Ugo Fiore

Prof. Ugo Fiore

Department of Management and Quantitative Sciences, Parthenope University of Naples, Naples, Italy
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Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

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

Representative Publications

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1 April 2019 in Information Sciences
Verified
Journal Article
Closed access
Ugo FioreUgo Fiore
Ugo Fiore
ASAlfredo De Santis
Alfredo De Santis
Francesca PerlaFrancesca Perla
Francesca Perla
PZPaolo Zanetti
Paolo Zanetti
FPFrancesco Palmieri
Francesco Palmieri

1 December 2013 in Neurocomputing
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Journal Article
Closed access
Ugo FioreUgo Fiore
Ugo Fiore
Francesco PalmieriFrancesco Palmieri
Francesco Palmieri
Aniello CastiglioneAniello Castiglione
Aniello Castiglione
ASAlfredo De Santis
Alfredo De Santis

9 March 2018 in Soft Computing
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Journal Article
Closed access
PDF file
CJChandrashekar Jatoth
Chandrashekar Jatoth
GGG. R. Gangadharan
G. R. Gangadharan
Ugo FioreUgo Fiore
Ugo Fiore
RBRajkumar Buyya
Rajkumar Buyya

20 June 2013 in Concurrency and Computation: Practice and Experience
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Journal Article
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Francesco PalmieriFrancesco Palmieri
Francesco Palmieri
Ugo FioreUgo Fiore
Ugo Fiore
Aniello CastiglioneAniello Castiglione
Aniello Castiglione

1 October 2010 in Computers & Security
Verified
Journal Article
Closed access
Francesco PalmieriFrancesco Palmieri
Francesco Palmieri
Ugo FioreUgo Fiore
Ugo Fiore

28 June 2014 in The Journal of Supercomputing
Verified
Journal Article
Open access
PDF file
Francesco PalmieriFrancesco Palmieri
Francesco Palmieri
SRSergio Ricciardi
Sergio Ricciardi
Ugo FioreUgo Fiore
Ugo Fiore
Massimo FiccoMassimo Ficco
Massimo Ficco
Aniello CastiglioneAniello Castiglione
Aniello Castiglione
This work analyzes a new and very subtle kind of security threat that can affect large-scale cloud-based IT service infrastructures, by exploiting the computational resources of their component data center to waste as much energy as possible. The consequence of these threats ranges from increased costs in the energy bill, to penalization for exceeding the agreed quantity of greenhouse gases (GHG) emissions, up to complete denial of service caused by electrical outages due to power budget exhaustion. We analyzed different types of such attacks with their potential impacts on the energy consumption, modeled their behavior and quantified how current energy-proportional technologies may provide attackers with great opportunities for raising the target facility emissions and costs. These efforts resulted in a simple model with some parametric reference values that can be used to estimate the impact of such attacks also in presence of very large infrastructures containing thousands or millions of servers.