SIEM systems are the focal point of the IT environment that security analysts are defending. SIEM systems centralize the collecting of security data from all relevant data sources, storing a wealth of information that may be utilized to obtain insight into real-time events and processes.
SIEM (Security Information and Event Management) is a monitoring and analytical system for security and auditing. SIEM technology combines log data, security alerts, and events into a single platform for real-time security monitoring analysis. SIEM is becoming a mainstream security technique because of the recent increase in cyber-attacks, as well as the tighter security requirements that enterprises are forced to follow.
As said mostly, SIEM is a security solution that assists enterprises in identifying potential security threats and vulnerabilities prior to their disrupting company operations. It detects anomalous user behavior and uses artificial intelligence to automate many of the manual processes associated with threat detection and incident response, and it has become a standard in today’s Security Operation Centers (SOCs) for security and compliance management use cases.
SIEM has evolved over time to become more than the log management systems that came before it, according to InfosecurityOutlook. It’s all because of the power of AI and machine learning, SIEM now enables advanced user and entity behavior analytics (UEBA). It’s a powerful data orchestration solution for dealing with constantly changing risks, as well as regulatory compliance and reporting.
SIEM software gathers log and event data from applications, devices, networks, infrastructure, and systems to do analysis and provide a comprehensive perspective of an organization’s information technology (IT).
The following are some of the key components of the SIEM solution:
• Open and scalable architecture: Ability to consolidate data from multiple systems, including on-premises, cloud, and mobile, into a single entity.
• Real-time visualization tools: Tools that assist security teams in visualizing linked security events to appropriately depict threat incidents.
• Big Storage: Capability to collect and manage massive, complicated data sets for indexing and organized and unstructured search.
• User and entity behavior analytics (UEBA): A solution for tracking behavioral changes in user data and detecting anomalies when patterns deviate from “normal.”
• SOAR (security, orchestration, and automation response): Technology that automates regular, manual analyst operations throughout the incident response workflow to boost operational efficiency.
This solutions can be installed on-premises or in the cloud. SIEM leverages rules and statistical correlations to produce actionable information during forensic investigations by analyzing all data in real-time. This technology evaluates all data, categorizing threat behavior by risk level to assist security teams in promptly identifying malicious actors and mitigating cyber-attacks.
SIEM is being implemented by organisations to protect their environments and to comply with an increasing number of compliance types. The next logical step once a company has accepted the necessity for SIEM is to design the technological implementation.