Much before the recent events made the rapid transition to remote work necessary for many organizations, cloud usage was on the rise. As per studies, more than 85 percent of companies have used at least some public cloud services, and nearly 40 percent have described themselves as “cloud-first” in their strategic approach to choosing computing resources. The figures today are likely to be even higher, with substantial growth shown by the most recent earnings results of all major cloud providers.
They are, of course, moving growing amounts of their confidential data to the cloud as companies invest in cloud technologies and services. Nearly one-quarter of enterprises keep more than 40 percent of their information in public cloud stores, while more than 75 percent store sensitive data on multiple public cloud providers’ infrastructure-as-a-service (IaaS) systems or software-as-a-service (SaaS) applications.
As more data moves to the cloud, security teams are challenged to protect increasingly complicated, distributed hybrid environments, and staff is required to operate on any device from anywhere at any time. For the requirements of the present reality, conventional perimeter-based and network-centric security delivery models are no longer adequate. Instead, we need cloud-powered security, which adopts a human-centric approach.
Protecting multi-cloud environments requires new ways of thinking. Here are some of the top tactics for meeting the challenges.
1: Concentrate on your data in the cloud applications.
Security teams tend to claim that in the early stages of the introduction of SaaS applications, these cloud-hosted apps can still be accessed via the enterprise’s on-site networking infrastructure. Security monitoring focuses on objects such as routers, firewalls, or network traffic in order to capture anomalous file movements or incidents within the perimeters of the corporate network.
Major among the problems with this approach is that it prevents businesses from realizing the full potential of SaaS business solutions. Employees may increase their productivity as they can use personal devices such as handheld devices (BYOD) to access these cloud-hosted services regardless of where they are while traveling or working from home and via in-office hardware.
Data protection needs to secure the data for cloud applications irrespective of how and where it is accessed. It is critical that the app itself is secured by security solutions so that security teams, particularly when it occurs on unmanaged devices, will have significant insight into the potentially hazardous usage of both allowed and unapproved cloud applications. For data stored in enterprise cloud applications, a DLP solution that includes cloud app coverage will allow your team to follow the same policies that you would apply on-site and in-network. It can also extend the same data discovery features to your cloud-hosted technology solutions.
2: Enforce cohesive strategies across the whole ecosystem.
Far too many organizations also have separate protection teams for data stored in the cloud and data stored on-site. Unfortunately, this is one field in which organizational silos are a recipe for disaster. Teams would need to spend a great deal of effort and time reconciling them if you set separate policies for cloud data and on-site data. The method would have to be repeated over and over again with every change in the environment. Usually, such changes take place at least every day.
Look for a DLP solution that can apply unified policies to all data at rest, in motion, or in use, whether inside cloud apps or those running in on-premise data centers. This simplifies the compliance standards enforcement process and decreases the risk of enduring a debilitating breach.
3: Strive to integrate dynamic risk-based policies.
Environments are inherently complex and diverse for multi-cloud computing. Data leakage can potentially occur inside them in a near-infinite variety of circumstances. You can customize individualized and adaptive policies for various levels of risk, which can be described based on behavior and adjusted in line with how users act and interact with data. This dynamic data protection strategy enables security to be frictionless.
