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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
009
Publications

2019

Anomaly Detection and Modeling in 802.11 Wireless Networks

Authors
Allahdadi, A; Morla, R;

Publication
CoRR

Abstract

2019

Predicting throughput in IEEE 802.11 based wireless networks using directional antenna

Authors
Kandasamy, S; Morla, R; Ramos, P; Ricardo, M;

Publication
Wireless Networks

Abstract
In IEEE 802.11 based wireless networks interference increases as more access points are added. A metric helping to quantize this interference seems to be of high interest. In this paper we study the relationship between the (Formula presented.) metric, which captures interference, and throughput for IEEE 802.11 based network using directional antenna. The (Formula presented.) model was found to best represent the relationship between the interference metric and the network throughput. We use this model to predict the performance of similar networks and decide the best configuration a network operator could use for planning his network. © 2017 Springer Science+Business Media, LLC

2019

Rapid detection of spammers through collaborative information sharing across multiple service providers

Authors
Azad, MA; Morla, R;

Publication
Future Generation Computer Systems

Abstract
Spammers and telemarketers target a very large number of recipients usually dispersed across many Service Providers (SPs). Collaboration and Information sharing between SPs would increase the detection accuracy but detection effectiveness depends on the amount of information shared between SPs. Having service provider's exchange call detail records would arguably attain the best detection accuracy but would require significant network resources. Moreover, SPs are likely to feel uncomfortable in sharing their call records because call records contain user's private information as well as operational details of their networks. The challenge towards the design of collaborative Spam over Internet Telephony (SPIT) detection system is two-fold: it should attain high detection accuracy with a small false positive, and should fully protect the privacy of users and their service providers. In this paper, we propose a COllaborative Spit Detection System (COSDS)-a collaborative SPIT detection system for the Voice over IP (VoIP) network where service providers collaborate for the effective and early detection of SPIT callers without raising privacy concerns. To this extent, COSDS relies on a trusted Centralized Repository (CR) and exchange of non-sensitive reputation scores. The CR computes global reputation of users by aggregating the reputation scores provided by the respective collaborating SPs. The data exchanged to the CR is not sensitive regarding users privacy, and cannot be used to infer the relationship network of users. We evaluate the performance of our system using synthetic data that we have generated by simulating the realistic social behavior of spammers and non-spammers in a network. The results show that the COSDS approach has better detection accuracy as compared to the traditional stand-alone detection systems. For instances, in a setup where spammers are making calls to recipients of many SPs, COSDS successfully identifies spammers with the True Positive (TP) rate of around 80% and false positive (FP) rate of around 2% on a first day, which further increases to 100% TP rate and zero FP rate in three days. COSDS approach is fast, requires a small communication overhead, ensures privacy of users and collaborating SP, and requires only few iterations for the reputation convergence within the SP. © 2018 Elsevier B.V.

2019

Lessons Learned and Challenges on Benchmarking Publish-Subscribe loT Platforms

Authors
Aguiar, A; Morla, R;

Publication
CPS-IOTBENCH '19: PROCEEDINGS OF THE 2019 2ND WORKSHOP ON BENCHMARKING CYBER-PHYSICAL SYSTEMS AND INTERNET OF THINGS

Abstract
The Internet of Things (IoT) emerged simultaneously in various research fields and application domains, leading to the appearence of a multitude of hardware, software technologies, horizontal platforms and data models. Lost in this diversity, adoption decisions are made to a large extent based on familiarity with a technology, or because there is a broad community support for it. In this context, bechmarking different technologies at different horizontal levels would provide a more solid justification for the adoption of a specific technology in a specific context. In this paper, we reflect on our previous work on benchmarking publish-subscribe IoT platforms as a middleware for IoT applications, reporting lessons learned and identifying challenges, thus contributing to the discussion on open topics and relevant downstream work.

2018

Benchmarking Pub/Sub IoT middleware platforms for smart services

Authors
Pereira, C; Cardoso, J; Aguiar, A; Morla, R;

Publication
Journal of Reliable Intelligent Environments

Abstract

Supervised
thesis

2017

Creation of a Marketplace for NFV Functions

Author
Luís Pedro Sousa Pinto

Institution
UP-FEUP

2017

Performance of side-channel attacks on encrypted 802.11 web traffic and impact of network-level noise

Author
Pedro Manuel Vasconcelos Fonseca

Institution
UP-FEUP

2017

A Link Level Simulation Framework for Machine Type Communication towards 5G

Author
Rui Francisco Mota Nunes

Institution
UP-FEUP

2017

Serviço para Product Placement em Televisão

Author
André Casais Regado

Institution
UP-FEUP

2017

Redundância de dados para uma Solução de Voz Sobre IP

Author
Tiago Lúcio Azeredo Lobo de Oliveira Miranda

Institution
UP-FEUP