Access management and Data path prediction for securing cloud-based services and enhancing cybersecurity solutions

Next decade will evidence the emergence of a new dawn of communications, where the machines communicate to each other without or with minimal human intervention. The existences cellular and ad-hoc networks infrastructure and recent advanced LTE technology encourage researchers to exploit to build a coexist communication between human to human (H2H) and machine to machine (M2M). The purpose of this research is that a cloud platform schema by adopting getaway (Access Point) as a mediator to separate between M2M and H2H communication to alleviate the traffic congestion and random access on cellular networks is introduced. As a method, the proposed model composes three stages: initialization stage, where machines register to the system and gain unique identifier. Classification stage, in this stage the mediator getaway classifies the data type and work to separate H2H communication and MTC. Finally, in the third stage, based on stage classification decision will take either to store those date into the cloud or give high priority to send those data to the cellular network. Early results allow us to show the performance of the data path prediction through this proposed research in which the decision then will be based upon predefine QoS and priority or emergency cases. Our novel proposed cloud platform can preserve high throughput and low latency. Obviously, traffic congestion has been mitigated. Low hit ratio to LTE network has also been achieved.