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About

About

Ricardo Morla is an assistant professor at the University of Porto. He teaches and does research at the Electrical and Computer Engineering Department at FEUP and at INESC TEC. His research interests are in management and control of IT systems and networks. He uses data analysis techniques and large-scale coordination techniques to help manage enterprise networks, IT services and infrastructure, and ambient intelligence systems. Ricardo holds a PhD in Computing from Lancaster University. He was a lecturer and post-doc at UC Irvine in 2007, and a visiting faculty at Carnegie Mellon University in 2010 under the CMU-Portugal program. He runs the Network and Services Laboratory at FEUP.

Interest
Topics
Details

Details

  • Name

    Ricardo Morla
  • Cluster

    Computer Science
  • Role

    Senior Researcher
  • Since

    15th September 1998
010
Publications

2021

An Initial Analysis of the Shortcomings of Conventional AI and the Benefits of Distributed AI Approaches in Industrial Use Cases

Authors
Hristoskova, A; Deleito, NG; Klein, S; Sousa, J; Martins, N; Tagaio, J; Serra, J; Silva, C; Ferreira, J; Santos, PM; Morla, R; Almeida, L; Bulut, B; Sultanoglu, S;

Publication
Artificial Intelligence Applications and Innovations. AIAI 2021 IFIP WG 12.5 International Workshops - 5G-PINE 2021, AI-BIO 2021, DAAI 2021, DARE 2021, EEAI 2021, and MHDW 2021, Hersonissos, Crete, Greece, June 25-27, 2021, Proceedings

Abstract

2021

Towards a Distributed Learning Architecture for Securing ISP Home Customers

Authors
Santos, PM; Sousa, J; Morla, R; Martins, N; Tagaio, J; Serra, J; Silva, C; Sousa, M; Souto, PF; Ferreira, LL; Ferreira, J; Almeida, L;

Publication
Artificial Intelligence Applications and Innovations. AIAI 2021 IFIP WG 12.5 International Workshops - 5G-PINE 2021, AI-BIO 2021, DAAI 2021, DARE 2021, EEAI 2021, and MHDW 2021, Hersonissos, Crete, Greece, June 25-27, 2021, Proceedings

Abstract

2020

Does domain name encryption increase users' privacy?

Authors
Trevisan, M; Soro, F; Mellia, M; Drago, I; Morla, R;

Publication
ACM SIGCOMM Computer Communication Review

Abstract

2020

Flow-based detection and proxy-based evasion of encrypted malware C2 traffic

Authors
Novo, C; Morla, R;

Publication
CoRR

Abstract

2020

802.11 wireless simulation and anomaly detection using HMM and UBM

Authors
Allahdadi, A; Morla, R; Cardoso, JS;

Publication
SIMULATION

Abstract
Despite the growing popularity of 802.11 wireless networks, users often suffer from connectivity problems and performance issues due to unstable radio conditions and dynamic user behavior, among other reasons. Anomaly detection and distinction are in the thick of major challenges that network managers encounter. The difficulty of monitoring broad and complex Wireless Local Area Networks, that often requires heavy instrumentation of the user devices, makes anomaly detection analysis even harder. In this paper we exploit 802.11 access point usage data and propose an anomaly detection technique based on Hidden Markov Model (HMM) and Universal Background Model (UBM) on data that is inexpensive to obtain. We then generate a number of network anomalous scenarios in OMNeT++/INET network simulator and compare the detection outcomes with those in baseline approaches—RawData and Principal Component Analysis. The experimental results show the superiority of HMM and HMM-UBM models in detection precision and sensitivity.

Supervised
thesis

2020

Detection of Encrypted Malware Command and Control Traffic

Author
Carlos António de Sousa Costa Novo

Institution
UP-FCUP

2020

Performance Anomaly Detection in 802.11 Wireless Networks Applying Hidden Markov Models

Author
Anisa Allahdadidastjerdi

Institution
UP-FCUP

2020

A Two Stage Classifier for DGA Detection

Author
Joaquim Pedro Marques Coelho dos Santos

Institution
UP-FEUP

2020

Adversarial Malware Command and Control Traffic Generation

Author
Carlos António de Sousa Costa Novo

Institution
UP-FEUP

2020

Attacking an Autonomous Vehicle Brake Anomaly Detector with Adversarial Learning Techniques

Author
Francisco Maria Fernandes Machado Santos

Institution
UP-FEUP