In the world of analytics, acronyms are a dime a dozen. Yet, in the IT and security space, there’s one important one to learn: “SIEM” & “Integration”.
What is a SIEM?
This word stands for Security Information and Event Management. SIEM is the process of aggregating IT security data from myriad sources, analyze and correlate alerts, and take appropriate action to address any deviations,
Do you plan to make investments into your security infrastructure? If so, it’s important to make sure the tools and systems you’re using are providing maximum value.
Today, we’re sharing how integrating SIEM best practices into your security approach can help you achieve the visibility you need to stay ahead. We’ll also share the exciting new ways that machine learning is making security analytics more accurate than ever before.
Ready to learn more? Let’s get started!
What is a SIEM?
Before we delve into why it’s important and how it’s evolving, let’s first review what SIEM entails.
SIEM Technology helps enterprise security professionals take an up-close look at all of the activities that take place inside of their IT environment
In short, SIEM technology helps enterprise security professionals take an up-close look at all of the activities that take place inside of their IT environment. It also creates a track record of all of these activities as they occur in real-time.
The core functions of SIEM are evident within the acronym itself. The name combines security event management (SEM) with security information management (SIM).
The former is the process of analyzing log and event data in real-time to monitor threats, correlate events and provide incident responses. The latter applies to the practice of collecting, analyzing and reporting on that log data.
While traditional log management systems have been around for decades, modern enterprises need more robust compliance management. As such, today’s SIEM solutions are more streamlined and detail-oriented. In addition, they provide the level of monitoring and reporting that’s necessary to support major industry mandates, including:
- Health Insurance Portability and Accountability Act (HIPAA)
- Sarbanes-Oxley Act (SOX)
- Payment Card Industry Data Security Standard (PCI DDS)
How Does SIEM Work?
When you integrate SIEM into your technology infrastructure, the software goes to work to collect and aggregates any log data that your IT systems generate.
These systems can be wide-reaching, encompassing everything from host systems, centralized directories, to network and security devices. This can also include any firewalls or antivirus filters that your organization has in place.
Every hour around the clock, these systems are busy and engaged. You might not always be aware of all of the updates and changes, but your SIEM software is. Every time an event or incident happens, the tool can first categorize it and then analyze it.
From there, it can generate reports and send alerts that can help you stay informed. For instance, your SIEM software can provide reports on any security-related incidents that occur, including:
- Successful or failed logins
- Suspicious malware activity
- Any potential malicious actions
What if the software notices any activity that deviates from preset rulesets? Then, it can send a real-time alert to notify key stakeholders on your IT team, and it can also generate a ticket to support your ITSM processes.
How Machine Learning Strengthens SIEM Integrations
Some of the newer SIEM Integration products on the market leverage capabilities that enable them to achieve deeper insights into security operations.
In addition to standard log data, these new technologies also incorporate threat intelligence feeds. Some products also feature advanced security analytics capabilities that look at both user and network behavior. This allows them to provide more intelligence behind what distinguishes a “normal” activity from a malicious one.
At Enterprise Integration, our AI solution is known as DRE or Digital Robotics Engine. It’s designed to manage big data with ease and replace repetitive, redundant tasks with automated workflows.
Consider the value of artificial intelligence (AI), deep learning capabilities, advanced statistical analysis, and other analytical methods. There are myriad tools that you can integrate into their SIEM integration setup to drive more informed results.
Leading the pack, however, is machine learning.
When you introduce automation into a traditional SIEM environment, you add more value to the way you manage risk and provide security for your organization.
Consider, for instance, the constant monitoring that SIEM requires. If your IT security team is unprepared to meet these demands, it won’t take long before burnout sets in. Manually keeping an eye on every system checkpoint is exhausting at best and impossible at worst.
This is where machine learning comes in. You aren’t required to incorporate it to run a powerful SIEM environment. Still, it’s a supplemental tool that can make it infinitely easier.
For example, when you incorporate DRE into your SIEM solution, some of the specific benefits it presents include:
- Self-learning to automate repetitive, unstructured processes
- Real-time analytics
- Data visualization dashboards
- The ability to share across departments (e.g. HR, IT, Finance, Sales)
- Top-level of enterprise security
- The ability to automate system alerts
Security Operations Center & SIEM Integration
When you partner with our team you can choose to incorporate DRE into any SIEM solution. Or, you can invest in our Managed SIEM Services and take advantage of our already-built Security Operations Center (SOC).
A few of the benefits of going this route include the ability to:
- Centralize all your security event data in one spot
- Correlate data across myriad security applications, including access control, antivirus, firewall, and other security-related applications
- Utilize innovative, top-tier AI tools and threat intelligence databases
- Identify concerning patterns
- Blacklist any suspicious addresses
- Address and correct potential vulnerabilities before they welcome a new attack
How much could your staff save if you installed a SIEM solution that automatically correlates data and various logs from multiple sources
Leveraging our managed SOC can help you achieve the security-related peace of mind you’re looking for, without the soaring costs often associated with more advanced analytics.
Especially if your team spends important time crating correlation rules that never stick, it’s smart to invest in a platform like ours that takes all the legwork out of the equation.
How much could your staff save if you installed a SIEM solution that automatically correlates data and various logs from multiple sources? Ours can do all of that and more. Moreover, it can help you make sense of disparate data sources and create a comprehensive look into your current security analytics.
When you choose our Managed SIEM strategies, you can claim the following benefits, among others:
- A secure, certified, compliance-ready cloud location for log files
- Automatically scoured OTX and other threat intelligence sources
- The ability to keep current with known threat agents worldwide
- The ability to detect patterns of abnormal activity
The software is also designed to help your SIEM systems take proactive control against potential threats. It does so by routinely scanning the Open Threat Exchange, analyzing security event information, and taking other actions.
As new threat agents emerge, you’ll know in real-time so you can prepare accordingly. Whenever you need to double-check a data point, you’ll find them all captured within a customizable dashboard for quick access.
Defining and Understanding Machine Learning
The term “machine learning” refers to a specific branch of AI. Specifically, it’s an approach that leverages AI algorithms to learn from experience over time following an initial data input.
When it comes to SIEM, advanced solutions can use machine learning to help their systems comprehend cybersecurity rulesets and other data. This helps them facilitate, quicken and improve security analytics. Any time spent handling rote tasks or even more advanced duties can now be directed to more mission-critical functions.
Depending on the level of skill and sophistication required, these machine learning systems can be as simple or complex as necessary. You can even configure some to make decisions autonomously, changing their behavior as required.
The Roles of Machine Learning
The basic explanation is that machine learning can enable your IT team to perform threat analytics and send risk notifications in real-time. Now, let’s take a look at some of the potential offerings it can provide.
Prediction
Machine learning algorithms enable SIEM systems to use previous patterns to predict and anticipate future data.
For a real-world example, consider the data patterns provided during a security breach. Machine learning capabilities enable systems to internalize those patterns. They can then use them to detect suspicious activities that could indicate a subsequent breach or infiltration.
This is an important step, especially given that a data breach can cost your company around $150 for every compromised record.
Incident Response Intelligence
Regardless of your company size or industry niche, a comprehensive incident response plan is a must-have resource. However, it isn’t enough to simply devise a plan and store it on your intranet.
Rather, your network security team should also have in place the robust reflexes required to identify a data breach and respond promptly to mitigate it. Machine learning allows your SIEM software to analyze previous incident response efforts and then provide custom recommendations to help guide future efforts.
This approach can strengthen your incident response plans and ensure they’re following the most effective strategies possible.
Data Clustering
Most AI programs facilitate data classification. However, most aren’t capable of grouping unrecognizable data points and event information.
On the other hand, machine learning can leverage data clustering capabilities to not only identify these unknown values but also group them into categories based on similarities detected.
Benefits of Machine Learning and SIEM Integration
Understanding the aforementioned roles of machine learning, what benefits does this technology present to SIEM solutions? There are three main roles that this functionality provides, so let’s review!
Reduced Manual Monitoring
While it won’t completely remove the need altogether, machine learning can greatly reduce the requirement for humans to continually monitor SIEM solutions.
In this sense, you can think of the technology not only as a second pair of eyes but another set of hands, too. This allows you to optimize your cybersecurity in a way never before possible.
Keep in mind, however, that specialized human intelligence triumphs AI. You’ll still need someone on board to monitor your SIEM solution.
Deeper Investigation into Alerts
It’s common for enterprise-wide SIEM solutions to generate false-positive alerts. When these occur, legitimate leads and security concerns can fall lower on the list of priorities.
Keeping up with these shifting, ever-changing demands can exacerbate feelings of exhaustion and burnout among your IT department. Machine learning can help investigate all security-generated alerts to reduce the number of false positives created.
Workflow Automation
The success of your IT team depends on smooth, seamless workflows that transfer data with ease. If you’re still relying heavily on manual efforts, there’s a high possibility of stress, human error, or both.
Machine learning allows users to automate and standardize workflows. From there, they can reduce the possibility of human error and get the job done much quicker.
Business Process Facilitation
When you make the shift to transfer most of your manual processes onto an automated platform, you immediately remove some of the work-related pressure plaguing your team and office.
Freed from around-the-clock security system monitoring, your IT employees are able to focus more clearly on other core infrastructure concerns.
Discover Our SIEM and Machine Learning Solutions
Now you know the benefits that both SIEM solutions and machine learning can present to your security analytics team.
Are you ready to try these tools for yourself?If so, you’ve come to the right spot.
What is SIEM? It’s the security analytics platform that could change your approach for the better, and you’re closer than you think to achieving it.
We provide a range of services designed to help your IT team excel. From custom technology solutions and support services to proactive monitoring and business process automation, we do it all. Check out our Managed SIEM Solutions to learn more today!
Could this be what your security is missing?
Now more than ever, the security of your organization’s business-critical information is of the utmost importance. It’s the most valuable asset you have, and not protecting it effectively can cause irrevocable damage to your reputation and to your bottom line.
As more and more data is generated in an increasingly digital marketplace, it will only become more difficult to maintain visibility of it all. Threat intelligence will also only become more complex and difficult to gain as cyberattacks grow in sophistication and frequency.
You need a way to easily achieve maximum visibility of your security information, while also boosting the accuracy of your security analytics – to ensure that you’re seeing and doing all that you can to protect your data, and to ensure that you’re doing so in the right places. As you now know, a SIEM integration and machine learning solution from Enterprise Integration can help you do just that.
Learn more about how SIEM Integration
can help give your IT security the edge it needs to prevent a data breach
Don’t Wait!
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