What Makes a SIEM “Next-Gen”?

Security information and event management (SIEM) is the bedrock of any successful security organization. In the last couple of years, there have been rumors that SIEM is dead, but that is not the case.

According to the Gartner® Hype Cycle™️ for Security Operations, 2024, SIEM is placed in the Plateau of Productivity phase on the Hype Cycle for Security Operations.* “Gartner Hype Cycles provide a graphic representation of the maturity and adoption of technologies and applications, and how they are potentially relevant to solving real business problems and exploiting new opportunities.”**

The Plateau of Productivity is described as: “Mainstream adoption starts to take off. Criteria for assessing provider viability are more clearly defined. The technology’s broad market applicability and relevance are clearly paying off.”**

Simply put, in our view, SIEM is not dead, it is a relevant and needed security solution for any organization.

But with cloud adoption continually increasing, adversaries utilizing advanced technologies to infiltrate organizations, and a dispersed workforce, companies must monitor infrastructure, applications, and data across multiple cloud environments. This is where Next-Gen SIEM comes into play. Next-Gen SIEM enables visibility across the entire IT environment and increases efficiency in detecting and responding to both known and unknown threats.

Next-Gen SIEM takes a proactive approach to threat detection, investigation, and response by implementing advanced technologies and analytics to improve detection capabilities to uncover both known and unknown threats.

Highly scalable, Next-Gen SIEM can handle large amounts of data across distributed architectures, including on-premises, in the cloud, and hybrid environments. Utilizing artificial intelligence (AI) and machine learning (ML), Next-Gen SIEM collects, normalizes, and analyzes large datasets across the IT environment to surface anomalies and trends. It detects known and unknown threats without relying solely on predefined rules and enables quicker response time with automatic correlation and contextual insight.

Next-Gen vs. Traditional SIEM Solutions

Traditional SIEM collects, stores, and analyzes log data across an IT environment. It helps businesses detect and respond to potential threats with real-time monitoring and analysis and helps organizations adhere to compliance mandates. It is often limited in scale, cannot handle distributed architectures across multiple clouds, and relies on manually created and fine-tuned rules-based detections of known threats.

Unlike traditional SIEM, Next-Gen SIEM is a cloud-native solution that collects, stores, and analyzes data across a borderless infrastructure. It uses AI to analyze data to surface unknown and sophisticated threats by establishing baselines and determining anomalies and trends. Next-Gen SIEM helps businesses take a more proactive approach to threat detection, investigation, and response by reducing alert fatigue while highlighting greater contextual insight into unknown threats.

	Next-Gen SIEM	Traditional SIEM
Data	Ingests from diverse data sets, including public and private cloud, including AWS, GCP, and Microsoft Azure	Collects log data across various systems and applications within an organization’s network
Analytics	Utilizes AI and ML to create a baseline across data sources and then surfaces anomalies and trends	Manual rules-based log collection and correlation
Detections	Utilizes AI and ML to detect both known and unknown threats; lower volume of alerts/alarms	Detects known threats utilizing predefined rules that need constant fine-tuning; high volume of alerts/alarms
Threats	Proactively predicts and prevents both known and unknown threats; usually includes global threat intelligence feeds	Reacts to known threats based on pre-defined rules
Incident response	Fast, with actionable contextual insight and correlation	Slow, manual correlation required

AI/ML: Detects unusual behavior in real time by creating a baseline of normal activity. By automatically scoring each event, it proactively determines whether an event is a threat that needs to be investigated.
Data collection and storage: Seamless data collection across distributed environments, including SaaS applications and cloud platforms like AWS, GCP, and Microsoft Azure. Ability to store large datasets for analysts to continuously perform search queries during threat investigations.
Scalability: Cloud-based architecture with open APIs that can easily adjust computing resources to meet changing demands and seamlessly integrate with other security solutions.
User entity and behavior analytics (UEBA): Uses ML to analyze the behaviors of users, routers, servers, and endpoints in a network to determine irregularities in normal behavior instead of relying on known signatures or predetermined rules.
Automated response: Automatically compiles contextual insight into an event that needs to be investigated and generates a playbook of actions that equips analysts with the necessary actions to quickly remediate suspicious events.

Benefits of Next-Gen SIEM

Next-Gen SIEM provides improved security posture through:

Flexible scalability
Comprehensive visibility
Increased analyst efficiency
Quicker response times

Anomali’s Approach to Next-Gen SIEM

SIEM is a critical component of modern cybersecurity strategies, providing centralized monitoring, real-time threat detection, and incident response capabilities. Anomali’s Security Analytics is a Next-Gen SIEM that combines a Security Data Lake architecture with AI-driven behavior analytics and natural language processing (NLP) to immediately surface contextual insight and enable quicker response to known and unknown threats with:

Flexible scalability: Anomali’s own scalable Security Data Lake enables organizations to collect, search, and store petabytes of data at a fraction of the cost of other solutions while easily integrating with other security products with an open API architecture
Comprehensive visibility: Anomali Security Analytics helps organizations quickly gain access to all security telemetry across the IT environment including SaaS and cloud environments
Increased analyst efficiency: Anomali Security Analytics' multi-layered automated threat detection system reduces alert fatigue by utilizing AI-driven behavior analytics into both known and unknown threats. Uplevel analyst skills with NLP search and analysis that delivers >140 billion records in < 45 seconds
Quicker response times: AI-driven behavioral analytics prioritizes, accelerates, and automates responses with precision-based attacker insights and breach context. Alert prioritization identifies which incidents need immediate attention.

Anomali’s AI-Powered Security Operations Platform further strengthens an organization’s security posture by integrating the core functionalities of SIEM, TIPs, SOAR, and UEBA into a single easy-to-use platform that enhances the effectiveness of security operations, improves threat detection, decreases response times, and simplifies compliance with regulatory requirements.

Schedule a demo to learn howAnomali Security Analytics can help your organization.

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* Gartner Hype Cycle for Security Operations 2024, Jonathan Nunez, Andrew Davies, 29 July 2024

** Gartner Methodology, Hype Cycle, https://www.gartner.com/en/research/methodologies/gartner-hype-cycle

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