Security analytics assesses an organization’s ability to detect, manage, and remediate threats. It enhances efforts in maintaining regulatory compliance, averting data losses, and preventing potential threat intrusions. The market for advanced security analytics solutions is expanding and we have seen a shift from rule-based detection methods to machine learning and AI-driven threat action responses. Its market is estimated to reach a valuation of USD 25.4 billion by 2026 and grow at a CAGR of 16.2% between 2021-26. Therefore, organizations will be investing in the latest solutions and enhancing their cyber security efforts in the near future.
Effective security analytics leverages automation and harvests data to reveal who is doing what across which environments. The best solutions combine SIEM, endpoint detection, network traffic analysis, and other features. In this guide, we will discuss what is security analytics, its key benefits and challenges, how it compares with SIEM, and more below.
What is Security Analytics?
Security analytics is a cybersecurity approach that involves the collection, aggregation, and analysis of data to augment an organization’s ability to detect, analyze, manage, and mitigate threats. It is a proactive means of making sense of high volumes of security data flowing in and out of the organization.
Security analytics solutions are usually deployed in organizations to provide rapid threat-hunting capabilities, accelerate incident response, and prevent potentially costly data breaches. They are also used to conduct real-time risk assessments and to enhance an organization’s overall cybersecurity posture.
Why is Security Analytics Important?
Security analytics is important for organizations because it makes it easier to collect large volumes of security data, process, and transform it. In today’s competitive landscape, it is crucial to analyze diverse datasets from multiple sources and identify correlations and anomalies in data.
Security analysis allows experts to conduct root cause investigations and pinpoint various attack patterns. It enables them to generate comprehensive reports and save their findings for future use. Attackers are always on the constant lookout to locate vulnerabilities and exploit them. Security analytics helps disrupt their movement by prioritizing risks and keeping pace with their growing efforts.
How does Security Analytics Work?
Security analytics provides the tools and features needed to investigate incidents, find out how IT systems are compromised, and learn more about emerging threats. It raises the security awareness of an organization by granting deep real-time visibility into its current infrastructure.
No business can know when a threat is incoming, but with security analytics software, organizations can predict the next attack and take appropriate measures. It helps them stay one step ahead of cybercriminals, address hidden and known vulnerabilities, and close identified gaps in security.
There is huge pressure on IT teams to report their latest findings to stakeholders. Security analytics keeps track of threat patterns, monitors movements, and immediately alerts all users in the enterprise once an anomaly is detected.
Who uses Security Analytics?
Almost every modern organization with a digital architecture or presence uses security analytics. Security Operations Centers (SOCs) consist of teams that have analysts, engineers, and other frontline members who use security analytics. CISOs in companies use security analytics solutions to make sure that sensitive data gets adequate protection.
Security analytics is needed by companies because it allows them to detect threats before they escalate, become major issues, and cause data breaches. It is a preventive measure that adds an extra layer of protection, thus ensuring robust cyber security.
Security Analytics vs SIEM
Millions of event and log data are generated on a daily basis and finding the Indicators of Compromise (IoC) can prove to be a huge challenge for enterprises. Security analytics provides full-stack visibility into infrastructures and analyzes mobile, social, information, and cloud-based channels.
SIEM is a great technology that deals with perimeter and signature-based cyber security. It is reflective of today’s dynamic threats. Many organizations choose between SIEM and security analytics and some combine both in an integrated fashion.
Below are the distinct differences between security analytics vs SIEM:
| Security Analytics | SIEM |
|---|---|
| Designed for modern business architectures, dynamic, microservices, and DevOps-friendly; is elastic, multi-tenant, and secure | Designed for monolithic business applications, static, and has long development and release cycles |
| For cloud-based infrastructure; | For on-premises infrastructure |
| Solutions can be deployed instantly and in near real-time | Takes 15 months on average to deploy |
| Uses continuous monitoring methodologies and behavioral-based modeling to protect against unknown and hidden threats. Identifies abstract threat patterns, anomalies, trends, and fraudulent activities in networks. | Delivers perimeter-based security by analyzing attack signatures; has fixed rule sets when it comes to threat detection |
| Holistic and enterprise-wide visibility with APIs, integrations, and cloud-native services | Limited visibility with port mirroring and security islands |
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Get a DemoSecurity Analytics Components
There are various components to security analytics and they are as follows:
- Threat detection and incident response
- Compliance management
- Reports and dashboards
- Correlations and security events monitoring
- Identity and access management
- Anomaly detection
- Endpoint data security
- Data collection and user behavior analytics
- Cloud security and threat intelligence
- Enhanced incident investigation
- Cyber forensic analysis
Most SIEM solutions come with a security analytics component that features live dashboards that intuitively visualize data via graphs and charts. Security teams can update these dashboards automatically, get alerts and notifications, and map data trends and relationships. Another facet of security analytics is the generation of real-time reports. These reports provide enhanced visibility into infrastructure operations and can be customized to fit internal security requirements. They can be exported in different formats and are based on known Indicators of Compromises (IoCs).
Benefits of Security Analytics
- One of the biggest benefits of security analytics is how it can analyze high volumes of security data coming from different sources. It flawlessly connects the dots between security events and alerts. Security analytics enables proactive threat discovery, response, and incident risk management.
- Good security analytics will limit the scope for data breaches by identifying and reducing attack surfaces. It will analyze threats from the attacker’s perspective and give users insights into where the next attack is targeting them. Businesses will be able to predict the frequency of attacks and better prepare for them.
- Security analytics can analyze a broad range of data such as endpoint and user behavior data, network traffic, cloud traffic, business applications, non-IT contextual data, external threat intelligence sources, third-party security data, and identity and access management information. It even provides proof of compliance during an audit and discovers hidden issues that may lead to policy violations, allowing organizations to effectively address them.
Key Challenges of Security Analytics
Some of the key challenges faced in security analytics are:
1. Shortage of Skilled Security Professionals
Although security analytics technologies are evolving, there is a shortage of skilled security professionals who can use them. In today’s digital threat landscape, the role of a threat hunter has become indispensable. A lack of skilled data scientists in the network security industry is a big problem.
2. Extrapolating Actionable Intelligence
Sometimes security analytics solutions don’t give the best security recommendations. Many services fall short and fail to deliver actionable insights via reporting. Simply handling and categorizing big data isn’t enough.
Many businesses are overwhelmed with the high volumes of data and need to analyze it in ways that benefit their business revenue growth and performance. Without reliable security analytics solutions, organizations will stay open to malicious threats. Security analytics platforms need to be managed properly so that companies know where to invest additional cybersecurity efforts or scale their resources accordingly.
Best Practices for Implementing Security Analytics
Here are some of the best practices for implementing security analytics:
- Password-protect your BIOS modifications. A malicious actor might try to change your boot parameters, so password protect the bootloader. Set passphrases for any chassis where you use self-encrypting drives. That way, if a drive is removed, it cannot be read.
- If you don’t set a passphrase, the data on the removed drive can still be read. However, you can use SEDs to encrypt data regardless of whether you choose to set a passphrase.
- When integrating security analytics with network shares, ensure that data streams between your provider and the security analytics management port cannot be intercepted.
- Enforce authentication with an API key for your external resources and account credentials. Change your API keys and user credentials regularly. Use methods like isolated subnets, VLANs, and user access controls for external servers and applications.
- If you are not using one of these, delete your firewall rules that may permit FTP data through a port or redirect all inbound HTTP requests to HTTPS.
- Disable root access via SSH and root logins. Review your log files regularly to check for root login attempts and malicious activities.
- Do not modify your system settings, such as CONF files, via the CLI unless you have proper technical documentation or support.
Security Analytics Use Cases
In today’s digital age, business continuity means everything, and operational failures can result in losing customers rapidly. Security analysis can make organizations more agile, responsive, and implement robust security measures to mitigate emerging threats.
The following are the most popular security analytics use cases for organizations:
1. Predictive Analytics and User Entity Behavior Analytics (UEBA)
UEBA goes beyond the traditional perimeters of detecting unknown risks, threats, signatures, and attack patterns. Machine learning models can detect false positives, anomalies, and generate predictive risk scores for threats.
Modern security analytics solutions models include great data ingestion capabilities. Advanced security analytics services provide features such as cyber fraud detection, stateful session tracking, privilege access monitoring, insider threat detection, IP protection, data exfiltration defenses, and more.
2. Identity Analytics (IA)
Identity analytics is quickly becoming the backbone of every organization. Security analytics helps users understand the role of identities in cloud environments. It identifies access outliers, orphan or dormant accounts, and defines intelligent roles. Besides confirming access privileges, it provides 360-degree visibility for identity groups, access entitlements, and helps establish baselines for normal and anomalous behaviors in networks. From risk-based authentication, risk account discovery, SoD intelligence, and more, identity analytics in security analytics safeguards users in organizations. It also prevents instances of cloud account hijacking, lateral movements, and licensing issues.
3. Compliance Management
When it comes to data protection and security, a company is expected to adhere to the latest industry norms and standards. There are different types of regulatory mandates and they can vary by region. Security analytics streamlines compliance management by enabling proactive measures and keeps companies up-to-date. They prevent potential compliance violations, lawsuits, and legal complications that may arise due to poor compliance practices. Most platforms support multi-cloud compliance and implement standards like PCI-DSS, HIPAA, ISO 27001, SOC 2, and others.
Security analytics solutions can store and archive log data for audit purposes as well. Besides this, they also generate compliance risk assessment scores and recommend remedial activities to be undertaken in the event of any gaps.
Conclusion
Increasingly sophisticated threats push organizations to bolster cyber defenses and adopt the best security analytics solutions. Successful defense needs full enterprise-wide visibility, holistic security, and threat intelligence capabilities.
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FAQs
Big data security analytics is the process of employing various advanced tools and technologies to analyze huge volumes of unstructured data in order to identify and mitigate potential threats. The aim is to scope out vulnerabilities in a company’s security systems and take remedial action.
The primary capabilities of security analytics solutions are – incident response and investigation, risk management, unauthorized data access prevention, privilege access and permissions management, compliance monitoring, and machine-driven threat detection.
Cybersecurity analytics involves the collection, aggregation, segmentation, transformation, and analysis of security data. It extracts insights used to perform vital business functions and safeguard organizations from incoming attacks.
Security analytics typically examines log files, network traffic, user behavior, system processes, and threat intelligence. It may also incorporate information from endpoints, applications, or cloud services to uncover hidden risks. By correlating these data points, security analytics tools can identify malicious activities, policy violations, and security gaps in real time.
Security analytics extends beyond traditional SIEM by integrating advanced analysis and threat intelligence, allowing proactive detection, anomaly tracking, and risk scoring. While SIEM typically collects and correlates event logs, security analytics provides deeper, in-depth context, helps anticipate sophisticated threats, and guides remediation efforts to reduce breach risks more effectively overall.
Yes. Small businesses can significantly benefit from security analytics by detecting threats, identifying policy misconfigurations, and gaining insights into unusual activity that might jeopardize sensitive data. Implementing streamlined solutions with built-in intelligence helps even limited teams respond quickly, reduce risk, and align with compliance standards without incurring large overhead costs.
Focus on monitoring login attempts, root access attempts, network traffic spikes, file integrity, and application performance. Track successful versus failed authentications, unusual data flows, and changes in configuration files or BIOS settings. Regularly review logs for suspicious patterns, correlate alerts from various endpoints, and adjust firewall or access controls accordingly.
