1,408 research outputs found

    Privaatsuse sĂ€ilitamine kasutades nĂ€ovahetusel pĂ”hinevat pildi anonĂŒĂŒmseks muutmise tööriista

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    The General Data Protection Regulation that was implemented in 2018 put increased stress on online privacy of people. This increased the pressure on social media platforms to protect privacy and follow the new set of guidelines. Currently, the only possible tool for preserving personal privacy is censorship, which either covers up or blurs out a part of an image that could potentially conceal vital details. This thesis proposes a proof of concept for a solution that could keep the image undisrupted while preserving the privacy of the person. This potential solution replaces the face with a generated face that lacks distinguishing features. This thesis describes the steps required to carry out face replacement. It takes advantage of precise facial detection in combination with a face collage that was generated by averaging copious amounts of facial images. The result is an image that still has all its details while preserving the privacy of the person. In estonian: Isikuandmete kaitse ĂŒldmÀÀrus, mis vĂ”eti kasutusele aastal 2018, rĂ”hutas inimeste privaatsust veebis. See nĂ”udis, et sotsiaalmeedia kanalid peavad kaitsma inimeste privaatsust ja jĂ€rgima uusi suuniseid. Hetkel ainuke vahend eraelu privaatsuse sĂ€ilitamiseks on tsensuur, mis katab vĂ”i hĂ€gustab osa pildist, kuid vĂ”ib potentsiaalselt varjata tĂ€htsaid detaile. Selles lĂ”putöös esitletakse lahenduse kontseptsioon, mis ei moonda pilti, kuid sĂ€ilitab inimese privaatsuse. See potentsiaalne lahendus asendab inimese nĂ€o genereeritud nĂ€oga, millel puuduvad eristatavad iseĂ€rasused. Selles lĂ”putöös kirjeldatakse vajalikke etappe, et teostada nĂ€ovahetust. See kasutab tĂ€pset nĂ€otuvastust koos nĂ€okollaaĆŸiga, mis loodi mitmete nĂ€gude kokku ĂŒhtlustamise teel. Tulemuseks on pilt, mis sisaldab kĂ”iki vajalikke detaile, kuid sĂ€ilitab inimese privaatsuse

    Functional anonymisation: Personal data and the data environment

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    Anonymisation of personal data has a long history stemming from the expansion of the types of data products routinely provided by National Statistical Institutes. Variants on anonymisation have received serious criticism reinforced by much-publicised apparent failures. We argue that both the operators of such schemes and their critics have become confused by being overly focused on the properties of the data themselves. We claim that, far from being able to determine whether data are anonymous (and therefore non-personal) by looking at the data alone, any anonymisation technique worthy of the name must take account of not only the data but also their environment. This paper proposes an alternative formulation called functional anonymisation that focuses on the relationship between the data and the environment within which the data exist (their data environment). We provide a formulation for describing the relationship between the data and their environment that links the legal notion of personal data with the statistical notion of disclosure control. Anonymisation, properly conceived and effectively conducted, can be a critical part of the toolkit of the privacy-respecting data controller and the wider remit of providing accurate and usable data

    Secure Dynamic Cloud-based Collaboration with Hierarchical Access

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    In recent years, the Cloud has emerged as an attractive way of hosting and delivering services over the Internet. This has resulted in a renewed focus on information security in the case where data is stored in the virtual space of the cloud and is not physically accessible to the customer. Through this thesis the boundaries of securing data in a cloud context, while retaining the benefits of the cloud, are explored. The thesis addresses the increasing security concerns of migrating to the cloud andutilising it for data storage.The research of this thesis is divided into three separate areas: securing data in an untrusted cloud environment, ensuring data access control in the cloud, and securing data outside the cloud in the user's environment. Each area is addressed by separate conceptual designs. Together these comprise a secure dynamic cloud-based collaboration environment with hierarchical access. To further validate the conceptual designs, proof of concept prototypes have been constructed.The conceptual designs have been devised by exploring and extending the boundaries of existing secure data-storage schemes, and then combining these with well-known security principles and cutting-edge research within the field of cryptography. The results of this thesis are feasible conceptual designs for a cloud-based dynamic collaboration environment. The conceptual designs address the challenges of secure cloud-based storage and allow the benefits of cloud-based storage to be utilised. Furthermore, this thesis provides a solid foundation for further work within this field

    Generating Artificial Data for Private Deep Learning

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    In this paper, we propose generating artificial data that retain statistical properties of real data as the means of providing privacy with respect to the original dataset. We use generative adversarial network to draw privacy-preserving artificial data samples and derive an empirical method to assess the risk of information disclosure in a differential-privacy-like way. Our experiments show that we are able to generate artificial data of high quality and successfully train and validate machine learning models on this data while limiting potential privacy loss.Comment: Privacy-Enhancing Artificial Intelligence and Language Technologies, AAAI Spring Symposium Series, 201

    Documentation FiFoSiM: integrated tax benefit microsimulation and CGE model

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    This documentation describes FiFoSiM, the integrated tax benefit microsimulation and CGE model of the Center of Public Economics at the University of Cologne. FiFoSiM consists of three main parts. The first part is a static tax benefit microsimulation module. The second part adds a behavioural component to the model: an econometricaly estimated labour supply model. The third module is a CGE model which allows the user of FiFoSiM to assess the global economic e€ects of policy measures. Two specific features distinguish FiFoSiM from other tax benefit models. First, the simultaneous use of two databases for the tax benefit module and second, the linkage of the tax benefit model to a CGE model. --FiFoSiM,microsimulation,CGE

    The Promise of Workplace Training for Non-College-Bound Youth: Theory and Evidence from German Apprenticeship

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    This paper assesses the potential of `workplace training' with reference to German Apprenticeship. When occupational matching is important, we derive conditions under which firms provide `optimal' training packages. Since the German system broadly meets these conditions, we evaluate the effectiveness of apprenticeship using a large administrative dataset. We find returns to apprenticeship for even the lowest ability school-leavers comparable to standard estimates of the return to school, and show that training is transferable across a wide range of occupations. We conclude that the positive experience with German Apprenticeship Training may guide the design of similar policies in other countries.

    The Promise of Workplace Training for Non-College Bound Youth: Theory and Evidence from German Apprenticeship

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    This paper assesses the potential of `workplace training' with reference to German Apprenticeship. When occupational matching is important, we derive conditions under which firms provide `optimal' training packages. Since the German system broadly meets these conditions, we evaluate the effectiveness of apprenticeship using a large administrative dataset. We find returns to apprenticeship for even the lowest ability school-leavers comparable to standard estimates of the return to school, and show that training is transferable across a wide range of occupations, such as a one-digit occupation group. We conclude that the positive experience with German Apprenticeship Training may guide the design of similar policies in other countries.German Apprenticeship Training, Human Capital, Occupational Mobility, Wages.

    Advancing security information and event management frameworks in managed enterprises using geolocation

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    Includes bibliographical referencesSecurity Information and Event Management (SIEM) technology supports security threat detection and response through real-time and historical analysis of security events from a range of data sources. Through the retrieval of mass feedback from many components and security systems within a computing environment, SIEMs are able to correlate and analyse events with a view to incident detection. The hypothesis of this study is that existing Security Information and Event Management techniques and solutions can be complemented by location-based information provided by feeder systems. In addition, and associated with the introduction of location information, it is hypothesised that privacy-enforcing procedures on geolocation data in SIEMs and meta- systems alike are necessary and enforceable. The method for the study was to augment a SIEM, established for the collection of events in an enterprise service management environment, with geo-location data. Through introducing the location dimension, it was possible to expand the correlation rules of the SIEM with location attributes and to see how this improved security confidence. An important co-consideration is the effect on privacy, where location information of an individual or system is propagated to a SIEM. With a theoretical consideration of the current privacy directives and regulations (specifically as promulgated in the European Union), privacy supporting techniques are introduced to diminish the accuracy of the location information - while still enabling enhanced security analysis. In the context of a European Union FP7 project relating to next generation SIEMs, the results of this work have been implemented based on systems, data, techniques and resilient features of the MASSIF project. In particular, AlienVault has been used as a platform for augmentation of a SIEM and an event set of several million events, collected over a three month period, have formed the basis for the implementation and experimentation. A "brute-force attack" misuse case scenario was selected to highlight the benefits of geolocation information as an enhancement to SIEM detection (and false-positive prevention). With respect to privacy, a privacy model is introduced for SIEM frameworks. This model utilises existing privacy legislation, that is most stringent in terms of privacy, as a basis. An analysis of the implementation and testing is conducted, focusing equally on data security and privacy, that is, assessing location-based information in enhancing SIEM capability in advanced security detection, and, determining if privacy-enforcing procedures on geolocation in SIEMs and other meta-systems are achievable and enforceable. Opportunities for geolocation enhancing various security techniques are considered, specifically for solving misuse cases identified as existing problems in enterprise environments. In summary, the research shows that additional security confidence and insight can be achieved through the augmentation of SIEM event information with geo-location information. Through the use of spatial cloaking it is also possible to incorporate location information without com- promising individual privacy. Overall the research reveals that there are significant benefits for SIEMs to make use of geo-location in their analysis calculations, and that this can be effectively conducted in ways which are acceptable to privacy considerations when considered against prevailing privacy legislation and guidelines

    Documentation FiFoSiM: Integrated tax benefit microsimulation

    Get PDF
    This paper describes FiFoSiM, the integrated tax benefit microsimulation and CGE model of the Center of Public Economics at the University of Cologne. FiFoSiM consists of three main parts. The first part is a static tax benefit microsimulation module. The second part adds a behavioural component to the model: an econometrically estimated labour supply model. The third module is a CGE model which allows the user of FiFoSiM to assess the global economic effects of policy measures. Two specific features distinguish FiFoSiM from other tax benefit models: First, the simultaneous use of two databases for the tax benefit module and second, the linkage of the tax benefit model to a CGE model. --FiFoSiM,microsimulation,CGE

    A Modified Anonymisation Algorithm Towards Reducing Information Loss.

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    The growth of various technologies in the modern digital world results in the col- lection and storage of huge amounts of individual\u27s data. In addition of providing direct services delivery, this data can be used for other non-direct activities known as secondary use. This includes activities such as doing research, analysis, quality and safety measurement, public health, and marketing
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