Unveiling the Top 5 Cloud Security Trends from 2024

Does anyone not use the cloud? Depending on whom you ask, somewhere between 94% and 98% of companies worldwide have adopted cloud computing in some form. This might mean storing data in the cloud, using cloud-based software-as-a-service (SaaS) for email, or leveraging sophisticated cloud architectures for enterprise computing. The cloud computing industry is on track to reach half a trillion dollars by 2028. Security is a major worry, however, with a survey from Check Point revealing that 94% of organizations are moderately to extremely concerned about cloud security.

These concerns are understandable. Public cloud providers like Microsoft and Amazon Web Services (AWS) maintain superb security for their infrastructure and networks. However, you, the customer, are responsible for securing your actual cloud environment assets. This shared responsibility model can make security a challenging proposition, especially in recent years. Users can spin up cloud instances without others being aware of what they’ve done, for example, putting corporate data at risk.

For these reasons, security leaders are eager to implement solutions and reap the benefits of cloud security. This article explores the issue. Continuing on the top of cyber resilience we’ve covered previously, it shares five of the top cloud security trends that influence thinking and decisions by security managers and their partners in IT and compliance.

What were the top 5 cloud security trends of 2024?

The top cloud security trends include the adoption of zero trust architecture, the integration of artificial intelligence (AI) into threat detection, the expansion of the secure access service edge (SASE), a focus on data privacy, and an increase in cloud-native application protections.

These different modes of robust cloud security protect cloud assets from unauthorized access and improper use. Mostly, though, they’re about cloud data protection. The cloud is increasingly home to valuable, sensitive data. Protecting that data from breach, corruption, and exfiltration is one of the main objectives of cloud security policies and countermeasures.

1. Adoption of Zero trust architecture

The first cloud security trend we'll explore is zero trust architecture. Zero trust architectures (ZTAs) are growing in popularity in the cloud, as well as in on-premises environments. Entire books have been written on the topic, but briefly, zero trust is a security model based on the idea of "Never trust, always verify." It takes the principle of "least privilege" to its logical extreme. Each user starts with no access privileges at all, eliminating potential trust issues. Only after verifying the user’s identity—often by authenticating his or her device—the zero trust architecture grants the absolute minimum access to legitimate users and proceeds to re-check the user’s identity and access privileges as his session continues.

Done right, a ZTA can deliver a range of security benefits. By restricting access to cloud assets, the ZTA reduces the security risk posed by malicious actors and insider threats. Your cloud security posture should improve with this proactive approach.

ZTA also makes it possible to evolve from perimeter-based security to a more data-centric approach. If you can grant access privileges to specific data sets rather than letting users into the network, where they can access all data, your data security will improve. This can be challenging to administer, however. You have to know who can access what, and that information is not always easy to come by or keep current.

Cloud ZTAs can also present some integration challenges. For example, making ZTA work in the cloud involves extending your identity and access management (IAM) solution across all of your cloud assets. This takes work, and you have to keep the configurations and identities up to date.

2. Integration of AI and ML in threat detection

Next up on our list of cloud security trends in the integration of AI and ML in threat detection. Cloud security solutions are embedding artificial intelligence (AI) and machine learning (ML) in their functionality, particularly for threat detection. These technologies are separate but connected. Again, these are vast subjects, but to keep things simple, AI software detects cyber threats mostly through pattern recognition. An AI-based threat detection solution can ingest massive amounts of data about network traffic, login attempts, user behavior, and so forth, and discern anomalies and patterns that suggest the presence of an emerging threat. ML keeps “training” the AI to get better at the process.

AI and ML benefit cloud security by endowing it with superhuman intelligence. A person could never review the amount of data and discover subtle evidence of threats the way an AI-based system can. And, AI typically makes it possible to detect cloud threats in real time, minimizing routine tasks through enhanced analytical capabilities. This enables rapid incident response processes, such as those performed by security orchestration, automation and response (SOAR) solutions.

AI can also facilitate behavior-based authentication, which can be part of ZTA. Behavior-based authentication uses AI to look at a number of data points related to a user’s behavior, such as device location, time of day, access requests, even device movement and other nuances of user behavior, and decide if a user is legitimate or a malicious actor, thus reducing the risk of unauthorized access. This approach is useful for cloud security because traditional authentication factors like device ID and even biometrics are less meaningful when anyone can access a cloud resource on any device from any location. Behavior is often the only way to be sure of who is who.

AI/ML-driven cloud security solutions come with their challenges, though. As experienced security professionals know, not every threat results in an anomaly, and not all anomalies are from threats. Tuning and training are thus critical for success. Otherwise, the solution can generate a flood of false positives that swamp security analysts. Or, it can miss a potential threat because it doesn’t see a meaningful pattern. Remember, the attackers are aware of AI, too, and they’re honing their skills to avoid creating anomalies.

3. Expansion of secure access service edge (SASE)

Our next cloud security trend is the expansion of secure access service edge, or SASE. SASE is a security framework, rather than a product. It’s a multi-element construct that combines a software-defined wide area network (SD-WAN) with zero trust, a secure web gateway (SWG), cloud access security broker (CASB), and firewall-as-a-service (FWaaS). One of the primary goals of SASE is to enable secure access to cloud resources from anywhere on any device—without traffic passing through a corporate network/data center and getting back-hauled to the end user. This is inefficient, costly, and poor for performance. When implemented correctly, SASE makes possible a secure, seamless, and high-performing user experience for the cloud.

SASE is not easy, however. A quick look at its five core elements suggests that SASEs are integration-heavy and require a commitment to supporting multiple solutions over time. It’s a lot to manage. Scaling SASE can be tricky, too. And, the process of assembling the CASB, SWG, and FWaaS can itself create security gaps through accidental misconfigurations or other unintended expansions of the attack surface.

4. Emphasis on enhanced data privacy regulations

Cloud security managers are emphasizing regulatory compliance with data privacy regulations. This is not a new area of cloud security work, but the number of regulations is growing, especially in the United States. Unlike the European Union, which has the General Data Protection Regulation (GDPR) covering all 27 member states in the EU, the US has no federal data privacy law. Instead, individual states are passing their own laws, such as California’s CCPA, Montana’s Consumer Privacy Act, and Florida’s Digital Bill of Rights.

These regulations put pressure on privacy managers and security teams to protect consumer data from breach. Penalties and other liabilities loom for companies that allow private data to be exfiltrated by attackers. The consumers themselves, referred to as “data subjects,” have distinct rights, too, such as the “right to be forgotten,” which forces companies to delete their data and prove that they have done so. The cloud, with its effortless replication capabilities, can make it challenging to comply with data subject rights. It’s easy to forget that you copied someone’s data to another volume.

Additionally, some European countries mandate “data sovereignty.” For instance, data about German citizens may not be stored in France. Without the right cloud data management tools, you can easily violate this rule and be subject to penalties.

5. Increase in cloud-native application protections

The final cloud security trend on our list is an increase in cloud-native application security protections. Cloud security managers are increasing their use of cloud-native application protection platforms (CNAPPs) that leverage threat intelligence. These platforms combine multiple cloud security tools into a single, cloud-hosted solution. For example, a CNAPP might perform vulnerability management, data security posture management, Kubernetes security, and more. They break down siloes and reduce the work of managing multiple cloud security solutions.

CNAPPs are helpful for developing cloud software, too. Kubernetes management, for instance, helps realize container security, which is important given the prevalence of containers in cloud applications. If the CNAPP provides continuous integration/continuous delivery (CI/CD) for software code, they make it easier to “shift left” and include security steps earlier in the cloud software development cycle. Secure coding practices can further bolster the security of cloud-native software code, e.g., validating inputs to prevent code injection attacks.