AI-Driven Compliance: The Key to Cloud Security

By Michael Massimi and Abhijit Chakravorty—-The growth of cloud computing continues unabated, but it has also created security challenges. The acceleration of cloud adoption has created greater complexity, with limited cloud technical expertise available in the market, an explosion in connected and Internet of Things (IoT) devices and a growing need for multi-cloud environments.

When clients migrate to the cloud, there is a high likelihood of data security problems given that many applications are not secure by design. When these applications migrate to cloud-native systems, mistakes in configuration settings can create cybersecurity risks. Delays in implementing the cloud security controls for client workloads occur during migrations, which compounds the issue. That’s why Gartner predicts that by 2025, 99% of cloud breaches will be caused by misconfigurations, most of which will be attributed to human error that could have been prevented.

Cloud security shared responsibility model

Based on the well-established cloud security shared responsibility model, clients and cloud service providers are both responsible for cloud security. The cloud service providers are responsible for the security “of the cloud,” while clients are responsible for security “in the cloud.” However, the extent of clients responsibility depends on the consumption model.

For the most part, the cloud service provider infrastructure is secure. However, there is a possibility of client-side data security issues, including cybersecurity and workload problems. Cloud misconfigurations happen when cloud security settings are not properly configured, creating vulnerabilities that can be leveraged by external hackers using ransomware or insider threat actors exploiting security gaps.

Understand compliance monitoring

As a general rule, clients can benefit from enacting access control by using data encryption and conducting regular audits. They should also establish compliance programs to address ongoing alignment with security controls. Cloud security standards should be implemented to address cloud services needs in meeting those relevant requirements issued by state and federal governments and industry standards. In addition, internal policies should provide critical guardrails for cloud security.

Understanding the cloud security standards for your cloud business estate and what additional protections would benefit your IT environment is critical. The ongoing management of cloud environment protection supports ongoing success. Many clients perform periodic audits of their cloud security compliance posture only to find that misconfigurations have crept in. Human error is typically to blame, so having a continuous controls compliance monitoring solution to attend to applicable cloud security requirements is vital to catch these misconfigurations as they arise in real-time.

Use gen AI to improve cloud security

As the world moves to embrace generative artificial intelligence (gen AI) for various use cases, there is an opportunity to use this emerging technology to improve cybersecurity protections in the cloud. Cloud security standards are a critical component of a client’s cybersecurity protections. Using AI technology to establish, monitor, and manage the cloud security controls within a client’s cloud estate should be designed to protect against human-caused misconfigurations and provide reporting against compliance to cloud security requirements.

There are three main ways to improve cloud security posture by establishing continuous controls monitoring capabilities using gen AI:

Deployment: cloud security standards can be translated by AI to enable seamless deployment of protective and detective cloud security controls, that would lead to improved productivity and compliance to such requirements.

Management: An AI model can be trained to continuously learn about the environment, provide up-to-date changes to the cloud security posture controls and respond quickly to any detected concerns.

Threat Detection: An AI model can also be trained to detect, correlate, and align cloud security standards with threats and automatic and semi-automatic response capabilities for real-time action and analysis.

Point security solutions help manage clients’ posture management for the cloud, and they will continue to be part of a cybersecurity toolbox that clients can utilize. However, static tools do not adapt in real-time. Rather, a continuous controls monitoring solution using gen AI demonstrates being the ideal solution, where client IT environments are compliant with the latest cloud security standards and can adapt to misconfiguration drift as it occurs, automatically correcting for high-risk exposures.

Flexible cyber defense with gen AI

Because a continuous controls monitoring solution is dynamic and self-healing, its capabilities should accelerate the deployment of cloud security controls that align with client policies. It would also improve security operations by providing visibility into cloud assets and activity across multiple cloud providers. Meanwhile, in the event of a security breach, the AI solution would identify threats and accelerate investigations through behavior analytics, data flow and vulnerability analysis.

If used properly, AI can be harnessed to help drive more effective cybersecurity controls, addressing compliance and improving overall cyber risk management and oversight in the cloud.

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