Combine SIEM and AI to Bulk Up Your IT Security

SIEM provides a security solution for threat detection and response, using features such as event correlation, custom detection rules and behavioural analytics for anomaly detection. These functions identify anomalous/suspicious activities, like multiple simultaneous logins or privileged escalation that occur on a single system. SOC teams also use NDR tools to identify anomalous/suspicious network behaviours, like port scanning, lateral movement, data exfiltration or connections to malicious IP addresses. Since most cyberattacks include network communications, NDR is typically used as a first line of defence for threat detection.

SIEMs also use advanced correlation to understand related threat activities. When a combination of advanced analytics and real-time correlation are prebuilt into a SIEM, these can be applied out of the box to network, asset, user and application activity to reach well beyond just known threats and identify anomalous activities that can indicate unknown threats.

An ideal SIEM solution lets you get started with standard use cases, such as threat detection, cloud monitoring and compliance reporting – right out of the box. As your practice matures and your business grows, your SIEM should scale to support more environments, multiple geographies and advanced use cases, such as deep-packet inspection, domain name system (DNS) analytics and tightly integrated security orchestration, automation and response (SOAR).

By combining SIEM with NDR, organizations have the analytics foundation for performing extended detection and response (XDR). When these two security technologies are tightly integrated, organizations can benefit from:

• Improved threat detection. When SIEM analytics, event correlation and rule sets trigger an alert, analysts tend to pivot to NDR tools to look at associated connections or dig into the network packets themselves to look for anomalous files. When SIEM and NDR are integrated, this data can be combined into high-fidelity alerts with all log and network data presented to analysts simultaneously. Leading systems will also include advanced analytics that looks for malicious behaviour across a kill chain that includes log and network data.
  
• Accelerated and streamlined security operations. When SIEM or NDR systems trigger an alert, security analysts begin a time-consuming series of processes including triaging alerts, querying different systems for supporting data and then prioritizing remediation tasks with IT operations. By combining all suspicious network- and system-level data, the combination of SIEM and NDR help organizations streamline and accelerate security operations by presenting suspicious event, network and log data into compact and comprehensive security alerts.

Artificial intelligence (AI) used within security solutions and systems handles repeatable tasks and helps make better and more informed decisions. AI proactively takes external data – information from everywhere – and combines it with a native environment to help organizations understand what their next move ought to be. In all cases, security specialists can decide how much work they want AI to do, whether it’s time-intensive tasks to making routine decisions.  

AI within a SOC provides access to a repository of institutional memory that can offer recommendations designed specifically for an organization. AI allows an organization to balance its security operations and solutions.

Chain together different potential incidents, automatically. AI excels at root-cause analysis automation and integration. AI catches connections for threat and risk insight – and it doesn’t get fatigued. AI shows interrelationships your staff might miss due to turnover, inexperience or the passing of time. Without AI, inexperienced analysts may close out an alert, thinking it was a single instance of an attack. AI finds commonalities across incidents using cognitive reasoning and offers actionable feedback with context – whether the commonalities are from a ticket closed yesterday or months prior. AI gathers external threat intel to add more context to your analysis and catches what others may miss.

Solve your people problem. AI determines root cause analysis and orchestrates next steps based on the knowledge it has built on threats and your organization. It never takes a vacation or leaves your company for another job. And you don’t have to worry about not recognizing a significant indicator of compromise (IOC).

Drive consistent and deeper investigations, every time. AI reads both unstructured and structured data and learns. AI provides the information you need to reduce mean time to detect and mean time to respond (MTTD and MTTR) – with a quicker, more decisive escalation process. AI offers advanced analytics to detect known and unknown threats. AI drives consistent and deeper investigations, every time, and empowers your analysts to make data-driven decisions instead of relying on their gut feeling.

Conduct more thorough and consistent investigations in a fraction of the time. Leveraging AI to perform automatic data mining of threat research/intelligence allows security analysts to conduct more thorough, consistent investigations in a fraction of the time and lets analysts focus on strategic threat investigations and threat hunting. AI correlates threat intelligence to investigations, giving analysts a more comprehensive view.

Focus on the most important alerts first. Alert prioritization helps analysts triage alerts effectively by focusing on the most critical alerts first, uncovering false negatives and false positives and greatly reducing the chances of missing critical incidents.

Leverage MITRE ATT&CK for more effective threat investigations. Mapping the attacker’s actions to the MITRE ATT&CK framework visually depicts a timeline of events showing the progression of a threat, resulting in faster and more accurate threat investigations, which in turn reduces dwell time.

Gain a comprehensive view of the investigation. Cross-investigation analysis reflects a more comprehensive view of the investigation beyond the current offence by identifying and connecting alerts linked to the same attack that, on the surface, may appear to be unrelated, thus reducing the number of alerts and duplication of work.

Have a robust and automated incident response (IR) workflow that spans people, process and technology. AI guides security analysts through a fast, complete response that’s driven by data and evidence. It automates workflow and remediation. It enables SOCs to assess and refine their IR processes, continually.

AI enables your SOC to be better prepared and recover faster – before, during and after a data breach. IBM’s QRadar Security Intelligence Platform takes this technology and integrates it into your SOC to provide an all-encompassing analytics solution – all on a single platform.

Security QRadar SIEM makes it possible to rapidly detect threats and accurately respond before attackers can cause financial or reputational damage to your brand. With more than 700 integrations, 1,500 out-of-the-box use cases and built-in network visibility, QRadar SIEM analyzes every aspect of your environment, finds suspicious activity and facilitates rapid responses. When threat actors trigger multiple detection analytics, move across the network or change their behaviours, QRadar SIEM notices. It tracks each tactic and technique used throughout a kill chain, scores the offence and automatically prioritizes high-fidelity alerts in real-time. Other key features include:

• X-Force Threat Intelligence Application: Pull in any threat intelligence feed using the open standard STIX and TAXII formats and deploy data to create custom rules for correlation, searching and reporting.
• User Behaviour Analytics (UBA): Detect insider threats within an organization using existing data in a QRadar SIEM deployment to generate new insights around users and risk. UBA provides risk profiling and unified user identities along with machine learning to establish normal behaviours and learned peer groups so QRadar SIEM can alert on user-related anomalies.
• Cloud-based SaaS Deployment Model: IBM Security QRadar on Cloud (QRoC) reduces infrastructure costs and maintenance by deploying to a Software as a Service (SaaS) environment hosted by IBM. IBM handles maintenance, upgrades and health monitoring.

CDW Canada is a comprehensive solutions provider for the IBM solutions portfolio and offers the expertise to fit your evolving business needs.