HDFT++ Hybrid Data Flow Tracking for SaaS Cloud Services

2017 ◽  
Author(s):  
Alexander Fromm ◽  
Vladislav Stepa
Keyword(s):  
Data Flow ◽  
Cloud Services ◽  
Hybrid Data ◽  
Data Flow Tracking ◽  
Saas Cloud

Sound and Precise Cross-Layer Data Flow Tracking

2016 ◽  
pp. 38-55 ◽  
Author(s):  
Enrico Lovat ◽  
Martín Ochoa ◽  
Alexander Pretschner
Keyword(s):  
Data Flow ◽  
Cross Layer ◽  
Data Flow Tracking

Base Address Recognition with Data Flow Tracking for Injection Attack Detection

2006 ◽  
Author(s):  
Satoshi Katsunuma ◽  
Hiroyuki Kurita ◽  
Ryota Shioya ◽  
Kazuto Shimizu ◽  
Hidetsugu Irie ◽  
...  
Keyword(s):  
Data Flow ◽  
Attack Detection ◽  
Base Address ◽  
Data Flow Tracking ◽  
Address Recognition

Data flow tracking-based block chain modelling

2019 ◽  
Vol 18 (4) ◽  
pp. 323
Author(s):  
Yu Tian ◽  
Wenxiu Hu ◽  
Ganglong Duan
Keyword(s):  
Data Flow ◽  
Block Chain ◽  
Data Flow Tracking

CLOUDSME

2021 ◽  
pp. 442-459
Author(s):  
Richard Otuka
Keyword(s):  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Adoption Process ◽  
Semantic Model ◽  
Service Adoption ◽  
Cloud Service Providers ◽  
Saas Cloud ◽  
Service Attribute

Presently, SMEs are finding it difficult to adopt cloud services for their businesses due to various service providers offering similar services. In addition, little work has been carried out in regards to the cloud services adoption process by SMEs. In this chapter, the authors propose CLOUDSME, a novel framework that aids in the adoption process of SaaS cloud services. Accordingly, they implement a decision support system, which includes an ontology of cloud services knowledge within the proposed framework. Analytical hierarchical process (AHP) is used to determine the weight of each cloud service attribute, and a benchmark is set to determine the acceptability of each cloud service based on its ability to meet the acceptable benchmark for each criteria. It can also help in a healthy competition to improve the quality of service among cloud service providers. The CLOUDSME semantic model will guide SME owners in answering user requirements towards decision making in the cloud service adoption process.

Pharmaceutical Companies SaaS Cloud Services Management Platform Based Design and Application

2014 ◽  
Vol 1030-1032 ◽  
pp. 1913-1918
Author(s):  
Qi Zhi Chang ◽  
Zhang You Hu ◽  
Xiao Hui Weng ◽  
Li Ding
Keyword(s):  
High Efficiency ◽  
Cloud Services ◽  
Jilin Province ◽  
Pharmaceutical Companies ◽  
Management Platform ◽  
Modern Enterprise ◽  
Pharmaceutical Enterprise ◽  
Low Costs ◽  
Saas Cloud ◽  
Design And Application

Summery: The pharmaceutical enterprise SaaS is based on the cloud services, the management platform follows the newest GMP criterion and ERP project matchmaking of modern enterprise. In carrying through it, high efficiency, low costs, simplified management, easy maintain, all these achieve idea of platform SaaS. The scope of implementation is based on the related pharmaceutical enterprise in Jilin province.

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