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SOTERIA: Preserving privacy in distributed machine learning
Brito, Cláudia Vanessa Martins; Ferreira, Pedro G.; Portela, Bernardo; Oliveira, Rui Carlos Mendes de; Paulo, JoãoWe propose Soteria, a system for distributed privacy-preserving Machine Learning (ML) that leverages Trusted Execution Environments (e.g. Intel SGX) to run code in isolated containers (enclaves). Unlike previous work, where all ML-related computation is performed at trusted enclaves, we introduce a hybrid scheme, combining computation done inside and outside these enclaves. The conducted experimental evaluation...
Privacy-preserving machine learning on Apache Spark
Brito, Cláudia Vanessa Martins; Ferreira, Pedro G.; Portela, Bernardo L.; Oliveira, Rui Carlos Mendes de; Paulo, Joao T.The adoption of third-party machine learning (ML) cloud services is highly dependent on the security guarantees and the performance penalty they incur on workloads for model training and inference. This paper explores security/performance trade-offs for the distributed Apache Spark framework and its ML library. Concretely, we build upon a key insight: in specific deployment settings, one can reveal carefully ch...
An innovative maturity model to assess supply chain quality management
Cubo, Catarina; Oliveira, Rui Carlos Mendes de; Fernandes, Ana Cristina; Sampaio, Paulo; Carvalho, Maria Sameiro; Afonso, PauloPurpose: This paper aims to present and discuss an innovative maturity model (MM) to assess supply chain quality management (SCQM). The SCQM MM can be used to guide organizations in the development and improvement of quality in their supply chains (SCs). Additionally, this paper intends to better understand that integration and its impacts on organizational performance. Design/methodology/approach: The proposed...
Diagnosing applications' I/O behavior through system call observability
Esteves, Tania; Macedo, Ricardo; Oliveira, Rui Carlos Mendes de; Paulo, JoaoWe present DIO, a generic tool for observing inefficient and erroneous I/O interactions between applications and in-kernel storage systems that lead to performance, dependability, and correctness issues. DIO facilitates the analysis and enables near real-time visualization of complex I/O patterns for data-intensive applications generating millions of storage requests. This is achieved by non-intrusively interce...
Toward a practical and timely diagnosis of application's I/O behavior
Esteves, Tania; Macedo, Ricardo; Oliveira, Rui Carlos Mendes de; Paulo, JoaoWe present DIO, a generic tool for observing inefficient and erroneous I/O interactions between applications and in-kernel storage backends that lead to performance, dependability, and correctness issues. DIO eases the analysis and enables near real-time visualization of complex I/O patterns for data-intensive applications generating millions of storage requests. This is achieved by non-intrusively intercepting...
Loom: a closed-box disaggregated database system
Coelho, Fábio; Alonso, Ana; Ferreira, Luis; Pereira, José; Oliveira, Rui Carlos Mendes deCloud native database systems provide highly available and scalable services as part of cloud platforms by transparently replicating and partitioning data across automatically managed resources. Some systems, such as Google Spanner, are designed and implemented from scratch. Others, such as Amazon Aurora, derive from traditional database systems for better compatibility but disaggregate storage to cloud service...
Optical bonding process of flat panel displays and their critical-to-quality fa...
Oliveira, Rui Carlos Mendes de; Viana, J. C.; Sampaio, PauloAutomotive and display manufacturers have been working on several products and production processes to allow automakers to produce the best display systems possible at a competitive cost. One of the production processes that has been receiving attention is the Optical Bonding process. With this process, displays see significant improvements regarding display contrast, enhanced visibility, and readability, as we...
TADA: a toolkit for approximate distributed agreement
da Conceição, Eduardo Lourenço; Nunes Alonso, Ana; Oliveira, Rui Carlos Mendes de; Pereira, JoséApproximate agreement has long been relegated to the sidelines compared to exact consensus, with its most notable application being clock synchronisation. Other proposed applications stemming from control theory target multi-agent consensus, namely for sensor stabilisation, coordination in robotics, and trust estimation. Several proposals for approximate agreement follow the Mean Subsequence Reduce approach, si...
Deploying decentralized, privacy-preserving proximity tracing
Troncoso, Carmela; Bogdanov, Dan; Bugnion, Edouard; Chatel, Sylvain; Cremers, Cas; Gurses, Seda; Hubaux, Jean-Pierre; Jackson, Dennis; Larus, James R.[Excerpt] CONTACT TRACING IS a time-proven technique for breaking infection chains in epidemics. Public health officials interview those who come in contact with an infectious agent, such as a virus, to identify exposed, potentially infected people. These contacts are notified that they are at risk and should take efforts to avoid infecting others—for example, by going into quarantine, taking a test, wearing a ...
Toward a common performance and effectiveness terminology for digital proximity...
Lueks, Wouter; Benzler, Justus; Bogdanov, Dan; Kirchner, Göran; Lucas, Raquel; Oliveira, Rui Carlos Mendes de; Preneel, Bart; Salathé, MarcelDigital proximity tracing (DPT) for Sars-CoV-2 pandemic mitigation is a complex intervention with the primary goal to notify app users about possible risk exposures to infected persons. DPT not only relies on the technical functioning of the proximity tracing application and its backend server, but also on seamless integration of health system processes such as laboratory testing, communication of results (and ...