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Scientific Publications

2021

Horus: Non-Intrusive Causal Analysis of Distributed Systems Logs

Francisco Neves, Nuno Machado, Ricardo Vilaça, José Pereira

51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2021)

Totally-Ordered Prefix Parallel Snapshot Isolation

Nuno Faria, José Pereira

8th Workshop on Principles and Practice of Consistency for Distributed Data (PaPoC @ EuroSys 2021)

 

Partially Monotonic Learning for Neural Networks

Joana Trindade, João Vinagre, Kelwin Fernandes, Nuno Paiva, Alípio Jorge

19th International Symposium on Intelligent Data Analysis (IDA 2021)

Efficient Privacy Preserving Distributed K-Means for Non-IID Data

André Brandão, Ricardo Mendes, João P. Vilela

19th International Symposium on Intelligent Data Analysis (IDA 2021)

Analysis of VM Migration Scheduling as Moving Target Defense against insider attacks

Matheus Torquato, Paulo Maciel, Marco Vieira

ACM/SIGAPP Symposium on Applied Computing (ACM SAC 2021)

2020

On the Use of Open-Source C/C++ Static AnalysisTools in Large Projects

José D’Abruzzo Pereira, Marco Vieira 

16th European Dependable Computing Conference (EDCC 2020)

An Availability Model for DSS and OLTP Applications in Virtualized Environments

Matheus Torquato, Charles F. Goncalves, Marco Vieira

16th European Dependable Computing Conference (EDCC 2020)

Vulnerability Analysis as Trustworthiness Evidence in Security Benchmarking: A Case Study on Xen

Charles F. Gonçalves, Nuno Antunes

5th IEEE International Workshop on Reliability and Security Data Analysis (RSDA 2020) 

Fault Injection to Generate Failure Data for Failure Prediction: A Case Study

João R. Campos, Ernesto Costa

31st International Symposium on Software Reliability Engineering (ISSRE 2020)

Using Attack Injection to Evaluate Intrusion Detection Effectiveness in Container-based Systems

J. Flora, P. Gonçalves, N. Antunes

25th IEEE Pacific Rim International Symposium on Dependable Computing (PRDC 2020)

Vulnerable Code Detection Using Software Metrics and Machine Learning

Nádia Medeiros, Naghmeh Ivaki, Pedro Costa, Marco Vieira 

IEEE Access

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