An analytics-driven security fabric is a comprehensive and interconnected system that leverages advanced analysis and data-driven insights to enhance cybersecurity across an organization’s network. It combines various security technologies, tools, and processes into a unified framework to provide a more proactive and effective approach to detecting, preventing, and responding to cyber threats.
The key components of this security fabric include data collection from various security-related sources, such as network devices, endpoints, applications, logs, and external threat intelligence feeds. Data aggregation and correlation consolidate and correlate the collected data to identify patterns, relationships, and anomalies that might indicate potential security incidents or vulnerabilities.
AI-enabled cybersecurity boosts an analytics-driven security fabric
AI benefits a security fabric by providing advanced analytics and machine learning that efficiently sorts through vast amounts of data produced by security tools, pinpointing any abnormalities, and assessing the information from thousands of sources. This includes newly connected assets that flood the network. AI is trained to distinguish between legitimate and malicious files, connections, devices, and users. AI-driven network and asset mapping and visualization provide a real-time understanding of expanding enterprise attack surfaces. It can identify and classify currently in-use assets, including those in containers, which can help detect any suspicious activity.
Integrating external threat intelligence feeds enriches the analysis and enhances threat detection. Advanced analytical techniques, such as artificial intelligence, machine learning, and behavioral analytics may then be applied. These techniques can analyze the data and identify security threats, suspicious activities, and potential vulnerabilities for mitigation as needed.
Automated orchestration and response enables continuous monitoring of the network and security infrastructure in real-time, generating alerts or notifications when abnormal or malicious activities are detected. By implementing automated response mechanisms to mitigate and contain security incidents in real-time, manual intervention and response time are reduced. Providing intuitive visualizations and reports to security teams and stakeholders enables them to understand the security posture, identify trends, and make informed decisions. Integrating with existing security technologies, such as firewalls, endpoint protection, and security information and event management (SIEM), creates a unified security ecosystem. Leveraging analytics and automation helps security teams stay ahead of evolving threats and minimize the impact of potential security breaches.
Cross-functional security with a unified dashboard simplifies forensics
RevBits Cyber Intelligence Platform (CIP) collects, processes, and preserves security data through its five security products. These include Endpoint Security, Email Security, Privileged Access Management, Zero Trust Network, and Deception Technology. The RevBits CIP unified dashboard provides a 360-degree view to analyze multi-vector cyberattack evidence. RevBits security products exchange intelligence to uncover the digital evidence analysts need to optimize detection and rapidly mitigate events.
Learn how RevBits analytics-driven cybersecurity products can be your best defense for protecting corporate assets today and into the future.
Originally Published on www.revbits.com
