État académique
Thèse soutenue le 2017-03-20
Sujet: Processus guidé pour l'identification d'exigences de sécurité à partir de l'analyse des risques
Direction de thèse:
Ellipse bleue: doctorant, ellipse jaune: docteur, rectangle vert: permanent, rectangle jaune: HDR. Trait vert: encadrant de thèse, trait bleu: directeur de thèse, pointillé: jury d'évaluation à mi-parcours ou jury de thèse.
Productions scientifiques
Research on Big DataCharacterizing the Field and Its Dimensions
International audience
Big Data has emerged as a significant area of study for both practitionersand researchers. Big Data is a term for massive data sets with largestructure. In 2012, Big Data passed the top of the Gartner Hype Cycle, attestingthe maturity level of this technology and its applications. The aim of this paperis to examine whether the Big Data research community reached the same levelof maturity. For this purpose, we provide a framework identifying existing andemerging research areas of Big Data. This framework is based on five dimensions,including the SMACIT perspective. Current and past research in Big Dataare analyzed using a bibliometric study of publications based on more than adecade of related academic publications. The results have shown that even ifsignificant contributions have been made by the research community, attested bya continuous increase in the number of scientific publications that address BigData, it lags behind entreprises’ expectations
ER 2015 MoBiD 2015 https://hal.archives-ouvertes.fr/hal-01215716 MoBiD 2015, Oct 2015, Stockholm Sweden. ER 2015, 2015, <10.1007/978-3-319-25747-1_18>ARRAY(0x7fe6a9173940) 2015-10-19
Thèse: Processus guidé pour l'identification des exigences de sécurité à partir de l'analyse des risques
Soutenance: 2017-03-20
Rapporteurs: Frédéric CUPPENS    Zoubida KEDAD