UGuard AI is a next-generation information security platform with the security information event management (SIEM) capabilities required to aggregate and analyze information security-related records from critical information security devices, operating systems and applications in the enterprise environment. It further provides four superior features: context-awareness, intelligent drive, historical data retrieval, and behavior abnormality analysis mechanism. Through advanced technologies such as big data analysis, mechanical learning, and artificial intelligence, it can efficiently extract more substantive information security information and present it in a visual way that is easy to understand and recognize. This prevents the traditional SIEM system from being too complicated in terms of information security information, causing enterprise information security managers to be unable to efficiently grasp the correct information security information, which will in turn delay the handling of major information security threats.
The new generation security information event management platform (NG-SIEM), which is the result of our long-standing professional experience in SOC information security operations, combined with U-SOC information security monitoring and control services for more than 180 customers, more than 1,400 security devices, and more than 10 years of continuous operation in the field, has given you the UGuard AI information security warfare platform. With the industry's most powerful big data engine leader Splunk Enterprise as the main processing core, its No-SQL technology can significantly improve the traditional security information event management (SIEM) solutions in processing performance loss and slow response time bottlenecks. It enables enterprises to proactively monitor, target, address and deter information security attacks by enabling early detection and prediction of hacker threats."
Graphical dashboards and security weather maps present security status to help security managers predict and take preventive measures in advance.
Through big data algorithm capability and intelligent event association engine, we can discover and actively list unknown possible threats from seemingly irrelevant information.
Through historical retrieval and trajectory data analysis, we can understand the real time point of hacker intrusion and detect the latent and silent abnormal changes in advance.
Through AI s intelligent rule-based approach, we can detect behavioral anomalies in specific devices, such as mass connection, password guessing, abnormal account login, abnormal network connection, etc.
Through big data algorithm capability and AI intelligent event correlation engine, machine learning is used to build a baseline to discover and proactively list unknown possible threats from seemingly irrelevant information.