Cloud SIEM: A Blueprint for Proactive Monitoring & Response
When a data breach occurs, time is an invaluable asset. The longer an intruder goes undetected, the more damage they can do. But the faster an organization discovers an incident, the sooner the threat can be neutralized.
A cloud security information and event management (SIEM) solution serves as an early warning system that gives companies the ability to recognize and respond to potential security threats faster. The cloud SIEM continually monitors security-relevant data from numerous source systems and seeks out indicators that a threat may be present. This guide explores the role a cloud SIEM plays in a modern data security strategy and the technologies shaping the future of advanced detection and response systems.
How Does a Cloud SIEM Work?
Today’s businesses operate in a complex network of hybrid and multi-cloud environments. Still, although modern cloud architectures offer many benefits, they also make it more difficult to monitor data, detect potential threats, and respond to security incidents. Security-related data now resides in multiple platforms and systems.
By collecting and analyzing data from all relevant sources, including security logs and contextual data gathered from servers and applications, the cloud SIEM empowers security teams to quickly recognize and respond to potential threats. A cloud SIEM provides a comprehensive view of data across an organization and uses machine learning and advanced analytics techniques to detect potential threats in real time.
Why Choose a Cloud SIEM
Cloud SIEMs offer numerous advantages, especially when compared to on-premises SIEMs. Here are five reasons today’s organizations are moving to a cloud SIEM as a cloud data security best practice.
Ease of Deployment and Use
Cloud SIEMs can be deployed quickly since they don’t require physical infrastructure. Additionally, because they’re cloud-based, maintenance and upgrades are typically handled by the cloud SIEM provider. Today’s cloud SIEMs feature user-friendly interfaces that are easy to configure and use with minimal technical expertise.
As a general rule, cloud SIEMs are more affordable than on-premises systems. With no hardware to purchase and maintain, and little to no involvement with updates, the cost of ownership is typically much lower than systems that rely on on-premises components.
When a business grows, the volume of security-related data that it produces grows along with it. Cloud SIEMs are not constrained by physical storage and compute infrastructure. As a result, they can scale organically with the business and easily accommodate spikes in demand.
A cloud SIEM solution can significantly reduce the resources required to manage compliance auditing and reporting, giving business leaders fast access to compliance-related information whenever it’s needed.
Faster Threat Detection and Response
Cloud SIEMs offer real-time threat detection and response with minimal traffic overhead, and improved processing speeds. As security data is ingested, it can be immediately analyzed with no resource contention.
Cloud SIEM Data Sources
Cloud SIEMs are only as effective as the data sources they analyze. These five data sources are commonly used to optimize a SIEM’s threat identification and response capabilities.
Network Traffic Data
Cloud SIEMs collect and analyze traffic data across an organization’s entire network. This information includes logs and flow data from individual users across on-premises and cloud applications, environments, and networks, making threat detection and insider risk management easier.
Cloud SIEMs play an important role in identifying network vulnerabilities and potential points of entry. Ingesting data from endpoints, including cloud-based virtual machines and containers, can help identify suspicious activity like malware infections or unauthorized software installations.
Threat Intelligence Data
Some cloud SIEMs automatically integrate threat intelligence, including data from both open-source feeds and commercial threat intelligence services. These feeds include data from the Department of Homeland Security, the Consensus Incidents Database, and the National Council of ISACs. For public sector data security, this is highly beneficial for enabling fast analytics and action on intelligence data.
User Activity Data
User and identity data is used to identify and flag anomalies such as logins from unusual locations and multiple failed login attempts. Organizations using a data security platform can feed data gathered from the platform into the SIEM, including data generated from the continuous monitoring of changes in user behavior and entitlements, and updates to security configurations and data classifications.
Cloud Service Logs
Real-time cloud service logs provide information about events and changes in the cloud environment. Additionally, organizations can integrate data monitoring and detection capabilities, enabling detailed analysis of individual user and data activity, data access events categorization, sensitive data indicators, and other security-relevant details on how data is being accessed and used. This tracking helps security teams proactively detect anomalies, providing an opportunity to address them before they grow into something more serious. Joining data monitoring and auditing capabilities with a cloud SIEM ensures suspicious patterns of use or other irregularities can be spotted quickly, strengthening the organization’s overall data security posture management.
Modern Security Data Lakes
As the volume of security-related data continues to grow, the resources required to keep pace can quickly outstrip the capabilities of a cloud SIEM. Security data lakes are enabling organizations to take cloud SIEM systems to the next level. A security data lake can store and analyze massive volumes of diverse data types, enabling teams to collect and analyze data from both traditional sources, such as logs and network traffic, as well as contextual business data, without constraint.
Cost-Effectively Integrate All Security-Relevant Data in Native Formats
Unlike SIEM solutions, a security data lake acts as a repository for all unstructured, semi-structured, and structured data, making it possible to store data in its native formats. With near-instant access to a massive amount of security-relevant data, teams can optimize activities such as threat hunting and incident investigations. Freed from the need to store data in predefined fields, organizations can collect and store more security-relevant data at scale, including user behavior analytics, proprietary threat feeds, open-source intelligence (OSINT), data monitoring, and contextual data from across the business.
Improved Threat Detection
With enriched data instantly available for use, security teams can more efficiently investigate attacks, perform post-incident forensics, and conduct threat hunting operations. The modern security data lake broadens and deepens the context surrounding potential security events, enhancing the effectiveness of threat detection and mitigation efforts.
It’s important to note that SIEM systems have features that aren’t found in security data lakes, including built-in alerts, dashboards, and ticketing. Many SIEM solutions now integrate with security data lakes so organizations can benefit from both.
Cloud SIEMs and What Comes Next for Cloud Security
Cloud SIEMs have emerged as a powerful tool for organizations seeking to improve their security posture and protect their assets from cyber threats. As a result, many cloud data security platforms now integrate a SIEM as a built-in functionality.
As organizations move more fully to the cloud and their infrastructure becomes more complex, the security data lake is emerging as a more robust solution for keeping up with the needs of modern security data management. A strong data security platform enables customers to take advantage of the features offered by a SIEM system while benefiting from the capabilities of a modern security data lake.
To learn recommended security strategies and tactics based on your organization’s processes, business needs, and technical capabilities, read Best Practices for Securing Sensitive Data.