In today’s world, more and more companies are facing cybersecurity threats that can lead to the leakage of confidential data, disruption of systems, and serious financial losses. This can be caused both by malicious actions of hackers, and by the incompetence of employees, technical failures, and other factors.

To ensure the security of information systems and protection against cyber-attacks, companies use various technologies and methods, including the help of SOC service provider.

SOC And Its Technologies

SOC or Security Operations Center is responsible for protecting the organization from cyber threats. SOC analysts monitor the organization’s network 24/7 and investigate any potential security incidents. If a cyber attack is detected, SOC analysts are responsible for taking any action necessary to address it. For these measures, it is necessary to have special technologies that help the work of SOC specialists.

The basic SOC technologies can be roughly divided into several levels. Let’s analyze them in more detail:

Data Collection And Analysis (Log Management, Big Data, Asset Management)

Log Management includes an approach to dealing with large volumes of computer-generated log messages. This technology is designed for collecting logs, centralized aggregation of logs, their long-term storage, real-time log analysis, log search, and reporting.

Big Data in information security is an approach based on the collection, analysis, and use of large amounts of heterogeneous data obtained from heterogeneous sources, including information systems, business systems, control and communication systems, as well as devices and sensors. This data is characterized by large volume and update speed.

Asset Management is a technology for managing a company’s assets (the company’s information and physical resources used). The more a company can reveal about its assets, the better its security. A complete and up-to-date inventory in real-time allows you to more effectively and quickly fix vulnerabilities and respond to information security threats.

Level And Data Analysis (SIEM, UEBA, TI, Machine Learning).

SIEM technology has solved the problem of centralizing information security monitoring. SIEM (Security Information And Event Management) is a system for managing events and security information. This system combines the ability to collect, analyze and manage information security in real-time. With the help of a SIEM system, you can detect security threats, identify anomalous user and system behavior, and quickly respond to security incidents. The SIEM system uses big data analysis techniques, including ML and AI, to detect threats and prevent attacks on information systems. The SIEM system is the most important tool for SOC.

User and Entity Behavior Analytics (UEBA) is a method for analyzing the behavior of users and entities in information systems in order to identify potential threats and anomalous activities.

The main task of UEBA is to detect targeted attacks and insider threats in a timely manner. UEBA uses machine learning algorithms and big data analysis to create profiles of users and IP objects and determine their normal behavior. When behavior deviates from this normal pattern, the system can signal an anomaly, allowing SOC service providers to quickly detect and respond to potential security threats.

Threat intelligence is the process of collecting, analyzing and interpreting information about current and potential threats to information security. Threat intelligence includes collecting information about various types of threats, such as malware, hacker groups, vulnerabilities, application attacks, phishing, DDoS attacks, and others.

This information may be collected from a variety of sources, including open sources, intelligence, event logs, and other internal and external sources. After collecting data on potential threats, the information is analyzed and used to determine the most likely attack scenarios and to develop strategies to prevent attacks and reduce risks. Sources of information about cyber threats include information from:

  • open sources 
  • social networks
  • technical information
  • device log files
  • forensic data
  • information obtained from Internet traffic.

Machine learning in information security plays an important role in detecting and analyzing threats, predicting and predicting attacks, as well as in making decisions about security and protection against cyber threats. These solutions involve creating algorithms that constantly learn from experience. In information security, machine learning can be used to create systems for detecting and preventing cyber attacks, analyzing potential threats, and managing risks. 

Machine learning can also be used to analyze large amounts of data, including detecting anomalies in the behavior of users and devices, as well as classifying and recognizing various types of security threats. This allows information security operators to quickly and accurately identify and respond to potential threats and develop more effective defense strategies.

Level of Automation And Response (IRP, SOAR)

IRP (Incident Response Platform) is a platform designed to automate the processes of monitoring, recording, and responding to information security incidents.

IRP helps information security teams and SOCs automate incident management processes and expedite incident resolution, which can significantly reduce incident response time and minimize potential damage to an organization. It also provides the ability to analyze past incident data and develop strategies to prevent and manage similar incidents in the future.

SOAR (Security Orchestration, Automation, and Response) solutions are software platforms or tools designed to automate and coordinate security, incident management, and threat response processes.

SOAR allows you to coordinate and orchestrate the actions of various security tools and systems, such as monitoring systems, protective devices, threat intelligence tools, and others. This allows you to create a consistent and automated workflow for handling incidents and threats. 

These solutions provide centralized storage and analysis of security data, including events, incidents, and personnel actions. This helps provide a more complete and accurate picture of threats and enables informed decision making.

Wrapping It Up

There are many tools and technologies for detecting threats, analyzing existing vulnerabilities, and for predicting new threats from anomalous activities. The domestic market is rich in technologies that greatly help information security monitoring centers in identifying threats. And this means that for each customer there is its own approach to solving monitoring problems. UnderDefense is an experienced SOC service provider with which your business can be safe at any time of the day.


By Swati