A Privacy-Aware Access Control Model for Distributed Network Monitoring

International audienceIn this paper, we introduce a new access control model that aims at addressing the privacy implications surrounding network monitoring. In fact, despite its importance, network monitoring is natively leakage-prone and, moreover, this is exacerbated due to the complexity of the highly dynamic monitoring procedures and infrastructures, that may include multiple traffic observation points, distributed mitigation mechanisms and even inter-operator cooperation. Conceived on the basis of data protection legislation, the proposed approach is grounded on a rich in expressiveness information model, that captures all the underlying monitoring concepts along with their associations. The model enables the specification of contextual authorisation policies and expressive separation and binding of duty constraints. Finally, two key innovations of our work consist in the ability to define access control rules at any level of abstraction and in enabling a verification procedure, which results in inherently privacy-aware workflows, thus fostering the realisation of the Privacy by Design vision

Big Data and Analysis of Data Transfers for International Research Networks Using NetSage

Modern science is increasingly data-driven and collaborative in nature. Many scientific disciplines, including genomics, high-energy physics, astronomy, and atmospheric science, produce petabytes of data that must be shared with collaborators all over the world. The National Science Foundation-supported International Research Network Connection (IRNC) links have been essential to enabling this collaboration, but as data sharing has increased, so has the amount of information being collected to understand network performance. New capabilities to measure and analyze the performance of international wide-area networks are essential to ensure end-users are able to take full advantage of such infrastructure for their big data applications. NetSage is a project to develop a unified, open, privacy-aware network measurement, and visualization service to address the needs of monitoring today's high-speed international research networks. NetSage collects data on both backbone links and exchange points, which can be as much as 1Tb per month. This puts a significant strain on hardware, not only in terms storage needs to hold multi-year historical data, but also in terms of processor and memory needs to analyze the data to understand network behaviors. This paper addresses the basic NetSage architecture, its current data collection and archiving approach, and details the constraints of dealing with this big data problem of handling vast amounts of monitoring data, while providing useful, extensible visualization to end users

A review on visual privacy preservation techniques for active and assisted living

This paper reviews the state of the art in visual privacy protection techniques, with particular attention paid to techniques applicable to the field of Active and Assisted Living (AAL). A novel taxonomy with which state-of-the-art visual privacy protection methods can be classified is introduced. Perceptual obfuscation methods, a category in this taxonomy, is highlighted. These are a category of visual privacy preservation techniques, particularly relevant when considering scenarios that come under video-based AAL monitoring. Obfuscation against machine learning models is also explored. A high-level classification scheme of privacy by design, as defined by experts in privacy and data protection law, is connected to the proposed taxonomy of visual privacy preservation techniques. Finally, we note open questions that exist in the field and introduce the reader to some exciting avenues for future research in the area of visual privacy.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work is part of the visuAAL project on Privacy-Aware and Acceptable Video-Based Technologies and Services for Active and Assisted Living (https://www.visuaal-itn.eu/). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 861091. The authors would also like to acknowledge the contribution of COST Action CA19121 - GoodBrother, Network on Privacy-Aware Audio- and Video-Based Applications for Active and Assisted Living (https://goodbrother.eu/), supported by COST (European Cooperation in Science and Technology) (https://www.cost.eu/)

Contextual Localization Through Network Traffic Analysis

opportunitiesforcontentserviceproviderstooptimizethecontent delivery based on user’s location. Since sharing precise location remainsamajorprivacyconcernamongtheusers,manylocationbased services rely on contextual location (e.g. residence, cafe etc.) as opposed to acquiring user’s exact physical location. In this paper, we present PACL (Privacy-Aware Contextual Localizer), which can learn user’s contextual location just by passively monitoring user’s network traffic. PACL can discern a set of vital attributes (statistical and application-based) from user’s network traffic, and predict user’s contextual location with a very high accuracy.WedesignandevaluatePACLusingreal-worldnetwork traces of over 1700 users with over 100 gigabytes of total data. OurresultsshowthatPACL(builtusingdecisiontree)canpredict user’s contextual location with the accuracy of around 87%. I

Smart TV face monitoring for children privacy

© 2018 Taiwan Academic Network Management Committee. All Rights Reserved. Many of the modern Television (TV) sets and digital TV set-top boxes are endowed with Smart TV capabilities. Those include computing and connectivity to online services such as video on demand, online games and even sports and healthcare. A lot of Smart TV devices also have built-in cameras, microphones and other sensors that provide for environmental monitoring and consequent context dependent feedback. Such Smart TV capabilities, however, can lead to privacy violations through unwanted tracking and user profiling by broadcasters and other service providers. There is a concern when underage users such as children who may not fully understand the concept of privacy are involved in using the Smart TV services. To address this issue, face recognition experiments were conducted with the IBM\u27s Watson and the Microsoft\u27s Face Application Programming Interface to reveal the potential of integrating facial recognition in future privacy aware Smart TV services

Visual Privacy Protection Methods: A Survey

Recent advances in computer vision technologies have made possible the development of intelligent monitoring systems for video surveillance and ambient-assisted living. By using this technology, these systems are able to automatically interpret visual data from the environment and perform tasks that would have been unthinkable years ago. These achievements represent a radical improvement but they also suppose a new threat to individual’s privacy. The new capabilities of such systems give them the ability to collect and index a huge amount of private information about each individual. Next-generation systems have to solve this issue in order to obtain the users’ acceptance. Therefore, there is a need for mechanisms or tools to protect and preserve people’s privacy. This paper seeks to clarify how privacy can be protected in imagery data, so as a main contribution a comprehensive classification of the protection methods for visual privacy as well as an up-to-date review of them are provided. A survey of the existing privacy-aware intelligent monitoring systems and a valuable discussion of important aspects of visual privacy are also provided.This work has been partially supported by the Spanish Ministry of Science and Innovation under project “Sistema de visión para la monitorización de la actividad de la vida diaria en el hogar” (TIN2010-20510-C04-02) and by the European Commission under project “caring4U - A study on people activity in private spaces: towards a multisensor network that meets privacy requirements” (PIEF-GA-2010-274649). José Ramón Padilla López and Alexandros Andre Chaaraoui acknowledge financial support by the Conselleria d'Educació, Formació i Ocupació of the Generalitat Valenciana (fellowship ACIF/2012/064 and ACIF/2011/160 respectively)

Weathering the Nest: Privacy Implications of Home Monitoring for the Aging American Population

The research in this paper will seek to ascertain the extent of personal data entry and collection required to enjoy at least the minimal promised benefits of distributed intelligence and monitoring in the home. Particular attention will be given to the abilities and sensitivities of the population most likely to need these devices, notably the elderly and disabled. The paper will then evaluate whether existing legal limitations on the collection, maintenance, and use of such data are applicable to devices currently in use in the home environment and whether such regulations effectively protect privacy. Finally, given appropriate policy parameters, the paper will offer proposals to effectuate reasonable and practical privacy-protective solutions for developers and consumers

'E' for exposed? Email and privacy issues

In March 1996, American Libraries featured a piece about a librarian at the University of California/Irvine whose supervisor intercepted her e-mail while she was absent on medical leave. As a result of this, UC's Office for Academic Computing began a review of e-mail privacy on the nine-campus system. This article and UC's reaction prompted my research into this topic