Cloud's popularity among SMEs fuels demand for identity-as-a-service
The rising adoption of cloud computing, especially among small and medium organizations, is fueling demand for new business models such as Identity as a Service (IDaaS) within the identity and access management (IAM) space. IDaaS will strike a balance between on-premise and cloud identity management, as well as significantly lower the cost of ownership of IAM solutions.
A Frost & Sullivan analysis titled, Technologies Empowering Future of Identify Management, finds that IAM challenges are more business-centric than technology-centric. Segments such as administration, authentication and auditing are developing technologies to improve service accuracy and cost efficiency.
Emerging services like Platform-as-a-Service (PaaS) and Infrastructure-as-a-Service (IaaS) are contributing heavily to the growth of IAM technologies.
"The shifting of enterprise solutions to the cloud has created a complex architecture that requires more advanced IAM solutions than the ones currently offered by traditional identity management vendors," noted Frost & Sullivan TechVision Industry Analyst Swapnadeep Nayak. "The emergence of IDaaS has proven beneficial to enterprises, as it will assist with regulatory compliance, reduce the expenses involved in extending on-premise solutions to the cloud, and support the same features as enterprises' legacy systems."
As most of the recent IT trends have been mobile centric, IAM solution providers need to ensure their innovations are mobile friendly to attract the attention of enterprises. Supporting cross-platform visualization and advanced analytics, as well as portable biometric technology, will give a huge boost to technology adoption rates.
"Biometric authentication is a key area that is experiencing significant technology development, especially with regard to accuracy levels of validation and flexibility of usage," noted Nayak. "Analytics is also growing rapidly due to the emergence of futuristic solutions like neural networks and machine learning."