Predictive computing is a relatively new area of research. Predictive computing helps people to predict the future or unknown events. It combines various statistical approaches like predictive analytics, predictive modeling, data mining, big data, and machine learning. Predictive computing uses current and historical facts to predict future events. It looks for relationships and patterns between data variables. The outcomes of data variables can be predicted if we know the values of explanatory variables. Cloud computing is another new technology that provides everything-as-a-service (XaaS) and is used widely in various businesses. All storage and computing devices use cloud platform due to its elasticity, scalability, and dynamicity. Cloud-based predictive computing is a technology that uses data available on the cloud. Presently, the data from the social sites (e.g., Facebook, Gmail, LinkedIn, election data, etc.) are stored on cloud, and the volume of this data is enormous which needs innovative predictive computing design and architecture. This chapter represents the cloud-based predictive intelligence and its security model. Architecture for predictive intelligence is proposed and compared with the existing models. An attack prediction algorithm is also proposed and compared for the accuracy in the predictive intelligence.
Consistently Evolving Times
Internet has changed computing in a radical way from its initial days to the present day. Cloud computing has emerged in leaps and bounds since the dawn of internet in the past decade. A large number of facilities of prevalent computing are now provided over the internet. These facilities have led to the shifting and evolution of the concept of parallel computing, to grid computing, to distributed computing, and currently to cloud computing. The notion of cloud computing has been around for quite some time, but it is still an emerging field of computer science. It has spread to wide range of facilities provided over internet. Technically, cloud computing may be defined as computing environment where the computing needs of one party can be outsourced to another party via internet. There are many advantages of cloud computing, the most important is that an end user need not to invest in any infrastructure and hence not for installation. Since there is no such infrastructure or installation, no manpower is required to handle or maintain the infrastructure, which leads to a tremendous reduction in cost. Other advantages include: easy management, uninterrupted service, disaster management, green computing to name a few.
Emergence of Predictive Analysis
Predictive analytics, the major market of which cloud-based predictive analytics platform market is a part, is used for making mathematical models – algorithms which could be used for making predictions – by applying a wide variety of mathematical techniques to historical data. When the two approaches of predictive analytics and cloud come together, it leads to the formation of a cloud-based predictive analytics platform. The cloud-based predictive analytics platform allows predictive analytics to be more scalable, more pervasive, and easier to deploy. A cloud-based predictive analytics platform uses the advantages of the cloud to improve the ROI and time to market of the most advanced analytics.
The rise of big data and the focus on data that is more voluminous, which comes in more varieties and arrives more quickly, have led to the growth of the cloud-based predictive analytics platform market. For the cloud-based predictive analytics platform market the shift was seen when the focus of many companies changed from buying and installing on-premise hardware to buying cloud-based services, and expanding to new cloud-based predictive analytics platforms, has been the recent trend, globally, for the IT solutions market. This has not only led to the growth of the predictive analytics market but also the growth of the cloud-based predictive analytics platform market.