What Is Cybersecurity Analytics (and Why Does It Matter)?

Across the nation and across the globe, the demand for qualified and experienced cybersecurity professionals continues to rise. In fact, according to data from the United States Bureau of Labor Statistics (BLS), the job outlook for information security analysts alone is projected to grow 33 percent between 2023 and 2033, which is much faster than the national average for all occupations.
 

If you're interested in advancing your career in cybersecurity, there are plenty of opportunities out there. As businesses and individuals strive to improve their defenses against ongoing cybersecurity attacks, there remains a dire need for cybersecurity analytics professionals. With the right education and training in this niche of cybersecurity, you could be ready to pursue this critical role.

How Cybersecurity Analytics Works

What is cybersecurity analytics, anyway? In simple terms, cybersecurity analytics involves the careful assessment of an organization's networks and systems to identify security risks and other vulnerabilities, ultimately aiming to thwart potential threats and enhance overall security.

Performing a cybersecurity risk assessment or analysis typically occurs in two stages: collection and analysis.

Data Collection and Integration

During the initial phase of a cybersecurity risk analysis, professionals collaborate with an organization to gather as much information as possible about its cybersecurity practices, safeguards, and strategies. This may involve working closely with the organization's own cybersecurity team or IT team, where applicable, to gain a deeper understanding of their strategies and procedures.

Analysis, Correlation, and Detection

Once cybersecurity analysts have the necessary data, they can begin performing a detailed analysis of an organization's critical infrastructure. Typically, this includes conducting a thorough threat and vulnerability analysis, which aims to identify weaknesses within the infrastructure that malicious actors could exploit.

During this stage of the process, cybersecurity analysts rely heavily on data analysis to identify the most likely threats and detect trends in the effectiveness of security controls. From there, these professionals can provide detailed security assessment reports to organizations with specific and actionable recommendations for improvement.

Key Components of Cybersecurity Analytics

Cybersecurity analytics is a data-driven field, and professionals working in this area of the industry must be well-versed in the tools and technologies used to extract meaningful insights from raw data.

Core Technologies and Tools

When conducting cybersecurity assessments and threat analyses, professionals must utilize a range of analytics tools. Tools used in cybersecurity analytics include network analysis, vulnerability assessment, penetration testing, and digital forensics tools.

Data Sources and Contextualization

At the end of the day, a cybersecurity risk assessment is only as valuable as the data that was used to conduct it. With this in mind, professionals working in cybersecurity analytics must know how to find sources of quality, reliable, and accurate data. Often, this kind of data comes from such sources as:

• Network traffic logs
• Endpoint events
• Cloud services
• Operating system event logs
• Intrusion detection system (IDS) alerts

Even once cybersecurity experts have the necessary data, they must also be able to contextualize it and determine its application in a threat analysis.

Types of Cybersecurity Analytics

When cybersecurity analytics professionals are called in to consult with an organization, one of three types of analytics is typically requested.

Descriptive and Diagnostic Analytics

Descriptive analytics (also known as diagnostic analytics) is often requested after a cybersecurity attack, such as a widespread data breach. The purpose of this type of analytics is to determine exactly what type of attack occurred, how the events unfolded, and how the attack was carried out in detail. From there, cybersecurity analytics professionals can utilize raw data to gain a deeper understanding of events, identify potential patterns, and provide recommendations to prevent similar attacks in the future.

Predictive and Prescriptive Analytics

In predictive cybersecurity analytics, the primary objective is proactive cybersecurity. Rather than responding to a threat after it has already occurred, organizations rely on predictive and prescriptive analytics to thwart future attacks. By analyzing cybersecurity data from reliable sources, professionals can use statistical modeling and other tools to predict the likelihood of specific attacks and take proactive measures to prevent them.

Real-Time and Streaming Analytics

Another type of cybersecurity analysis that can be useful is real-time or streaming analytics, which (as the term implies) involves monitoring and analyzing data continuously and in real-time. This approach to cybersecurity analytics can be especially useful in identifying signs of an attack before they actually occur, which can improve reaction times and mitigate the effects of an attack.

Benefits of Cybersecurity Analytics

When quality data is used to gain insights into cybersecurity threats, organizations and individuals alike can benefit in a number of ways.

Improved Threat Detection and Response

First, cybersecurity analytics can empower organizations to detect or even predict the likelihood of certain threats before they occur. This, in turn, makes it possible for attacks to be thwarted entirely or mitigated more quickly, especially when threat response plans are in place ahead of time.

Enhanced Operational Efficiency and Compliance

When organizations have cybersecurity analytics procedures in place, they can enhance their operational efficiency while maintaining compliance with stringent cybersecurity regulations. This may be especially true in industries that are heavily regulated when it comes to handling sensitive security information or personal data. With the right cybersecurity analytics, organizations can maintain compliance and avoid potential penalties or fines.

Greater Visibility Across the IT Environment

In many ways, cybersecurity analytics can provide a more holistic view of an organization's cybersecurity practices and strategies. In turn, this can translate to better visibility of threats and other important security analytics across the entire IT environment, encompassing not just cybersecurity analysts, but also other members of IT and security teams.

Support for Strategic Decision-Making

When cybersecurity analytics is done right, organizational leaders and decision-makers can have the information and threat intelligence that they need to make informed decisions regarding cybersecurity strategies and procedures. By understanding the threats most likely to impact the organization, decision-makers can confidently implement cybersecurity changes and upgrades to protect their systems and networks.

Early Warning and Proactive Defense

Because cybersecurity analytics can be used proactively to identify threats that may otherwise be overlooked, they are instrumental in providing organizations with the early warning that may be needed to defend against an attack before it is carried out.

Use Cases and Real-World Applications

From predicting potential threats to identifying signs of ongoing attacks, cybersecurity analytics tools can be utilized across a wide range of industries, and in some cases, even within government agencies.

Industry-Specific Applications

Some examples of industries that rely heavily on cybersecurity analytics in today's dynamic cybersecurity landscape include:

• Financial services - Analytics can be used to protect better sensitive consumer financial data, as well as to defend against fraud and other types of attacks proactively.
• Healthcare - Organizations in healthcare, including facilities and health insurance agencies, may rely on cybersecurity analytics to protect sensitive patient data, such as health records, while mitigating cyberattacks that can directly impact patient care.
• Retail/e-commerce - As more businesses operate online, cybersecurity analytics are paramount in protecting consumer financial data (such as credit card and other payment information) while keeping connections secure.

Enterprise and Government Adoption

Likewise, cybersecurity analytics have become increasingly valuable in enterprise operations and the public sector, including government agencies. Because many government agencies have fallen victim to cybersecurity attacks in recent years, the need for cybersecurity analytics has become increasingly apparent as a means of protecting government systems and confidential data.

The Future of Cybersecurity Analytics

The field of cybersecurity analytics has made significant strides in recent years, leaving many to wonder what new trends and technologies may be on the horizon.

Evolution Through Artificial Intelligence (AI)

One of the most notable developments in cybersecurity analytics that we're likely to see evolve in the future is the use of artificial intelligence as a threat detection tool. Using AI and machine learning, it is possible to analyze data faster and more efficiently than ever before, which means potential threats or attacks can be recognized and defended against even sooner.

Similarly, AI is enabling organizations to establish automated responses to certain cybersecurity threats. With AI-powered threat response, it may be possible to mitigate losses and damage resulting from an attack while better protecting an organization's reputation.

Integration With Emerging Security Frameworks

As new cybersecurity analytics technologies emerge, professionals in this field will also need to learn how to integrate these tools into both new and existing security frameworks. By leveraging innovative technologies and adapting them to emerging frameworks, cybersecurity professionals can minimize risks. One prime example of a new security framework gaining traction in the cybersecurity world is the zero-trust approach, which assumes that no users or devices are inherently safe or trusted within a network.

Learn More in a Cybersecurity Analytics Degree Program

Unfortunately, cybersecurity threats are only likely to become more advanced and widespread as time progresses, highlighting the need for experienced and knowledgeable cybersecurity experts to thwart attacks and protect sensitive data. Enter the role of the cybersecurity analytics professional, who can uncover cybersecurity threats and shape proactive defense strategies in an evolving online landscape.

If you're serious about exploring cybersecurity analytics as a career option, and if you already have your bachelor's degree in cybersecurity or a related field, then Champlain College Online's master's degree in cybersecurity analytics may be right for you. This program covers such critical topics as advanced threat analysis, machine learning applications, and data-driven strategy to help you better protect digital assets. Plus, with its convenient online format, you can work your education into your busy life and still graduate in as little as 10 months.

Learn more about this program by getting in touch with our admissions team today. Ready to apply? Get started with your online application.