Bibliografie tematiche / Privicy protection

Letteratura scientifica selezionata sul tema "Privicy protection"

Autore: Grafiati

Pubblicato: 6 luglio 2024

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Articoli di riviste sul tema "Privicy protection":

Xie, Guangxu, Gaopan Hou, Qingqi Pei e Haibo Huang. "Lightweight Privacy Protection via Adversarial Sample". Electronics 13, n. 7 (26 marzo 2024): 1230. http://dx.doi.org/10.3390/electronics13071230.

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Adversarial sample-based privacy protection has its own advantages compared to traditional privacy protections. Previous adversarial sample privacy protections have mostly been centralized or have not considered the issue of hardware device limitations when conducting privacy protection, especially on the user’s local device. This work attempts to reduce the requirements of adversarial sample privacy protections on devices, making the privacy protection more locally friendly. Adversarial sample-based privacy protections rely on deep learning models, which generally have a large number of parameters, posing challenges for deployment. Fortunately, the model structural pruning technique has been proposed, which can be employed to reduce the parameter count of deep learning models. Based on the model pruning technique Depgraph and existing adversarial sample privacy protections AttriGuard and MemGuard, we design two structural pruning-based adversarial sample privacy protections, in which the user obtains the perturbed data through the pruned deep learning model. Extensive experiments are conducted on four datasets, and the results demonstrate the effectiveness of our adversarial sample privacy protection based on structural pruning.

Bonomi, Luca, Xiaoqian Jiang e Lucila Ohno-Machado. "Protecting patient privacy in survival analyses". Journal of the American Medical Informatics Association 27, n. 3 (21 novembre 2019): 366–75. http://dx.doi.org/10.1093/jamia/ocz195.

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Abstract Objective Survival analysis is the cornerstone of many healthcare applications in which the “survival” probability (eg, time free from a certain disease, time to death) of a group of patients is computed to guide clinical decisions. It is widely used in biomedical research and healthcare applications. However, frequent sharing of exact survival curves may reveal information about the individual patients, as an adversary may infer the presence of a person of interest as a participant of a study or of a particular group. Therefore, it is imperative to develop methods to protect patient privacy in survival analysis. Materials and Methods We develop a framework based on the formal model of differential privacy, which provides provable privacy protection against a knowledgeable adversary. We show the performance of privacy-protecting solutions for the widely used Kaplan-Meier nonparametric survival model. Results We empirically evaluated the usefulness of our privacy-protecting framework and the reduced privacy risk for a popular epidemiology dataset and a synthetic dataset. Results show that our methods significantly reduce the privacy risk when compared with their nonprivate counterparts, while retaining the utility of the survival curves. Discussion The proposed framework demonstrates the feasibility of conducting privacy-protecting survival analyses. We discuss future research directions to further enhance the usefulness of our proposed solutions in biomedical research applications. Conclusion The results suggest that our proposed privacy-protection methods provide strong privacy protections while preserving the usefulness of survival analyses.

Zhenjiang Zhang, Zhenjiang Zhang, e Xiaohua Liu Zhenjiang Zhang. "Cloud-side Collaborative Privacy Protection Based on Differential Privacy". 電腦學刊 32, n. 4 (agosto 2021): 239–51. http://dx.doi.org/10.53106/199115992021083204019.

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Meier, Yannic, Johanna Schäwel e Nicole C. Krämer. "Between protection and disclosure: applying the privacy calculus to investigate the intended use of privacy-protecting tools and self-disclosure on different websites". Studies in Communication and Media 10, n. 3 (2021): 283–306. http://dx.doi.org/10.5771/2192-4007-2021-3-283.

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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.

Nussy, Jennifer Ingelyne. "Mekanisme Komisi Pemberantasan Korupsi dalam Proses Penyadapan dilihat dari Perspektif Hak Asasi Manusia (HAM)". JURNAL BELO 5, n. 2 (19 maggio 2020): 74–85. http://dx.doi.org/10.30598/belobelovol5issue2page74-85.

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ABSTRACT Recognition and protection of a guarantee of human dignity to earn a respectable place in the eyes of the law and government. Related to the interests of law enforcement, the Corruption Eradication Commission (KPK) for the purpose of wiretapping evidence in court, while will protecting the privacyrights of suspects. Legal protections for the accused to be seen as matter of law adopted. Therefore, the protection of the privacy rights of a person to be seen in the investigation process. For the Commission to conduct wiretaps should see privacy rights as stipulated in the law and the government should establish a special set of rules that intercepts, thus providing the possibility for law enforcement has the authority to do so does not conflict with human rights.

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Corones, Stephen, e Juliet Davis. "Protecting Consumer Privacy and Data Security: Regulatory Challenges and Potential Future Directions". Federal Law Review 45, n. 1 (marzo 2017): 65–95. http://dx.doi.org/10.1177/0067205x1704500104.

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This article considers the regulatory problems of online tracking behaviour, lack of consent to data collection, and the security of data collected with or without consent. Since the mid-1990s the United States Federal Trade Commission has been using its power under the United States consumer protection regime to regulate these problems. The Australian Competition and Consumer Commission (ACCC), on the other hand, has yet to bring civil or criminal proceedings for online privacy or data security breaches, which indicates a reluctance to employ the Australian Consumer Law (‘ACL’) in this field.1 Recent legislative action instead points to a greater application of the specifically targeted laws under the Privacy Act 1988 (Cth) (‘Privacy Act’), and the powers of the Office of the Australian Information Commissioner (OAIC), to protect consumer privacy and data security. This article contends that while specific legislation setting out, and publicly enforcing, businesses’ legal obligations with respect to online privacy and data protection is an appropriate regulatory response, the ACL's broad, general protections and public and/or private enforcement mechanisms also have a role to play in protecting consumer privacy and data security.

Singla, Arun. "The Evolving Landscape of Privacy Law: Balancing Digital Innovation and Individual Rights". Indian Journal of Law 2, n. 1 (2024): 1–6. http://dx.doi.org/10.36676/ijl.v2.i1.01.

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The rapid pace of digital innovation presents significant challenges to existing privacy laws, necessitating a delicate balance between technological advancement and the protection of individual rights. This paper explores the evolving landscape of privacy law, highlighting the tension between fostering digital innovation and ensuring robust privacy protections. Through a historical overview, the paper traces the development of privacy laws from their inception to the current global regulatory framework, including key legislations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). It delves into the challenges posed by emerging technologies, such as artificial intelligence, the Internet of Things (IoT), and big data, and examines case studies that illustrate these challenges. The analysis reveals a dynamic interplay between innovation and privacy, where stringent regulations may impede technological progress, while lax privacy protections may undermine individual rights. The paper proposes legal reforms and innovative approaches to privacy protection, advocating for a flexible legal framework that can adapt to technological advancements while safeguarding privacy. The conclusion underscores the importance of ethical considerations in shaping future privacy laws and the need for a balanced approach that supports both digital innovation and the protection of individual rights.

Chen, Zhixuan, Yixiang Zhang e Zhiyu Zhang. "Research on Privacy Protection Willingness of New Media Platform Users Based on Theory of Planned Behavior". Communications in Humanities Research 16, n. 1 (28 novembre 2023): 264–71. http://dx.doi.org/10.54254/2753-7064/16/20230726.

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In todays digital age, new media platforms have become an important channel for people to obtain information and entertainment. However, what followed was peoples growing concerns about personal privacy security. This study takes all adults who use new media platforms as the research object, explores various factors that affect the willingness to protect privacy, and provides in-depth and practical suggestions for protecting personal privacy. We used the theory of planned behavior, incorporating factors such as age and privacy concerns. Through questionnaire survey, a large amount of data was collected and analyzed using SPSS26. The results showed that although age was not significantly correlated with privacy protection willingness, attitude, subjective norms, perceived behavioral control, and privacy concerns were significantly positively correlated with privacy protection willingness. From the research results and discussion, it can be seen that individual attitudes towards privacy protection and social pressure are important factors that determine the willingness to protect privacy. At the same time, individuals perceived behavioral control and privacy concerns will also affect their privacy protection behavior. To sum up, this study deeply analyzes the privacy protection willingness of adults on new media platforms, and provides guidance and suggestions for privacy protection behaviors in the digital society. This has certain significance for protecting personal privacy and promoting the sustainable development of the digital society.

Nahra, Kirk J. "Remarks by Kirk J. Nahra". Proceedings of the ASIL Annual Meeting 116 (2022): 127–29. http://dx.doi.org/10.1017/amp.2023.65.

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U.S. privacy law often is criticized in comparison with international privacy regimes, particularly the European Union's General Data Protection Regulation. Parts of this criticism are fair, but, at the same time, U.S. privacy law provides meaningful protections in a substantial set of circumstances, and, on occasion, provides either “better” privacy protection than the GDPR or presents a more targeted approach to balancing appropriate privacy protections with other important public policy concerns. This balancing often is not a question of “consumers vs. industry” (although it certainly can be). In some situations—particularly in the health care settings that I will focus on—it often is a question of providing an appropriate balance between privacy interests and other policy interests that benefit both industry and consumers.

Più fonti

Tesi sul tema "Privicy protection":

Maifada, Magoudani Mahamadou. "Construire et mettre en œuvre un droit des données personnelles dans l’espace UEMOA : étude comparée à partir des cas du Burkina Faso, de la Côte d’Ivoire, du Niger et du Sénégal à la lumière du droit français et européen". Electronic Thesis or Diss., Paris 12, 2023. http://www.theses.fr/2023PA120073.

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La présente thèse propose une analyse approfondie du cadre juridique entourant la protection des données personnelles au sein de l'Union Économique et Monétaire Ouest-Africaine (UEMOA), particulièrement le Burkina Faso, la Côte d’Ivoire, le Niger et le Sénégal – l’espace étudié. Elle s'attarde sur les motivations ayant conduit ces États à adopter des législations spécifiques influencées par des modèles étrangers, notamment le modèle français de la Loi Informatique et Libertés, plutôt que de se baser sur des références nationales ou communautaires.Cette analyse explore le processus de création de ces réglementations, du développement législatif aux initiatives des institutions internationales. Un intérêt particulier est accordé à l'influence de l'Organisation Internationale de la Francophonie (OIF) ainsi que la Commission de l’Informatique et des Libertés française dans la promotion des premières législations nationales au sein de cet espace.La thèse procède également à une comparaison détaillée entre les réglementations en vigueur au sein de l'UEMOA et le Règlement Général sur la Protection des Données (RGPD) de l'Union européenne. Cette comparaison met en lumière les similitudes et les distinctions significatives, notamment en ce qui concerne la portée d'application, la responsabilité des acteurs, et les droits des individus concernés.En outre, l'étude examine la mise en œuvre pratique de ces réglementations, en se penchant sur le rôle des acteurs clés notamment les autorités de contrôle, les responsables de traitement, des Organisations de la Société Civile (OSC) ainsi que les personnes protégées de chaque État. Elle analyse les défis auxquels sont confrontées les autorités de contrôle et les politiques de coopération visant à renforcer l'effectivité du droit des données personnelles.Enfin, la thèse explore les limites de ce droit des données personnelles, notamment son interaction avec les politiques publiques dans le domaine des télécommunications et les enjeux liés à la cybercriminalité.Dans l'ensemble, ce travail offre une vision complète et nuancée du droit des données personnelles au sein de l'UEMOA, mettant en lumière les motivations, les réalisations, les obstacles et les perspectives dans un contexte juridique africain en constante évolution. Il constitue une contribution significative à la compréhension de la protection des données personnelles dans le contexte africain sur le plan juridique
This thesis provides an in-depth analysis of the legal framework surrounding the protection of personal data within the West African Economic and Monetary Union (WAEMU), specifically focusing on Burkina Faso, Côte d'Ivoire, Niger, and Senegal – the areas under study. It delves into the motivations that led these states to adopt specific legislations influenced by foreign models, notably the French model of the "Loi Informatique et Libertés," rather than relying on national or community references.This analysis explores the development process of these regulations, from legislative evolution to international institutions' initiatives. Special attention is given to the influence of the International Organization of La Francophonie (IOF) and the French Commission for Data Protection (Commission de l'Informatique et des Libertés) in promoting the initial national legislations within this region.Furthermore, the thesis conducts a detailed comparison between the existing regulations within WAEMU and the European Union's General Data Protection Regulation (GDPR). This comparison highlights significant similarities and differences, particularly concerning the scope of application, stakeholders' responsibilities, and the rights of the individuals concerned.Moreover, the study examines the practical implementation of these regulations, focusing on key actors, including regulatory authorities, data controllers, Civil Society Organizations (CSOs), and data subjects in each state. It analyzes the challenges faced by regulatory authorities and cooperation policies aimed at enhancing the effectiveness of personal data rights.Finally, the thesis explores the limitations of personal data rights, particularly in their interaction with public policies in the telecommunications sector and the issues related to cybercrime.Overall, this work offers a comprehensive and nuanced perspective on personal data rights within WAEMU, shedding light on the motivations, achievements, challenges, and prospects in the ever-evolving African legal context. It constitutes a significant contribution to the understanding of personal data protection in the African legal context

Sallaku, Redlon <1994&gt. "Privacy and Protecting Privacy: Using Static Analysis for legal compliance. General Data Protection Regulation". Master's Degree Thesis, Università Ca' Foscari Venezia, 2019. http://hdl.handle.net/10579/14682.

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The main purpose of the thesis is to study Privacy and how protecting Privacy, including the new regulation framework proposed by EU the GDPR, investigating how static analysis could help GDPR enforcement, and develop a new static analysis prototype to fulfill this task in practice. GDPR (General Data Protection Regulation) is a recent European regulation to harmonize and enforce data privacy laws across Europe, to protect and empower all EU citizens data privacy, and to reshape the way organizations deal with sensitive data. This regulation has been enforced starting from May 2018. While it is already clear that there is no unique solution to deal with the whole spectrum of GDPR, it is still unclear how static analysis might help enterprises to fulfill the constraints imposed by this regulation.

Li, Min. "Privacy Protection on Cloud Computing". VCU Scholars Compass, 2015. http://scholarscompass.vcu.edu/etd/3844.

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Cloud is becoming the most popular computing infrastructure because it can attract more and more traditional companies due to flexibility and cost-effectiveness. However, privacy concern is the major issue that prevents users from deploying on public clouds. My research focuses on protecting user's privacy in cloud computing. I will present a hardware-based and a migration-based approach to protect user's privacy. The root cause of the privacy problem is current cloud privilege design gives too much power to cloud providers. Once the control virtual machine (installed by cloud providers) is compromised, external adversaries will breach users’ privacy. Malicious cloud administrators are also possible to disclose user’s privacy by abusing the privilege of cloud providers. Thus, I develop two cloud architectures – MyCloud and MyCloud SEP to protect user’s privacy based on hardware virtualization technology. I eliminate the privilege of cloud providers by moving the control virtual machine (control VM) to the processor’s non-root mode and only keep the privacy protection and performance crucial components in the Trust Computing Base (TCB). In addition, the new cloud platform can provide rich functionalities on resource management and allocation without greatly increasing the TCB size. Besides the attacks to control VM, many external adversaries will compromise one guest VM or directly install a malicious guest VM, then target other legitimate guest VMs based on the connections. Thus, collocating with vulnerable virtual machines, or ”bad neighbors” on the same physical server introduces additional security risks. I develop a migration-based scenario that quantifies the security risk of each VM and generates virtual machine placement to minimize the security risks considering the connections among virtual machines. According to the experiment, our approach can improve the survivability of most VMs.

Xu, Wanxin. "AFFECT-PRESERVING VISUAL PRIVACY PROTECTION". UKnowledge, 2018. https://uknowledge.uky.edu/ece_etds/122.

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The prevalence of wireless networks and the convenience of mobile cameras enable many new video applications other than security and entertainment. From behavioral diagnosis to wellness monitoring, cameras are increasing used for observations in various educational and medical settings. Videos collected for such applications are considered protected health information under privacy laws in many countries. Visual privacy protection techniques, such as blurring or object removal, can be used to mitigate privacy concern, but they also obliterate important visual cues of affect and social behaviors that are crucial for the target applications. In this dissertation, we propose to balance the privacy protection and the utility of the data by preserving the privacy-insensitive information, such as pose and expression, which is useful in many applications involving visual understanding. The Intellectual Merits of the dissertation include a novel framework for visual privacy protection by manipulating facial image and body shape of individuals, which: (1) is able to conceal the identity of individuals; (2) provide a way to preserve the utility of the data, such as expression and pose information; (3) balance the utility of the data and capacity of the privacy protection. The Broader Impacts of the dissertation focus on the significance of privacy protection on visual data, and the inadequacy of current privacy enhancing technologies in preserving affect and behavioral attributes of the visual content, which are highly useful for behavior observation in educational and medical settings. This work in this dissertation represents one of the first attempts in achieving both goals simultaneously.

Winkler, Stephanie D. "Protecting Online Privacy". UKnowledge, 2016. http://uknowledge.uky.edu/comm_etds/47.

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Online privacy has become one of the greatest concerns in the United States today. There are currently multiple stakeholders with interests in online privacy including the public, industry, and the United States government. This study examines the issues surrounding the protection of online privacy. Privacy laws in the United States are currently outdated and do little to protect online privacy. These laws are unlikely to be changed as both the government and industry have interests in keeping these privacy laws lax. To bridge the gap between the desired level of online privacy and what is provided legally users may turn to technological solutions.

Gunnarsson, Annicka, e Siri Ekberg. "Invasion of Privacy : Spam - one result of bad privacy protection". Thesis, Blekinge Tekniska Högskola, Institutionen för programvaruteknik och datavetenskap, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5393.

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Our personal privacy is being eroded from various directions as modern technologies bring lots of new threats towards our personal privacy. Unfortunately, people are often oblivious about it and accept invasion of privacy to a great extent without questions. This thesis is a presentation of our study dealing with privacy violations while using the Internet. It also includes a further investigation about unsolicited bulk email, which is one of many consequences of bad privacy protection. We have also examined the differences between the United States and the European Union and found that the fundamental privacy protection is better in the European Union. We have used different methods to complete this thesis such as studies of literature and articles as well as performing a spam study. Using these methods we have concluded that privacy violations on the Internet is a significant problem and that the Internet users have a right to an adequate privacy protection.

Matusek, F. (Florian). "Selective privacy protection for video surveillance". Doctoral thesis, Oulun yliopisto, 2014. http://urn.fi/urn:isbn:9789526204154.

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Abstract An unparalleled surge in video surveillance has occurred in recent years, due to some tragic events such as terror attacks, bank robberies and the activities of organized crime. Video surveillance technology has advanced significantly, which has even enabled the automatic tracking of individuals. However, in the opinion of the public the increase in security has brought about a decrease in personal privacy. Through video surveillance citizens could be monitored more easily than ever before, thus considerably intruding into their personal privacy. It was assumed that security and privacy in video surveillance was a zero-sum game in which citizens were forced to choose one over the other. This study was based on the belief that this notion is false. It was assumed that it can be possible to keep personal privacy while guaranteeing the utmost security. A solution to this issue was sought using Hevner’s design science research guidelines and design science research cycles. A video surveillance system was designed and constructed that would protect the personal privacy of uninvolved individuals under surveillance while still providing a high level of security, namely the Privacy Enhancing Video Surveillance system PEVS. PEVS protected the privacy of individuals by automatically scrambling the image regions where people were present in video streams. If a criminal act should take place, it was possible, with the proper authorization, to selectively unscramble the data of individuals of interest to analyze the situation. This enabled to analyze the situation without intruding into the privacy of uninvolved people on the one hand, while on the other hand using the data as evidence of possible criminal activity. Hence, the privacy of individuals was protected while maintaining the same level of security. PEVS provided the first technology-based video surveillance solution, which showed only relevant individuals in the image while leaving the identity of everyone else unrevealed. Therefore, the main contribution of this thesis was the construction of a novel approach to video surveillance systems, capable of selectively protecting the privacy of individuals. This included introducing an architecture for a privacy preserving video surveillance system, which consisted of several sub-constructs. These included storage techniques for privacy data and shadow detection and segmentation methods, which increased the accuracy and speed of previous methods. Further, novel security and privacy metrics for video surveillance were introduced. The overall system was a significant improvement over the existing knowledge base that has thus far seen only first steps to selective privacy protection but has failed to provide a complete system
Tiivistelmä Videovalvonnassa on tapahtunut viime vuosina merkittävää kasvua johtuen järkyttävistä tapahtumista kuten terrori-iskut, pankkiryöstöt ja järjestäytyneen rikollisuuden toimet. Videovalvontateknologia on kehittynyt merkittävästi mahdollistaen jopa yksittäisten ihmisten automaattisen seurannan. Turvallisuuden lisääntymisen katsotaan kuitenkin vähentäneen yksityisyyttä. Videovalvonnan avulla ihmisiä pystytään seuraamaan helpommin kuin koskaan aikaisemmin tunkeutuen täten heidän yksityisyytensä alueelle. On oletettu, että turvallisuus ja yksityisyys videovalvonnassa on nollasummapeliä, jossa kansalaisten on valittava yksityisyyden ja turvallisuuden välillä. Tämä tutkimus perustuu olettamukseen, että edellä esitetty ei pidä paikkaansa, vaan että on mahdollista suojata yksityisyys samalla taaten täysi turvallisuus. Ratkaisua tähän ongelmaan etsittiin suunnittelutieteellisen tutkimuksen avulla. Työssä suunniteltiin ja toteutettiin videovalvontajärjestelmä PEVS (Privacy Enhancing Video Surveillance system), joka suojaa valvonnanalaisten sivullisten yksityisyyttä ja siitä huolimatta tuottaa korkean turvallisuustason.. PEVS suojaa henkilöiden yksityisyyttä salaamalla automaattisesti videoaineistosta ne kuva-alat, joissa esiintyy ihmisiä. Mikäli laitonta toimintaa havaittaisiin, olisi riittävillä käyttöoikeuksilla mahdollista purkaa salaus mielenkiinnon kohteena olevien henkilöiden kohdalta tilanteen analysoimiseksi. Tämä mahdollisti yhtäältä puuttumattomuuden sivullisten yksityisyyteen ja toisaalta tiedon käyttämisen todistusaineistona mahdollisen rikoksen tutkimisessa. Tällä järjestelmällä yksityisyys oli mahdollista suojata samanaikaisesti, kun turvallisuudesta huolehdittiin. PEVS mahdollisti ensimmäistä kertaa maailmassa videovalvonnan, joka näyttää vain relevantit henkilöt jättäen muiden henkilöllisyyden paljastamatta. Sen takia tämän tutkimuksen merkittävin kontribuutio oli uudenlaisen lähestymistavan kehittäminen videovalvontaan, joka kykenee valikoivasti suojelemaan ihmisten yksityisyyttä. Tämä ratkaisu sisältää yksityisyyden suojaavan, useita rakenneosia sisältävän videovalvontajärjestelmäarkkitehtuurin esittelyn. Rakenneosiin kuuluu yksityisen tiedon tallennusmenetelmiä ja varjontunnistus- ja segmentointimetodeja, jotka paransivat aiemmin käytettyjen metodien tarkkuutta ja nopeutta. Lisäksi esiteltiin uudenlainen turvallisuus- ja yksityisyysmetriikka videovalvonnalle. Toteutettu järjestelmä on huomattava lisäys nykytietämykseen, jossa yksityisyyden suojan osalta on otettu vasta ensiaskelia ja joka ei mahdollista kattavaa järjestelmää

Chaudhari, Jayashri S. "Privacy Protection for Life-log System". UKnowledge, 2007. http://uknowledge.uky.edu/gradschool_theses/491.

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Tremendous advances in wearable computing and storage technologies enable us to record not just snapshots of an event but the whole human experience for a long period of time. Such a \life-logandamp;quot; system captures important events as they happen, rather than an after-thought. Such a system has applications in many areas such as law enforcement, personal archives, police questioning, and medicine. Much of the existing eandamp;reg;orts focus on the pattern recognition and information retrieval aspects of the system. On the other hand, the privacy issues raised by such an intrusive system have not received much attention from the research community. The objectives of this research project are two-fold: andamp;macr;rst, to construct a wearable life-log video system, and second, to provide a solution for protecting the identity of the subjects in the video while keeping the video useful. In this thesis work, we designed a portable wearable life-log system that implements audio distortion and face blocking in a real time to protect the privacy of the subjects who are being recorded in life-log video. For audio, our system automatically isolates the subject's speech and distorts it using a pitch- shifting algorithm to conceal the identity. For video, our system uses a real-time face detection, tracking and blocking algorithm to obfuscate the faces of the subjects. Extensive experiments have been conducted on interview videos to demonstrate the ability of our system in protecting the identity of the subject while maintaining the usability of the life-log video.

Ajam, Nabil. "Privacy protection for location-based services". Télécom Bretagne, 2010. http://www.theses.fr/2010TELB0124.

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Dans cette thèse, nous nous intéressons à l'expression des principes de protection de la vie privée. Nous spécifions ces exigences de vie privée en proposant de les introduire dans les modèles des politiques de sécurité existants. Ainsi, nous suggérons l'application d'un seul modèle pour le contrôle d'accès et la protection de la vie privée. Le modèle de contrôle d'accès doit être étendu par de nouvelles conditions d'accès et de paramètres, à savoir les contextes, constituant les exigences de la vie privée. Pour cela, nous définissons le modèle Privacy-aware Organisation-Based Access Control (PrivOrBAC). L'administration de PrivOrBAC est manifestement différente des modèles d'administration des modèles contrôles d'accès. Nous identifions trois cas à introduire dans le modèle d'administration. Premièrement, à cause de l'attractivité des nouveaux services, les utilisateurs définissent généralement une politique de vie privée trop permissive qui ne correspond pas réellement à leurs préférences. Nous proposons que le contrôleur des données puisse prendre en charge la définition de la politique en se basant sur le contrat de service (SLA) incluant les préférences utilisateurs. Deuxièmement, le modèle d'administration doit prendre en compte la modélisation des interceptions légales. Cet accès est prioritaire vis à vis des préférences utilisateurs. Troisièmement, nous présentons le cas où les deux organisations, le contrôleur de données et les fournisseurs de services, doivent partager l'accès à la même ressource. Grâce au modèle d'interopérabilité O2O, les préférences utilisateurs peuvent être propagées et ainsi respectées par les organisations tierces demandant l'accès. Nous nous sommes focalisés sur les données de localisation qui représentent les données privées à protéger dans notre étude. Nous proposons une architecture prête à être déployer dans les systèmes d'information des services de localisation (LBS). Nous utilisons MotOrBAC, le prototype du modèle OrBAC, pour adapter notre solution au cadre des réseaux cellulaires. Nous avons aussi étendu la passerelle Parlay X par une nouvelle Privacy web service pour permettre un accès sécurisé et respectant la vie privée des fournisseurs de services aux données enregistrées dans les réseaux cellulaires
In this dissertation, we propose the expression and the modelling of the most important principles of privacy. We deduce the relevant privacy requirements that should be integrated in existing security policy models, such as RBAC models. We suggest the application of a unique model for both access control and privacy requirements. Thus, an access control model is to be enriched with new access constraints and parameters, namely the privacy contexts, which should implement the consent and the notification concepts. For this purpose, we introduce the privacy-aware Organisation role Based Access Control (OrBAC) model. The administration of this new model is significantly different from previous models. Three cases are identified. First, the privacy policy may be defined by the data collector but data owners have the possibility to set their preferences through a contracted Service Level Agreement (SLA). Second, the administration model allows legal organisations, for legal purposes, to impose their needs by bypassing user's preferences. Third, we present the case of a privacy policy which is negotiated between the data collector and the requestor based on user's preferences, defined in the SLA. Overall, our proposal is a distributed administration of privacy policies. Focusing on Location Based Services (LBSs), we finally propose a complete privacy framework ready to be deployed in information systems. We use the model prototype to adapt our solution to cellular networks when the requesters are the service providers. This prototype uses parlay gateways with web services. We also extend the set of Parlay X gateway standardised web services by proposing a dedicated privacy web service to enforce privacy protection

Du, Jing. "Privacy protection in location-based applications". HKBU Institutional Repository, 2007. http://repository.hkbu.edu.hk/etd_ra/816.

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Libri sul tema "Privicy protection":

Blume, Peter. Protection of informational privacy. Copenhagen: DJØF Pub., 2002.

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South African Law Reform Commission. Privacy and data protection. [Pretoria: South African Law Reform Commission], 2003.

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South African Law Reform Commission. Privacy and data protection. Pretoria: South African Law Reform Commission, 2005.

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Saad, Abdul Raman. Personal data & privacy protection. Kelana Jaya, Selangor, Malaysia: Malayan Law Journal Sdn. Bhd., 2005.

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Smiley, Sophie. Protecting our privacy. Cambridge: Independence, 2004.

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Rodrigues, Rowena, e Vagelis Papakonstantinou, a cura di. Privacy and Data Protection Seals. The Hague: T.M.C. Asser Press, 2018. http://dx.doi.org/10.1007/978-94-6265-228-6.

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Caloyannides, Michael A. Privacy protection and computer forensics. 2^a ed. Boston: Artech House, 2004.

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Kuschewsky, Monika. Data protection & privacy: Jurisdictional comparisons. London: Thomson Reuters, 2014.

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George, Yee, a cura di. Privacy protection for e-services. Hershey PA: Idea Group Pub., 2006.

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Bainbridge, David I. Data protection. Welwvyn Garden City: CLT Professional Pub., 2000.

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Capitoli di libri sul tema "Privicy protection":

Weik, Martin H. "privacy protection". In Computer Science and Communications Dictionary, 1334. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_14678.

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Hallinan, Dara, e Paul de Hert. "Genetic Classes and Genetic Categories: Protecting Genetic Groups Through Data Protection Law". In Group Privacy, 175–96. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46608-8_10.

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Chaudhuri, Arijit, e Tasos C. Christofides. "Protection of Privacy". In Indirect Questioning in Sample Surveys, 151–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36276-7_7.

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Gulzar, Nikki, Basra Abbasi, Eddie Wu, Anil Ozbal e WeiQi Yan. "Surveillance Privacy Protection". In Intelligent Multimedia Surveillance, 83–105. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41512-8_5.

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Hung, Patrick C. K., Marcelo Fantinato e Jorge Roa. "Children Privacy Protection". In Encyclopedia of Computer Graphics and Games, 1–3. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-08234-9_198-1.

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Hung, Patrick C. K., Marcelo Fantinato e Jorge Roa. "Children Privacy Protection". In Encyclopedia of Computer Graphics and Games, 293–95. Cham: Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-23161-2_198.

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Poikela, Maija Elina. "Privacy Protection Behaviour". In T-Labs Series in Telecommunication Services, 109–29. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34171-8_7.

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Chaudhuri, Arijit, Sanghamitra Pal e Dipika Patra. "Protection of Privacy". In Randomized Response Techniques, 119–38. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-9669-8_7.

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Tang, Alan. "Workforce Data Protection". In Privacy in Practice, 329–61. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003225089-29.

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Stahl, Bernd Carsten, Doris Schroeder e Rowena Rodrigues. "Privacy". In Ethics of Artificial Intelligence, 25–37. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17040-9_3.

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AbstractPrivacy and data protection are concerns raised about most digital technologies. The advance of artificial intelligence (AI) has given even higher levels of prominence to these concerns. Three cases are presented as examples to highlight the way in which AI can affect or exacerbate privacy concerns. The first deals with the use of private data in authoritarian regimes. The second looks at the implications of AI use of genetic data. The third concerns problems linked to biometric surveillance. Then follows a description of how privacy concerns are currently addressed via data protection regulation and a discussion of where AI may raise new challenges to existing data protection regimes. Current European data protection law requires data protection impact assessment. This chapter suggests that a broader AI impact assessment could broaden the remit of such an assessment to offer more comprehensive coverage of possible privacy concerns linked to AI.

Atti di convegni sul tema "Privicy protection":

Rezer, Tatiana. "Privacy Right as A Personal Value in an Information Society". In The Public/Private in Modern Civilization, the 22nd Russian Scientific-Practical Conference (with international participation) (Yekaterinburg, April 16-17, 2020). Liberal Arts University – University for Humanities, Yekaterinburg, 2020. http://dx.doi.org/10.35853/ufh-public/private-2020-76.

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The relevance of the topic is that the continuous and rapid increase in the role and volume of information in human life leads to the need to develop ways of protecting private information as a subject of personal property and personal value. Privacy is a natural human right and is enshrined in the European Convention on the Protection of Human Rights and Basic Freedoms, as well as in the Constitution of the Russian Federation. The regulation of the right to privacy is enshrined in the Russian Civil and Criminal Codes, which provide for legal liability for violations of this right. However, with regulations in place, the human element remains and often leads to leaks of private information, which destroys the personal value of the right. The article examines the concept of the right to privacy, its importance in the information society and human life, and the ways in which it can be protected. The aim of the study is to identify ways of protecting and complementing the right to privacy in the information society. The comparative legal analysis method allowed us to identify the mechanisms for the legal protection of the right to privacy. The case-analysis method enabled us to analyse Yandex’s data breach situation, while the content analysis method allowed us to make recommendations for protecting personal data. Main conclusions: the right to privacy as a personal value in the information society has not been sufficiently addressed in the scientific literature; self-protection as well as raising human legal awareness of information technology can be used as mechanisms to protect privacy.

Ye, Mengmei, Zhongze Tang, Huy Phan, Yi Xie, Bo Yuan e Sheng Wei. "Visual privacy protection in mobile image recognition using protective perturbation". In MMSys '22: 13th ACM Multimedia Systems Conference. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3524273.3528189.

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Srinivasan, S. "Privacy Protection and Data Breaches". In InSITE 2015: Informing Science + IT Education Conferences: USA. Informing Science Institute, 2015. http://dx.doi.org/10.28945/2261.

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Data breach is the act of accessing a central data repository without the consent of the data owner. Data breaches are occurring frequently and involve millions of records. Major breaches have been reported since 2005. Often data breaches occur due to someone with malicious intent accessing the stored data. In this paper we look at the types of data breaches and how they impact people’s privacy, we introduce a data protection model with the goal of protecting people’s privacy. Given today’s mobile information needs it is essential to have access to personal data. Social networks are making it difficult to keep personal information private. We provide several different summaries to show the effect of data breaches and data losses on people. We conclude this paper with a set of recommendations to protect people’s privacy.

"Place Determinants for the Personalization-Privacy Tradeoff among Students". In InSITE 2018: Informing Science + IT Education Conferences: La Verne California. Informing Science Institute, 2018. http://dx.doi.org/10.28945/4069.

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Aim/Purpose: [This Proceedings paper was revised and published in the 2018 issue of the journal Issues in Informing Science and Information Technology, Volume 15] In this exploratory study we investigate the influential factors of users' decisions in the dilemma whether to agree to online personalization or to protect their online privacy. Background: Various factors related to online privacy and anonymity were considered, such as user's privacy concern on the Web in general and particularly on social networks, user online privacy literacy and field of study. Methodology: To this end, 155 students from different fields of study in the Israeli academia were administered closed-ended questionnaires. Contribution: The main conceptual contribution of this study was the creation of a new direct scale for assessing user decisions regarding the personalization-privacy tradeoff. Another contribution was the investigation of the predictive factors of the personalization-privacy tradeoff. While previous studies found that users seldom allow their privacy concerns to affect their online behavior, our results revealed the opposite, as the participants with a higher level of concern for online privacy tended to prefer privacy protection, at the expense online personalization. Findings: The multivariate linear regression analysis showed that as the participants' privacy concern increases, they tend to prefer privacy protection over online personalization. In addition, we found significant differences between men and women, as men tended to favor privacy protection more than women did. Recommendations for Practitioners: The new direct scale that was developed may be used by other practitioners to measure other issues relating to the privacy paradox behavior. Recommendation for Researchers: The questionnaire may be used by other researchers to examine online information behavior. Impact on Society: This research has social implications for the academia and general public as they show that by raising the concern for the protection of personal information on the Web, it is possible to influence the personalization-privacy tradeoff and encourage users to prefer privacy protection. Furthermore, the enhancement of users' preference for privacy protection over Web-surfing convenience may be used as a mean to mitigate the online privacy paradox behavior. Future Research: Since our results were based on students' self-perceptions, which might be biased, future work should apply qualitative analysis to explore additional types and influencing factors of online privacy behavior.

Chhetri, Chola, e Vivian Genaro Motti. "Privacy Concerns about Smart Home Devices: A Comparative Analysis between Non-Users and Users". In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1002207.

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Privacy concerns of smart home device (SHD) users have been largely explored but those of non-users are under-explored. The success of smart home technology comes to fruition only when concerns of both users and non-users are addressed. Understanding of non-user concerns is essential to inform the design of user-centric privacy-preserving SHDs, facilitate acceptance, and bridge the digital divide between non-users and users. To address this gap, we conducted a survey of SHD non-users and comparatively analyzed their privacy concerns with those of users.Methods: We used university email list-servs, snowball sampling and random sampling methods to recruit participants (n=91) for an IRB-approved online survey, titled ‘smart home study’. Our pre-tested questionnaire asked about SHD (non-)usage, privacy concerns (open-ended), suggestions for developers and demographics. We followed a mixed-methods approach to analyze privacy concerns (qualitative/thematic), explore non-use reasons (qualitative/thematic), compare non-users and users concerns (quantitative), and analyze design suggestions (qualitative/thematic). Results: Thematic analysis of privacy concerns of non-users (n=41) and users (n=50) by two researchers performing open-coding (Cohen’s kappa = 0.8) resulted in 17 codes. We then performed axial coding to generate three thematic areas of privacy concerns. The first theme was ‘data collection concerns’ which included five codes: recording audio/video, tracking occupancy, listening to private conversations, monitoring usage/behavior, and identity theft. The second theme was ‘data sharing concerns’ which included four codes: selling data, third party data access, leakage without consent, and marketing data. The third theme was ‘data protection concerns’ which included eight codes: hacking, data handling, protecting data, secondary use, aggregation, data abuse, data loss, and fraud. The three privacy concerns themes belong to the personal communication and personal data privacy dimensions of privacy. Chi-square test between non-users and users showed the privacy concerns of non-users differed significantly (X2=8.46, p<0.05) from users. Non-users reported higher level of concerns in data collection and data protection themes than those of users (46% vs 24% and 34% vs 30% respectively). However, non-users reported fewer concerns in the data sharing theme than those of users (15% vs 28% respectively).Most non-users reported their non-use reason to be privacy concerns (68%). Other non-use reasons included lack of interest in SHDs (32%), cost (22%), lack of perceived usefulness (12%), insecurity or potential of hacking (10%), and perceived difficulty of usage (7%).The thematic analysis of participants’ suggestions for developers resulted in four main themes: (a) data anonymization and minimization, (b) data protection and security, (c) transparent data use policies, and (d) user-centric practices. Based on our findings, we recommend that developers address the data collection and data protection concerns to allow SHD non-users to consider using them. In addition, we recommend addressing data sharing concerns to retain trust of current users. We discuss some guidelines in the paper.Conclusion: This paper contributes by eliciting SHD non-user privacy concerns and provides insights on addressing the concerns, which will be useful for developers towards the design of user-centric privacy-preserving SHDs.

Bennett, Colin, e Smith Oduro-Marfo. "GLOBAL Privacy Protection". In UbiComp '18: The 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3267305.3274149.

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Karunagaran, Surya, Saji K. Mathew e Franz Lehner. "Privacy Protection Dashboard". In SIGMIS-CPR '17: Computers and People Research Conference. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3084381.3084424.

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Li, Chau Yi, Ali Shahin Shamsabadi, Ricardo Sanchez-Matilla, Riccardo Mazzon e Andrea Cavallaro. "Scene Privacy Protection". In ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2019. http://dx.doi.org/10.1109/icassp.2019.8682225.

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Zhao, Fangyuan, Xuebin Ren, Shusen Yang e Xinyu Yang. "On Privacy Protection of Latent Dirichlet Allocation Model Training". In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/675.

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Latent Dirichlet Allocation (LDA) is a popular topic modeling technique for discovery of hidden semantic architecture of text datasets, and plays a fundamental role in many machine learning applications. However, like many other machine learning algorithms, the process of training a LDA model may leak the sensitive information of the training datasets and bring significant privacy risks. To mitigate the privacy issues in LDA, we focus on studying privacy-preserving algorithms of LDA model training in this paper. In particular, we first develop a privacy monitoring algorithm to investigate the privacy guarantee obtained from the inherent randomness of the Collapsed Gibbs Sampling (CGS) process in a typical LDA training algorithm on centralized curated datasets. Then, we further propose a locally private LDA training algorithm on crowdsourced data to provide local differential privacy for individual data contributors. The experimental results on real-world datasets demonstrate the effectiveness of our proposed algorithms.

Matveev, Artem. "Cost-Efficient Data Privacy Protection in Multi Cloud Storage". In 3rd International Conference on Data Mining and Machine Learning (DMML 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.120706.

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Data privacy in the cloud is a big concern for all of its users, especially for public clouds. Modern trends in studies utilise multiple clouds to achieve data privacy protection. Most of the present studies focus on business-oriented solutions, but current study aims to create a solution for individual users which would not increase the cost of ownership, and provide enough flexibility and privacy protection by combining password protection, key-derivation, multilayer encryption and key distribution across multiple clouds. New design allows to use single cloud to store protected user data, meanwhile use free plans on other clouds to store key information on others and thereby does not rise a cost of the solution. As a result, proposed design gives multiple layers of protection of Data Privacy while having a low cost of use. With some further adaptation it could be proposed as a business solution.

Rapporti di organizzazioni sul tema "Privicy protection":

Plesser, Ronald L., e Emilio W. Cividanes. Privacy protection in the United States:. Gaithersburg, MD: National Institute of Standards and Technology, 1992. http://dx.doi.org/10.6028/nist.ir.4781.

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Chang, LiWu, e Ira A. Moskowitz. An Integrated Framework for Database Privacy Protection. Fort Belvoir, VA: Defense Technical Information Center, gennaio 2001. http://dx.doi.org/10.21236/ada465125.

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Riyadi, Gliddheo. Data Privacy in the Indonesian Personal Data Protection Legislation. Jakarta, Indonesia: Center for Indonesian Policy Studies, 2021. http://dx.doi.org/10.35497/341482.

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Hasty, III, e Thomas J. Protection of Personal Privacy Interests under the Freedom of Information Act. Fort Belvoir, VA: Defense Technical Information Center, giugno 1991. http://dx.doi.org/10.21236/ada242183.

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Lunt, Teresa, Paul Aoki, Dirk Balfanz, Glenn Durfee, Philippe Golle, Diana Smetters, Jessica Staddon, Jim Thornton e Tomas Uribe. Protecting the Privacy of Individuals in Terrorist Tracking Applications. Fort Belvoir, VA: Defense Technical Information Center, aprile 2005. http://dx.doi.org/10.21236/ada433707.

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Buillamon, Bernardo. Risk Mitigation as a Cost-Effective Microfinance Strategy: Case Study IDB-Peru Global Micro-Enterprise Credit Program. Inter-American Development Bank, marzo 2000. http://dx.doi.org/10.18235/0008670.

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Abstract (sommario):

Improved microfinance strategies in Peru have increased credit access for microentrepreneurs. To establish effective national credit reporting systems elsewhere in the region, ensured universal reporting cooperation, reliable identification, privacy and consumer protection are needed.

Rothstein, M. A. Genetic secrets: Protecting privacy and confidentiality in the genetic era. Office of Scientific and Technical Information (OSTI), luglio 1998. http://dx.doi.org/10.2172/656488.

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Vaz, Maria João, e Helena Machado. A systematic literature review of Big Data in tourism industry: a state of the art and future directions. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, maggio 2022. http://dx.doi.org/10.37766/inplasy2022.5.0012.

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Review question / Objective: P.E.O: Population, exposure, outcome. What privacy and data protection challenges are linked by different stakeholders, to the Big Data's application in the tourism sector: P - stakeholders; E - Big Data in tourism; O - privacy and data protection challenges. Condition being studied: This investigation aims to map the social and ethical controversies associated with the use of Big Data, addressing the “technological optimism” that tends to surround the use of these techniques in the tourism sector, which may compromise sustainable tourism in the long term. Main outcome(s): It allows to develop an awareness of benefits and risks and to involve all stakeholders in the debate. It will increase transparency, and promote more accessible communication while promoting the sharing of experiences and opinions from different interest groups. This type of solution should be implemented at an early stage of the process.

Abdul Hamid, Umar Zakir. Privacy for Software-defined Battery Electric Vehicles. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, giugno 2024. http://dx.doi.org/10.4271/epr2024012.

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<div class="section abstract"><div class="htmlview paragraph">The integration of software-defined approaches with software-defined battery electric vehicles brings forth challenges related to privacy regulations, such as European Union’s General Data Protection Regulation and Data Act, as well as the California Consumer Privacy Act. Compliance with these regulations poses barriers for foreign brands and startups seeking entry into these markets. Car manufacturers and suppliers, particularly software suppliers, must navigate complex privacy requirements when introducing vehicles to these regions.</div><div class="htmlview paragraph"><b>Privacy for Software-defined Battery Electric Vehicles</b> aims to educate practitioners across different market regions and fields. It seeks to stimulate discussions for improvements in processes and requirements related to privacy aspects regarding these vehicles. The report covers the significance of privacy, potential vulnerabilities and risks, technical challenges, safety risks, management and operational challenges, and the benefits of compliance with privacy standards within the software-defined battery electric vehicle realm.</div><div class="htmlview paragraph"><a href="https://www.sae.org/publications/edge-research-reports" target="_blank">Click here to access the full SAE EDGE</a><sup>TM</sup><a href="https://www.sae.org/publications/edge-research-reports" target="_blank"> Research Report portfolio.</a></div></div>

Rothstein, M. A. Genetic secrets: Protecting privacy and confidentiality in the genetic era. Final report. Office of Scientific and Technical Information (OSTI), settembre 1998. http://dx.doi.org/10.2172/656499.

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