Cyberattacks challenge the corporate security system every year, especially with the advancement of technology, after all, this revolution has brought with it a series of challenges and risks for cybersecurity.
This is because, every day, thousands of new threats are created and the traditional solutions, although very necessary, are not always enough to stop all of them, after all, this revolution in the form of attack requires more intelligence in the detection process.
Given this scenario, the analysis of people's behavior is no longer a choice for organizations, but rather a necessity for risks to be mitigated.
Want to know more? Keep reading this text and find out why behavioral analysis to prevent targeted attacks is so important to protect your institution.
What is behavioral analysis?
Behavioral analytics is an approach to cybersecurity that focuses on observing, monitoring, and interpreting the behaviors of users, systems, and networks to identify activities that may indicate potential threats or attacks.
It works like this, the first generation firewalls analyze the contents of the packet and other metadata such as IP addresses, for example, in this way they can identify and prevent attackers from infiltrating networks.
Antivirus software, on the other hand, constantly scans file systems for malware and other signs that an infected file exists.
With this, behavioral analysis comes to complement these actions and make cybersecurity increasingly effective.
This analysis combines Artificial Intelligence and machine learning to thoroughly analyze all activities based on people's behavior.
In this way, it is possible to analyze situations that can be considered normal and those that represent some risk to the institution. This analysis helps IT teams step up their actions to resolve potential issues.
The tools used for this analysis collect information such as:
People interact with devices;
How they use the apps;
What is the digital behavior of these users.
User behavioral analytics solutions are able to detect threats that traditional defense tools can't identify.
This contributes to significantly decreasing the time it takes to detect and respond to cyberattacks.
That is, in contrast to traditional approaches that rely on signatures or predefined rules to detect threats, this approach looks for patterns of behavior and identifies deviations that may signal unusual behavior.
How does behavioral analytics work?
Behavioral analytics works by gathering data on users' behavior patterns from system logs.
It uses intelligent analysis methods to interpret each data set and establish references of these behavior patterns. The process involves several steps, from data collection to incident response.
Data collection
The first step of behavioral analysis is extensive data collection. This data is obtained from various sources, based on the entire IT infrastructure of the organization.
First, we have the system logs, which are records of operating system and application events.
These logs detail all the activities performed, such as accessing files, executing commands, and configuring changes, providing insight into what happens inside a system.
In addition, network traffic is another essential source, because it captures data from network packets and reveals communications between devices, including the source and destination of data, as well as the content of transmissions.
Another important source of data is authentication logs, which document login attempts, both successful and failed, as well as password changes and privileged access.
These logs are essential for identifying suspicious or unauthorized activity. Interactions with applications also provide valuable insights by showing how people interact with software and services, including usage patterns.
Finally, security sensors, such as firewalls, intrusion detection systems (IDS), and intrusion prevention systems (IPS), are very important data sources that monitor and protect systems from potential threats, helping to maintain the integrity and security of networks and devices.
Data Processing
After collecting the data, it needs to go through a processing process to establish a behavior profile.
This step involves the use of Machine Learning and Artificial Intelligence techniques to analyze large volumes of data and identify consistent patterns.
It starts with data pre-processing, which includes cleaning and normalizing the data collected to remove duplicate information and inconsistencies, ensuring the accuracy and effectiveness of the data used in the analysis.
Next, feature engineering occurs, where relevant characteristics are extracted from the raw data, such as transforming login records into metrics such as login frequency, access times, and geolocation.
In addition, statistical modeling is applied to identify patterns of normal behavior.
This may involve creating individual profiles for each user or device, as well as aggregated profiles for groups of users.
Finally, Machine Learning models are trained using the data collected, employing techniques to group similar behaviors or supervised algorithms to classify behaviors as normal or anomalous.
This process is essential for detecting deviations and potential security threats, allowing for a quick and efficient response.
Analysis and Response
After anomalies have been detected, it is essential to verify whether they pose a real threat or just a false alarm.
This involves a detailed analysis of the context of suspicious activity, such as checking for other signs of compromise, for example, changes to important settings or attempts to communicate with suspicious servers.
In addition, data correlation is done, where anomalies detected from different sources are checked to identify patterns that may indicate a true threat.
In many cases, it is necessary for security analysts to manually review these anomalies to confirm that they are indeed threats.
If a threat is confirmed, measures should be taken immediately, such as blocking the suspected user's access, isolating the compromised device, or activating incident response plans to contain and mitigate the damage.
PhishX as an ally of organizations
Cyberattacks have become increasingly sophisticated and difficult to detect, the complexity and accuracy of these attacks make it difficult to identify and protect effectively through traditional security methods.
In this context, behavioral analysis emerges as a solution to face these challenges.
By monitoring and analyzing people's behavior, organizations are able to identify patterns and activities that may indicate the presence of a threat.
PhishX can assist your organization in behavioral analysis, our ecosystem uses monitoring tools that analyze people's behavior.
Through our platform, it is possible to carry out attack simulations and obtain results in real time. This allows organizations to assess the risks present in their teams.
In addition, we offer an analysis of the vulnerability of the devices, helping to identify the risks they pose to the organization.
All this information is presented in intuitive graphs, making it easy to visualize and interpret the data.
Our ecosystem also includes training, booklets, videos and announcements. With this, by analyzing the data, you can develop cybersecurity actions and promote employee awareness in a single place.
PhishX is an all-in-one platform that helps businesses identify risks and implement effective strategies to combat and mitigate threats.
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