Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning

Deep Learning has recently become hugely popular in machine learning, providing significant improvements in classification accuracy in the presence of highly-structured and large databases. Researchers have also considered privacy implications of deep learning. Models are typically trained in a centralized manner with all the data being processed by the same training algorithm. If the data is a collection of users' private data, including habits, personal pictures, geographical positions, interests, and more, the centralized server will have access to sensitive information that could potentially be mishandled. To tackle this problem, collaborative deep learning models have recently been proposed where parties locally train their deep learning structures and only share a subset of the parameters in the attempt to keep their respective training sets private. Parameters can also be obfuscated via differential privacy (DP) to make information extraction even more challenging, as proposed by Shokri and Shmatikov at CCS'15. Unfortunately, we show that any privacy-preserving collaborative deep learning is susceptible to a powerful attack that we devise in this paper. In particular, we show that a distributed, federated, or decentralized deep learning approach is fundamentally broken and does not protect the training sets of honest participants. The attack we developed exploits the real-time nature of the learning process that allows the adversary to train a Generative Adversarial Network (GAN) that generates prototypical samples of the targeted training set that was meant to be private (the samples generated by the GAN are intended to come from the same distribution as the training data). Interestingly, we show that record-level DP applied to the shared parameters of the model, as suggested in previous work, is ineffective (i.e., record-level DP is not designed to address our attack).Comment: ACM CCS'17, 16 pages, 18 figure

Using System Analysis and Personas for e-Health Interaction Design

Today, designers obtain more central roles in product and service development (Perks, Cooper, & Jones, 2005). They have to deal with increasingly complicated problems, like integrating the needs of various stakeholders while taking care about social, ethical and ecological consequences of their designs. To deal with this demanding design situation, they need to apply new methods to organize the available information and to negotiate the stakeholder’s perspectives. This paper describes how systems analysis supports the design process in a complex environment. In a case study, we demonstrate how this method enables designers to describe user requirements for complex design environments while considering the perspectives of various stakeholders. We present a design research project applying cybernetic systems analysis using the software ''System-Tools'' (Vester, 2002). Results from the analysis were taken to inform the design of an electronic patient record (EPR), considering the particularities of the German health care system. Based on the analysis, we developed a set of requirements for every stakeholder group, detailing the patients' perspective with persona descriptions. We then picked a main persona as reference for the EPR design. We describe the resulting design sketch and discuss the value of cybernetic systems analysis as a tool to deal with complex social environments. The result shows how the method helps designers to structure and organize information about the context and identify fruitful intervention opportunities for design. Keywords: E-Health; System Analysis, Cybernetics; Personas.</p

CHORUS Deliverable 4.5: Report of the 3rd CHORUS Conference

The third and last CHORUS conference on Multimedia Search Engines took place from the 26th to the 27th of May 2009 in Brussels, Belgium. About 100 participants from 15 European countries, the US, Japan and Australia learned about the latest developments in the domain. An exhibition of 13 stands presented 16 research projects currently ongoing around the world

A Middleware for Self-Organising Distributed Ambient Assisted Living Applications

This paper presents a middleware approach for self-organising distributed applications in the area of Ambient Assisted Living (AAL) as part of a home service platform. The middleware uses real time data processing techniques to identify complex events based on sensor input and service logs. This low-level and high-level information represents the platform’s context model, which forms the basis for self-organisation properties: Controllers use context information to manage running services while adhering to strategies defined by users or inferred by the system itself

CHORUS Deliverable 3.4: Vision Document

The goal of the CHORUS Vision Document is to create a high level vision on audio-visual search engines in order to give guidance to the future R&D work in this area and to highlight trends and challenges in this domain. The vision of CHORUS is strongly connected to the CHORUS Roadmap Document (D2.3). A concise document integrating the outcomes of the two deliverables will be prepared for the end of the project (NEM Summit)

Live Social Semantics

Social interactions are one of the key factors to the success of conferences and similar community gatherings. This paper describes a novel application that integrates data from the semantic web, online social networks, and a real-world contact sensing platform. This application was successfully deployed at ESWC09, and actively used by 139 people. Personal profiles of the participants were automatically generated using several Web~2.0 systems and semantic academic data sources, and integrated in real-time with face-to-face contact networks derived from wearable sensors. Integration of all these heterogeneous data layers made it possible to offer various services to conference attendees to enhance their social experience such as visualisation of contact data, and a site to explore and connect with other participants. This paper describes the architecture of the application, the services we provided, and the results we achieved in this deployment

Linked Data - the story so far

The term “Linked Data” refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions of assertions— the Web of Data. In this article, the authors present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. They describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked Data community as it moves forward

Consuming the experience : the effect of experimental stimuli on the contextual self

This thesis develops identity theory in the context of experiential consumption through the creation of a contextual self. This unique feature of identity advances theory more commonly associated with service-dominant logic, under the proposition that experiences are a consumption activity in their own right which are under-valued when treated as a sub-activity of service consumption. Using a music festival as an experiential example, literature is identified based on the interpretive effects of symbolic interactionism. This highlights the importance of objective, inter-subjective, and subjective stimuli, namely the physical environment, the social environment, and the individual environment respectively. This provides a way of understanding contextual identity and subsequent value creation. This is explored using an in-depth study based on interactionist enquiry as a means to understand the lived experience of the festival-goer in their native habitat. Participant observations and in-field interviews with attendees are conducted using a semi-structured process, and analysed along thematic lines as a way to show the influence of existing theory as well as emerging lines of enquiry. Conclusions identify a 'contextual identity' – a unique identity formed by the persuasive effects of objective and inter-subjective stimuli. However, contextual identity only truly exists in comparison to individuals not attending the experience. During the experience itself, the strength of contextual identity diminishes, acting as no more than a primer for more dominant, deep-rooted identity concepts. The result of this experience-primed identity is the ‘contextual self’, which becomes the dominant behavioural guide during the actual experience. Implications are applicable across a number of contexts and provide not only a better theoretical understanding of identity within the experiential consumption process, but also practical suggestions to improve the consumer's experience