What are the top 7 security analytics use cases for businesses? Why should your enterprise invest in a more analytical cybersecurity solution?
Security analytics solutions aim to collect raw data from disparate network sources. With this aggregated information, security analytics can create actionable insights to identify security; in turn, these events can facilitate immediate investigative responses via the correlation of activities and alerts.
Moreover, security analytics solutions can collect data from throughout your IT infrastructure. This data includes endpoint and user behavior data, network traffic, cloud traffic, and non-IT contextual data.
Of course, security analytics does more than that. It can also detect advanced attacks, identify risks not easily monitored by conventional security products such as signature rules. Thus, this cybersecurity solution can more readily identify unknown attacks.
Above all, security analytics provides enterprises with a tool which helps them transition away from the stagnant prevention cybersecurity model. Instead, they can embrace the modern detection and remediation model of InfoSec. It offers necessary unified visibility on your enterprise, both real-time and historic.
But what specifically can security analytics offer your business? We dive into the security analytics use cases, the broad categories and the individual capabilities, below.
The Three Categories Security Analytics Use Cases
Security analytics use cases generally fall into three broad categories. All of them can prove useful to your enterprise, depending on your industry, size, and cybersecurity risk.
Real-Time Rule-Based Use Cases
Usually, real-time rule-based use cases apply to the detection and remediation of known cyber attacks or attackers; specifically, rule-based analytics draws from threat intelligence feeds. Additionally, real-time rule-based use cases define and detect rule-based approaches such as SIEM.
Real-Time Security Analytics Use Cases
Real-Time Security Analytics allows for the triaging of incoming alerts from other real-time systems like SIEM. Moreover, it can match potential threat patterns requiring longer detection times. For example, real-time security analytics can analyze potentially dangerous IP addresses to discover previous attacks and their severity.
Unlike the above categories, batch security analytics applies cybersecurity to unknown attacks and attackers; after all, IT teams best handle unknown attacks batches. Batch security uses deep statistical models and large data set profiling to discover threats and remediate them. Moreover, it can help with visualizing the threats and security vulnerabilities.
The Top 7 Security Analytics Use Cases
With the top categories of security analytics use cases defined, we can dive deeper into the top use cases for businesses. You may find that only some of these use cases apply to your IT infrastructure or cybersecurity. However, knowing what security analytics can offer your business can help facilitate your research and your cybersecurity.
1. Cloud Security Monitoring
The cloud poses its own obstacles as well as its own rewards to enterprises looking to digitally transform. Indeed, the cloud offers more efficient communications and increased profitability for businesses of all sizes. However, the cloud offers particular cybersecurity challenges as the IT infrastructure scales and becomes more porous.
Security analytics offers cloud applications monitoring. This provides host sensitive data and monitors cloud-hosted infrastructure. Also, many solutions offer support across several relevant cloud platforms.
2. User Behavior Analysis
Your users interact with your IT infrastructure all of the time, and their behaviors determine the success or failure of your cybersecurity. Therefore, your security analytics need to monitor your employees for unusual behaviors which can indicate an insider threat or a compromised account.
One of the most renown security analytics use cases, user behavior analysis or UEBA follows behaviors across time. It can correlate potentially malicious activities by looking for suspicious patterns. Indeed, UEBA provides visibility into your IT environment, compiling user activities from multiple datasets into complete profiles.
3. Network Traffic Analysis
Traffic continually moves in and out of your network at all times, often via communications such as email. Due to its high volume, it can prove difficult to maintain transactional visibility over all the network traffic. Security analytics use cases allow for the analysis of your enterprise network traffic; it can establish baselines and detect anomalies.
Additionally, this can work in tandem with cloud security monitoring to analyze traffic moving into and out of cloud infrastructure. It can also illuminate dark spaces hidden in infrastructures and analyze encrypted sensitive data, ensuring it stays in proper channels.
4. Data Exfiltration Detection
Data exfiltration refers to any unauthorized movement of data within and moving out of your network. Unauthorized data movements could cause data leakage or data theft.
Thus, security analytics helps protect against new cases of data leakage which may elude traditional data loss prevention solutions. Indeed, these data exfiltration detection capabilities work alongside with network traffic analysis. Through data exfiltration detection, security analytics can prevent data leakage beyond what is known through traditional threat intelligence. In fact, it can even discover data leakage in encrypted communications.
5. Insider Threat Detection
Insider threats can pose as much danger to your enterprise as external threat actors. An ignorant, neglectful, or actively malicious user can do as much damage as any fileless malware attack. In some rare cases, an insider threat can even destroy a network.
Via security analytics, your business can anticipate insider threats through behaviors such as abnormal login times, unauthorized database access requests, and unusual email usage. Additionally, it can look for the indicators of data theft behaviors and provide visibility into third-party actors.
6. Incident Investigation
SIEM solutions provide your IT security team with alerts; these result from correlated security events discovered around your IT infrastructure. Under normal circumstances, your team would then investigate these alerts to determine whether they lead to legitimate incidents or false alarms.
However, the sheer number of security alerts from SIEM solutions can overwhelm your IT security team. Often, correlation errors can cause more false positives than legitimate leads, fostering burnout and frustration. To mitigate these issues, security analytics can automate incident investigations, providing contextualization to alerts. Thus your team has more time to investigate legitimate leads and deal with potential breaches.
7. Threat Hunting
Of course, security alerts offer a reactive cybersecurity answer to potential breaches. But always reacting to breaches leaves you perpetually on the back foot against hackers. Instead, your IT security team most proactively engage in threat hunting. They need to search for potential indicators of breaches and dwelling threats which may linger in your IT infrastructure.
Security analytics helps to automate threat hunting, providing an extra set of eyes for your threat hunting efforts. Crucially, threat hunting automation can help with detecting malware beaconing activity and watering hole attacks, a special form of the lateral movement attack.
How to Learn More About Security Analytics Use Cases
You can always download our free SIEM Buyer’s Guide. We examine vendors from both categories in-depth, with our Bottom Line on each!
Latest posts by Ben Canner (see all)
- Why Does Your Enterprise Need SIEM in 2020? - December 4, 2019
- Here are the Top 5 Benefits of SIEM for Enterprises - November 26, 2019
- Everything We Know About the Macy’s Data Breach - November 20, 2019