Cookies
Usamos cookies para melhorar nosso site e a sua experiência. Ao continuar a navegar no site, você aceita a nossa política de cookies. Ver mais
Aceitar Rejeitar
  • Menu
Sobre

Sobre

Ricardo Morla é professor auxiliar na Universidade do Porto. Ensina e desenvolve investigação no Departamento de Engenharia Electrotécnica e de Computadores da FEUP e no INESC TEC. Os seus interesses de investigação centram-se na gestão e no controlo de redes e sistemas IT. Aplica técnicas de análise de dados e técnicas de coordenação em grande escala para ajudar a gerir redes empresariais, serviços e infraestrutura IT, e sistemas de inteligência ambiente. É doutorado em Computação pela Universidade de Lancaster. Foi lecturer e post-doc na Universidade da Califórnia em Irvine em 2007, e professor convidado na Universidade de Carnegie Mellon em 2010 no âmbito do programa CMU-Portugal. Dinamiza o laboratório de Redes e Serviços da FEUP.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Ricardo Morla
  • Cargo

    Investigador Sénior
  • Desde

    15 setembro 1998
  • Nacionalidade

    Portugal
  • Contactos

    +351222094299
    ricardo.morla@inesctec.pt
010
Publicações

2020

Does domain name encryption increase users' privacy?

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

Publicação
ACM SIGCOMM Computer Communication Review

Abstract

2020

802.11 wireless simulation and anomaly detection using HMM and UBM

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

Publicação
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.

2019

Anomaly Detection and Modeling in 802.11 Wireless Networks

Autores
Allahdadi, A; Morla, R;

Publicação
CoRR

Abstract

2019

Predicting throughput in IEEE 802.11 based wireless networks using directional antenna

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

Publicação
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

Autores
Azad, MA; Morla, R;

Publicação
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.

Teses
supervisionadas

2019

Cybersecurity analysis of a SCADA system under current standards, penetration testing and definition of mitigating strategies

Autor
Filipe Pestana Duarte Rocha

Instituição
UP-FEUP

2019

Monitorização de um Sistema Publish-Subscribe ROS para Enumeração e Deteção de Intrusões

Autor
João Pedro Xavier Araújo

Instituição
UP-FEUP

2019

Deteção de nomes de domínios gerados aleatoriamente

Autor
António Jorge Aguiar do Vale

Instituição
UP-FEUP

2019

Computação Paralela na Análise de Tráfego de Redes de Comunicação

Autor
Tiago Samuel da Rocha Silva

Instituição
UP-FEUP

2018

An Architecture for the Scalable Benchmarking of IoT Middleware and Streaming Platforms

Autor
Luís Rodrigues Zilhão Nogueira

Instituição
UP-FEUP