With cybersecurity making the headlines for all the negative reasons, there seemed to be more thefts and breaches involving digital identity than ever before, leaving trusted technologies to generate negative headlines.
FREMONT, CA: Security identity access is deemed to be everywhere, but with the help of modern technologies, there is supposed to be a more positive narrative to creating and managing an immutable digital identity. New authentication technologies and trends that continuously protect pre-, during, and post-authorization, while leveraging individual behaviors securely and privately will become mainstream, leaving the cybercriminals in the dust. Thus organizations should consider evaluating their identity and access management (IAM) capabilities to identify and then close the risks that could lead to a breach of sensitive data.
Here are three trends to look up to, which can be leveraged to reduce risks around identities and data in the cloud.
IAM and Single Sign-On (SSO)
While it is common for companies to use single sign-on (SSO) solutions to provide access to public cloud platforms and resources, the focal-point has typically been on administrative users. Companies are also providing cloud access to non-people identities such as applications, services, and other compute resources.
While it has forever been essential for organizations to have a governance model for developing their IAM frameworks, in this new paradigm, organizations must have a deep understanding of what access to data is possible, coupled with an enhanced ability to monitor and analyze the ongoing access. Leveraging IAM analytics will offer better visibility into how access to data is used once granted and helps to discover unused privileges as well as identifies the previously unknown risks of over-permissioned identities, misconfigurations, and deviations from the governance models.
Behavioral analysis of IAM access patterns is yet another powerful method which can bring policy violations to the surface. Artificial Intelligence (AI) and Machine Learning (ML), mainly, are highly being used to alert on a wide range of changes in user and application behavior. These changes can include the location of the API call, the API client, or the kinds of permissions.
While AI and ML are not the silver bullets, by any means, but they can certainly help to draw attention to the policy violations and identify attacks before they become breaches.