3,717 research outputs found

    A Comprehensive Bibliometric Analysis on Social Network Anonymization: Current Approaches and Future Directions

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    In recent decades, social network anonymization has become a crucial research field due to its pivotal role in preserving users' privacy. However, the high diversity of approaches introduced in relevant studies poses a challenge to gaining a profound understanding of the field. In response to this, the current study presents an exhaustive and well-structured bibliometric analysis of the social network anonymization field. To begin our research, related studies from the period of 2007-2022 were collected from the Scopus Database then pre-processed. Following this, the VOSviewer was used to visualize the network of authors' keywords. Subsequently, extensive statistical and network analyses were performed to identify the most prominent keywords and trending topics. Additionally, the application of co-word analysis through SciMAT and the Alluvial diagram allowed us to explore the themes of social network anonymization and scrutinize their evolution over time. These analyses culminated in an innovative taxonomy of the existing approaches and anticipation of potential trends in this domain. To the best of our knowledge, this is the first bibliometric analysis in the social network anonymization field, which offers a deeper understanding of the current state and an insightful roadmap for future research in this domain.Comment: 73 pages, 28 figure

    A metric-based approach to assess risk for "on cloud" federated identity management

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    The cloud computing paradigm is set to become the next explosive revolution on the Internet, but its adoption is still hindered by security problems. One of the fundamental issues is the need for better access control and identity management systems. In this context, Federated Identity Management (FIM) is identified by researchers and experts as an important security enabler, since it will play a vital role in allowing the global scalability that is required for the successful implantation of cloud technologies. However, current FIM frameworks are limited by the complexity of the underlying trust models that need to be put in place before inter-domain cooperation. Thus, the establishment of dynamic federations between the different cloud actors is still a major research challenge that remains unsolved. Here we show that risk evaluation must be considered as a key enabler in evidencebased trust management to foster collaboration between cloud providers that belong to unknown administrative domains in a secure manner. In this paper, we analyze the Federated Identity Management process and propose a taxonomy that helps in the classification of the involved risks in order to mitigate vulnerabilities and threats when decisions about collaboration are made. Moreover, a set of new metrics is defined to allow a novel form of risk quantification in these environments. Other contributions of the paper include the definition of a generic hierarchical risk aggregation system, and a descriptive use-case where the risk computation framework is applied to enhance cloud-based service provisioning.This work was supported in part by the Spanish Ministry of Science and Innovation under the project CONSEQUENCE (TEC2010-20572-C02-01).Publicad

    Routes for breaching and protecting genetic privacy

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    We are entering the era of ubiquitous genetic information for research, clinical care, and personal curiosity. Sharing these datasets is vital for rapid progress in understanding the genetic basis of human diseases. However, one growing concern is the ability to protect the genetic privacy of the data originators. Here, we technically map threats to genetic privacy and discuss potential mitigation strategies for privacy-preserving dissemination of genetic data.Comment: Draft for comment
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