Ana Respicio

Prof. Dr. Ana Respicio

LASIGE, Lisbon, Lisboa, Portugal
+1
orcid

Research Focus & Metrics

Academic Career Length

22Years (2005-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
1 June 2018 in Computers & Security
Verified
Journal Article
Closed access
KCKrzysztof Cabaj
Krzysztof Cabaj
DDDulce Domingos
Dulce Domingos
Zbigniew KotulskiZbigniew Kotulski
Zbigniew Kotulski
ARAna Respicio
Ana Respicio

26 March 2019
Verified
Book Chapter
Open access
PDF file
SVSalvatore Vitabile
Salvatore Vitabile
MMMichal Marks
Michal Marks
DSDragan Stojanović
Dragan Stojanović
SPSabri Pllana
Sabri Pllana
Jose M. MolinaJose M. Molina
Jose M. Molina
Ioan SalomieIoan Salomie
Ioan Salomie
Recent developments in sensor technology, wearable computing, Internet of Things (IoT), and wireless communication have given rise to research in ubiquitous healthcare and remote monitoring of human’s health and activities. Health monitoring systems involve processing and analysis of data retrieved from smartphones, smart watches, smart bracelets, as well as various sensors and wearable devices. Such systems enable continuous monitoring of patients psychological and health conditions by sensing and transmitting measurements such as heart rate, electrocardiogram, body temperature, respiratory rate, chest sounds, or blood pressure. Pervasive healthcare, as a relevant application domain in this context, aims at revolutionizing the delivery of medical services through a medical assistive environment and facilitates the independent living of patients. In this chapter, we discuss (1) data collection, fusion, ownership and privacy issues; (2) models, technologies and solutions for medical data processing and analysis; (3) big medical data analytics for remote health monitoring; (4) research challenges and opportunities in medical data analytics; (5) examples of case studies and practical solutions.

1 March 2020 in Parallel Computing
Verified
Journal Article
Closed access
VAVasco Amaral
Vasco Amaral
BNBeatriz Norberto
Beatriz Norberto
MGMiguel Goulão
Miguel Goulão
MAMarco Aldinucci
Marco Aldinucci
SBSiegfried Benkner
Siegfried Benkner
AVAri Visa
Ari Visa

16 September 2010 in Journal of Scheduling
Verified
Journal Article
Closed access
PDF file
MMMarta Mesquita
Marta Mesquita
MMMargarida Moz
Margarida Moz
APAna Paias
Ana Paias
JPJosé Paixão
José Paixão
MPMargarida Pato
Margarida Pato
ARAna Respicio
Ana Respicio

6 November 2008 in Public Transport
Verified
Journal Article
Closed access
PDF file
MMMarta Mesquita
Marta Mesquita
APAna Paias
Ana Paias
ARAna Respicio
Ana Respicio

16 April 2018 in Journal of Decision Systems
Verified
Journal Article
Closed access
LALuís Almeida
Luís Almeida
ARAna Respicio
Ana Respicio
With the emergence of the Internet, the volume of cyberattacks has been progressively growing and, therefore, adequate security of information has a crucial role in IT systems. Organisations face complex decisions regarding the selection of security controls that allow protecting their information assets. The implementation of these controls should ensure an adequate level of protection. However, their selection requires knowledge about the vulnerabilities and threats existing in the organisation, and the investment in security must comply with economic constraints. This work proposes a framework to support an organisation to identify security vulnerabilities and optimise a portfolio of security controls to mitigate them. Those security controls may be of a mixed nature, such as hardware controls, software controls, policies, procedures and training actions. The framework is established using the standards ISO/IEC 27001:2013 and ISO/IEC 27002:2013 to support the identification of vulnerabilities/threats and the choice of controls that can mitigate them. Once the existing vulnerabilities/threats are identified, one has to select the subset of controls to implement, assuring an adequate mitigation at the lowest cost. An integer programming model is used to address this optimisation problem within the framework, which has been implemented as a prototype decision support tool.