Using Behavioral Analytics to Combat Cybersecurity Risks

On a global scale, the United States is one of the most targeted countries by cybercriminals, with a report indicating that 46% of global attacks in 2022 will occur in the country. These statistics showcase that organizations and individuals are fighting a never-ending war on data theft.

Most organizations in this world have now adopted various cybersecurity solutions and cloud security software in an attempt to ensure the safety and security of their data from potential threats. Among all the impactful strategies, one of the modern-day tactics is integrating behavioral analytics.

In this article, you will get a detailed understanding of how behavioral analytics are used to combat cybersecurity risks.

Understanding behavioral analytics – why use it for cybersecurity?

For everyone new to the cybersecurity concept, behavioral analytics is the act of running an iterative investigation on the past performance of the business. Thus, it helps in creating insights for making better decisions on various aspects of organizational productivity. Cybersecurity is the key to not just enhancing but also protecting a business’s productivity.

It is a form of analytics that helps businesses detect malicious threats and insider activities. Any abnormal behavior within the business system will be indicated as a first sign of a cyber threat. Therefore, one of the easiest ways of detecting such attacks is by running an assessment across the behavioral patterns to find any potential anomalies.

Areas Where Behavioural Analytics Helps You with Detecting Potential Threats

With the use of behavioral analytics tools, you can potentially use the data that has been collected earlier. It is to create a specific behavioral profile for every user. With the combination of this data and the ML tools, you will be able to track predictable patterns depending on usage over time.

Thus, the tools you are using must send you an alert upon finding a pattern that is possibly a threat. Some of the areas where you can find threats with the use of cloud security software embedded with behavioral analytics are:

1. Credential Usage

Credential usage is one of the biggest problems in data security. More than 61% of all breaches were due to the leveraged use of credentials. Passwords are mostly used in order to manage and secure identities and important accounts, but at the same time, they are easily stolen, mistyped, or forgotten.

Behavioral analytics can easily detect the unusual use of the credentials. It will indicate misuse of the privileges if the account owner is tracked while doing or accessing things they should not. In this way, you can identify and neutralize the threat at the earliest possible time.

2. Departmental Usage

If behavioral analytics shows you results that don’t align with the usual behavior of the department, it is an indication that there’s something wrong. For instance, if a person from the HR department runs complex queries on your business system, there’s something wrong with the usage.

Using behavioral analysis, the other departmental end-points, such as data and time of work, login frequency, transfer of data volume, and others, can also indicate potential threats.

3. Typing Cadence

Typing cadence is a parameter that records the rhythm of how long someone holds down various keys on the keyboard. Following that, it also records how long it takes for the same person to move between two keys. It is just like handwriting, which is unique to each person! Most behavioral analysts know it as keystroke dynamics.

With behavioral analytics keeping an eye on this parameter, too fast or too slow typing can indicate that a bot is accessing business data or using stolen credentials. It is such an effective parameter that tech experts are soon planning to integrate typing cadence as one of the biometric factors for enabling authentication for systems and devices in the future.

Ways Behavioural Analytics Extends its Help for Added Cybersecurity Benefits

Most businesses are seeking cloud migration for their business data. It is to ensure that disaster recovery becomes easy for their business. In accordance with that, businesses are also leveraging the potential of cloud security software with behavioral analytics. Here are a few ways this form of analytics is going to give you a leading edge against threat hunting:

1. Smart Monitoring of the Security

In a business enterprise, you need to set up monitoring for the users, assets, and network. Behavioural analytics being implemented into all three domains will help you understand normal behaviors and baseline them.

For instance, suppose an asset within your business system is designed to carry out specific functions over a network. With behavioral analytics, your team will have knowledge of who accesses an asset, how often it is accessed, and how frequently the processes or applications are used.

Now, when the baselines are determined, you will get a trigger when anything within the system happens other than the specified pattern. Thus, monitoring becomes smarter with behavioral analytics.

 2. Automate the Process of Predicting Cyberthreat Patterns

For automating and optimizing the analytics, it is quite important for your business to employ both supervised and unsupervised learning. Supervised learning teaches how behavioral analytics usually work. In such cases, the cloud security software can be coded to look at specific data types and baseline them to look for various anomalies.

If the baseline data limit crosses the process of identifying anomalies while an asset is being used within the system, then an alert will be raised. On the other hand, unsupervised learning or automated behavioral analytics is a better approach. The algorithms are used to allow the devices to discover unusual patterns and raise an alert upon any detection of anomalies.

3. Supports in Correlating the Data Across the Systems

To maximize the integration of behavioral analytics within security operations, we need to look into the behaviors of all three domains and integrate them together. With such an approach, businesses have the feasibility of getting a complete visualization of what is happening within the enterprise.

Thus, identification of the threat actors will become easier. You get to understand how many and which devices were attacked and compromised in a particular data breach. Apart from that, you will get details on how the cyberattacker got in and what data has been compromised on your network.


You need to be flexible in terms of adapting cybersecurity solutions because the attackers are quite smart at finding loose ends in your system. Criminals are constantly evolving their methods, and so should you. Therefore, it is high time you consider reiterating all of your existing analytical or detection methods and improving them to keep the attackers away.

In the pursuit of that, behavioral analytics can be a winning strategy. It will help you enhance your business’s cybersecurity protection quotient. To learn more about cybersecurity and behavioral analytics, you can check out the services of STL Digital.


1. What is behavioral analytics in the arena of cybersecurity?

Behavioral analytics is the concept of using artificial intelligence, machine learning, big data, and proper analytics to detect any potential malicious behavior. It analyzes the differences between everyday or normal activities and the unusual usability patterns of the system.

2. How can network behavior analysis help boost cyber security parameters?

The network behavior analysis helps you enhance the network safely by monitoring the traffic to your business network. Following that, it observes any unusual activity and the use of network functions. The alert is raised, and defensive methods are then initiated.

3. Can behavioral analysis detect geographical irregularities?

Yes, behavioral analysis can detect geographical irregularities by checking if an account is being accessed from a different IP address or browser, if you are experiencing multiple login attempts from unknown overseas IP addresses, and others. Following that, if a particular user is making continuous wrong login attempts, which is new for his/her access records, behavioral analysis software still detects it as an anomaly.

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