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Cloud Data Protection: What You Need to Know
It’s no surprise that cloud adoption continues to be a major force impacting organizations today. A 2020 McKinsey survey indicated that many organizations saw several years worth of digital transformation take place in 2020. An IDG survey, which we referenced in our Securing Best of Breed SaaS Applications webinar, suggested that 95% of organizations expect to be partly or fully in the cloud by the end of 2021, with almost half the applications used by their workforce being SaaS or open source. With rapid and dramatic cloud adoption, however, comes a variety of security challenges that can only be addressed with cloud data protection. In this post, we’re going to highlight the defining features of cloud data protection and illustrate why it’s so invaluable to security teams today.
What is cloud data protection?
As the name implies, cloud data protection refers to techniques and technologies that center around protecting data at rest and in transit within the cloud. The reason that data protection is so pivotal is that unlike traditional IT environments, cloud systems have no perimeter in the traditional sense. Historically, security revolved around keeping intruders out and hardening systems explicitly owned by an organization. However, the entire point of cloud adoption is to enable data to be wherever it needs to in order to be useful. As such, data itself is best thought of as part of your organization’s attack surface — the more data you have, the bigger your exfiltration risk.
By 2025 the amount of data stored in the cloud by governments, organizations, and individuals will reach 100 Zettabytes (an estimated 50% of the world’s 200 zettabytes of data at that time) which means that for many organizations their attack surface is expanding whether they realize it or not. This risk stems in part from core attributes that define how cloud systems, especially SaaS systems, are meant to work, which we highlight in the video excerpt below.
How does cloud data protection work?
Cloud data protection solutions, like cloud-native data loss prevention, focus on enabling security teams in two key ways:
- They provide visibility into cloud systems. Because the velocity of data entering and moving through cloud environments scales with the amount of users and devices using these systems, it can be hard at any given moment to know how much sensitive data lives in the cloud and where exactly it is, even within sanctioned apps. Without a solution to provide a detailed view, ideally across all of your cloud systems, you’ll have trouble understanding your risk and knowing where your data is.
- They allow teams to take action. Good cloud data protection solutions don’t just let you see risk, but they let you take action too. They’re “smart” enough to avoid alert fatigue and let you standardize and automate the appropriate responses to data policy violations. For example, the Nightfall DLP platform uses machine learning to immediately identify when a file contains PII or secrets and credentials, and lets you automatically redact messages containing such files in applications like Slack.
Why is cloud data protection so important?
Why do modern organizations need cloud data protection? There are several reasons, each just as important to consider.
1. The risks and cost of exposures tends to be higher in the cloud
As we discussed above, data is growing rapidly in the cloud and many organizations don’t have the best handle on the data proliferating within cloud silos. The end result is that basic policy violations have the potential to expose a massive amount of records. We discussed this very issue in an article recently published in ITProPortal. In that post, we revealed that just five cloud data leaks in 2020 exposed nearly 27 billion records. The data was derived from our 16 year breach report published earlier this year. In the report, we illustrated that misconfigurations in cloud systems, especially those like AWS S3 and Elasticsearch, can result in disproportionately higher numbers of exposures because of the volumes of data stored in these systems.
SaaS systems aren’t exempt from this risk either. Systems like GitHub can contain secrets that can be used to access other systems and collaborative tools like Google Drive, Jira, and Confluence may have files that are exposed publicly due to permissions misconfigurations. The commonality with all cloud exposures is that they can go on indefinitely until an organization is notified by an altruistic third party, or until they acquire the tools that let them see any data exposures.
2. Security and IT teams are stretched thin
It’s no secret that the cybersecurity industry is currently undergoing a skills shortage and that, at the same time, the costs of breaches are rising. This leaves security professionals in the hard spot of triaging risk, possibly leaving gaps in some organizations’ security programs. Having a solution that can intelligently automate security tasks and only alert on events that are critical. Such tools are doubtlessly invaluable.
3. It’s very difficult to consistently enforce proper data policies in the cloud
One of the key problems organizations face regarding security and compliance is ensuring that employees are aware of best practices and verifying that they’re following these guidelines. Without sufficient visibility into cloud systems, this can be very difficult to do for the reasons we’ve highlighted above.
The shared responsibility model, best articulated by AWS, requires organizations to understand their risks and have the ability needed to address them. Organizations should begin this work by identifying and mapping critical cloud security areas to processes and solutions that are relevant. Ty Sbano, Sisense’s Chief Security & Trust Officer, briefly illustrates how resources like CIS’s representation of the shared security model could be used to help with this process in the segment below.
What’s the ROI of Cloud Data Protection?
Ultimately, cloud data protection can provide a lot of value to organizations if they look for solutions with the right attributes. Solutions that simplify both security and are minimally invasive to the employee experience. We wrote a detailed guide breaking down the ROI of cloud data protection, which you can download here.
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Nightfall is the industry’s first cloud-native DLP platform that discovers, classifies, and protects data via machine learning. Nightfall is designed to work with popular SaaS applications like Slack, Google Drive, GitHub, Confluence, Jira, and many more via our Developer Platform. You can schedule a demo with us below to see the Nightfall platform in action.
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