Veröffentlichungen

Sphynx ist in der Regel Partner in Forschungsprojekten, die neue und innovative Ergebnisse hervorbringen. Hier finden Sie einen Index aller Forschungsarbeiten und Veröffentlichungen, an denen unsere Teammitglieder mitgewirkt haben:

2017

Petroulakis et al., 2017. Fault Tolerance Using an SDN Pattern Framework, IEEE Global Communications Conference 2017 (Globecom 2017), Singapore, December 2017

2017

Krotsiani et al., 2017. Cloud Certification Process Validation using Formal Methods, 15th International Conference on Service Oriented Computing (ICSOC 2017), LNCS, Malaga, Spain, 15-17 November 2017

2017

Anisetti et al., 2017. Towards Transparent and Trustworthy Cloud, IEEE Cloud Computing 4(3):40-48, January 2017, DOI: 10.1109/MCC.2017.51

2017

Pino et al., 2017. Pattern-Based Design and Verification of Secure Service Compositions, IEEE Transactions on Services Computing, April 2017, DOI: 10.1109/TSC.2017.2690430, (SJR: 1.2)

2017

Tietz et al., 2017. Associations between hearing performance and physiological measures – an overview and outlook, Studies in Studies in Health Technology and Informatics, 100-104, July 2017

2017

Koloutsou et al., 2017. Speech audiometry test with picture-related sentence lists in Modern Greek for partially hearing children, Journal of Hearing, Balance and Communication, doi: 10.1080/21695717.2017.1389176, Oct 2017

2017

Fysarakis K. (ed.), 2017. Slicing / Virtualisation and Strong Isolation, in “5G-PPP Phase 1 Security Landscape White Paper”, 5G-PPP Security Working Group, June 2017

2016

Exarchos et al., 2016. Multiparametric data analysis for diagnostic decision support in balance disorders, IEEE International Conference on Biomedical and Health Informatics (BHI), USA, 2016

2016

Anisetti et al., 2016. Security Certification for the Cloud: The CUMULUS approach, In Guide to Security Assurance for Cloud Computing, (eds) Zhu S.Y., Hill R., Trovatti M., Computer Communications and Networks Series, Springer International Publishing, ISBN: 978-3-319-25986-4, DOI: 10.1007/978-3-319-25988-8, 2016

2016

Exarchos et al., 2016. Mining Balance Disorders’ data for the development of Diagnostic Decision Support Systems, Computers in Biology and Medicine, Vol 77(1): 240 – 248, October 2016