows that quasi-open bisimilarity is the coarsest bisimilarity congruence for the applied $$\pi $$ π -calculus. Furthermore, we show that this equivalence is suited to security and privacy problems expressed as an equivalence problem in the following senses: (1) being a bisimilarity is a safe choice since it does not miss attacks based on rich strategies; (2) being a congruence it enables a compositional approach to proving certain equivalence problems such as unlinkability; and (3) being the coarsest such bisimilarity congruence it can establish proofs of some privacy properties where finer equivalences fail to do so.

Digital healthcare information systems promise to improve care efficiency, to reduce complexity for patients, and to increase access to information and advance research efforts. A prominent example are multi-sided-platforms (MSP), which are essentially an information business, linking key healthcare stakeholders for individualized as well as aggregated information services. However, platform-based health innovation relies on the extensive collection, storage, and use of sensitive health information, raising issues of information privacy. This study uses the privacy calculus perspective to shed light on patients’ trade-off considerations. We use the case of a MSP, which connects patients, care providers and researchers, in order to model a multi-level calculus for health information of terminally ill patients. These insights inform stepwise consent options, which highlight the trade-offs between information value and patient privacy. By reflecting on the implications for patient empowerment this conceptual paper develops a research agenda on how to study and design responsible health information systems.