Children and overtourism : a cognitive neuroscience experiment to reflect on exposure and behavioural consequences

As tourism research has paid limited attention to children, this study investigates children’s reactions to tourism development, focusing on their unique viewpoints on the World Heritage Site of Dubrovnik, Croatia. It employed cognitive neuroscience methods with 397 participants, revealing that, despite their preference for sustainable tourism scenarios, children exhibit a notable fixation on images emblematic of overtourism and associated challenges, particularly overcrowding. When exposed to sustainable tourism photographs, there was an observable increase in physiological arousal, albeit not as pronounced as when confronted with an overtourism scenario. Intriguingly, regardless of the scenario, children predominantly expressed neutral emotions. Within the sustainable tourism context, gender differences manifest as girls exhibiting lower levels of place attachment. Furthermore, inner-city residents exhibit diminished levels of nature connectedness, and emotions are indirectly linked to nature connectedness, place attachment, or pro-environmental behaviour. Conversely, in the unsustainable scenario, older children and inner-city residents exhibited a heightened sense of neutrality towards overtourism-related concerns, whereas those outside the inner city displayed a stronger affinity for nature connectedness. Positive emotions were negatively associated with nature connectedness and pro-environmental behaviour but positively associated with place attachment. Accordingly, this study advocates a more inclusive and sustainable future through children’s empowerment in tourism development

Application development with GUI at a secondary vocational school

Katedra informačních technologií a technické výchovyFaculty of EducationPedagogická fakult

Conception de protocoles cryptographiques préservant la vie privée pour les services mobiles sans contact

The increasing number of worldwide mobile platforms and the emergence of new technologies such as the NFC (Near Field Communication) lead to a growing tendency to build a user's life depending on mobile phones. This context brings also new security and privacy challenges. In this thesis, we pay further attention to privacy issues in NFC services as well as the security of the mobile applications private data and credentials namely in Trusted Execution Environments (TEE). We first provide two solutions for public transport use case: an m-pass (transport subscription card) and a m-ticketing validation protocols. Our solutions ensure users' privacy while respecting functional requirements of transport operators. To this end, we propose new variants of group signatures and the first practical set-membership proof that do not require pairing computations at the prover's side. These novelties significantly reduce the execution time of such schemes when implemented in resource constrained environments. We implemented the m-pass and m-ticketing protocols in a standard SIM card: the validation phase occurs in less than 300ms whilst using strong security parameters. Our solutions also work even when the mobile is switched off or the battery is flat. When these applications are implemented in TEE, we introduce a new TEE migration protocol that ensures the privacy and integrity of the TEE credentials and user's private data. We construct our protocol based on a proxy re-encryption scheme and a new TEE model. Finally, we formally prove the security of our protocols using either game-based experiments in the random oracle model or automated model checker of security protocols.Avec l'émergence de nouvelles technologies telles que le NFC (Communication à champ proche) et l'accroissement du nombre de plates-formes mobiles, les téléphones mobiles vont devenir de plus en plus indispensables dans notre vie quotidienne. Ce contexte introduit de nouveaux défis en termes de sécurité et de respect de la vie privée. Dans cette thèse, nous nous focalisons sur les problématiques liées au respect de la vie privée dans les services NFC ainsi qu’à la protection des données privées et secrets des applications mobiles dans les environnements d'exécution de confiance (TEE). Nous fournissons deux solutions pour le transport public: une solution utilisant des cartes d'abonnement (m-pass) et une autre à base de tickets électroniques (m-ticketing). Nos solutions préservent la vie privée des utilisateurs tout en respectant les exigences fonctionnelles établies par les opérateurs de transport. À cette fin, nous proposons de nouvelles variantes de signatures de groupe ainsi que la première preuve pratique d’appartenance à un ensemble, à apport nul de connaissance, et qui ne nécessite pas de calculs de couplages du côté du prouveur. Ces améliorations permettent de réduire considérablement le temps d'exécution de ces schémas lorsqu’ils sont implémentés dans des environnements contraints par exemple sur carte à puce. Nous avons développé les protocoles de m-passe et de m-ticketing dans une carte SIM standard : la validation d'un ticket ou d'un m-pass s'effectue en moins de 300ms et ce tout en utilisant des tailles de clés adéquates. Nos solutions fonctionnent également lorsque le mobile est éteint ou lorsque sa batterie est déchargée. Si les applications s'exécutent dans un TEE, nous introduisons un nouveau protocole de migration de données privées, d'un TEE à un autre, qui assure la confidentialité et l'intégrité de ces données. Notre protocole est fondé sur l’utilisation d’un schéma de proxy de rechiffrement ainsi que sur un nouveau modèle d’architecture du TEE. Enfin, nous prouvons formellement la sécurité de nos protocoles soit dans le modèle calculatoire pour les protocoles de m-pass et de ticketing soit dans le modèle symbolique pour le protocole de migration de données entre TEE

Employee and Organization Security Value Alignment Through Value Sensitive Security Policy Design

Every member of the organization must be involved in proactively and consistently preventing data loss. Implementing a culture of security has proven to be a reliable method of enfranchising employees to embrace security behavior. However, it takes more than education and awareness of policies and directives to effect a culture of security. Research into organizational culture has shown that programs to promote organizational culture - and thus security behavior - are most successful when the organization\u27s values are congruent with employee values. What has not been clear is how to integrate the security values of the organization and its employees in a manner that promotes security culture. This study extended current research related to values and security culture by applying Value Sensitive Design (VSD) methodology to the design of an end user security policy. Through VSD, employee and organizational security values were defined and integrated into the policy. In so doing, the study introduced the concept of value sensitive security policy (VSP) and identified a method for using VSPs to promote a culture of security. At a time when corporate values are playing such a public role in defining the organization, improving security by increasing employee-organization value congruence is both appealing and practical

Advances in Sensors, Big Data and Machine Learning in Intelligent Animal Farming

Animal production (e.g., milk, meat, and eggs) provides valuable protein production for human beings and animals. However, animal production is facing several challenges worldwide such as environmental impacts and animal welfare/health concerns. In animal farming operations, accurate and efficient monitoring of animal information and behavior can help analyze the health and welfare status of animals and identify sick or abnormal individuals at an early stage to reduce economic losses and protect animal welfare. In recent years, there has been growing interest in animal welfare. At present, sensors, big data, machine learning, and artificial intelligence are used to improve management efficiency, reduce production costs, and enhance animal welfare. Although these technologies still have challenges and limitations, the application and exploration of these technologies in animal farms will greatly promote the intelligent management of farms. Therefore, this Special Issue will collect original papers with novel contributions based on technologies such as sensors, big data, machine learning, and artificial intelligence to study animal behavior monitoring and recognition, environmental monitoring, health evaluation, etc., to promote intelligent and accurate animal farm management