Use Case II
Cybersecurity and Analysis
About
Outcomes
Integrate with a myriad of data sources and feeds, allowing for real time updates on the latest cybersecurity threats and vulnerabilities. Ensuring timely awareness and proactive mitigations.
Leveraging machine learning, we can analyze data from multiple sources, including network logs, security events, and user behavior. This enables the detection of anomalous activities, potential intrusions, and sophisticated attacks.
Streamline incident response by automating routine tasks such as threat identification, incident triaging, and containment. This reduces response time and minimize the impact of security incidents.
Gain full visibility and control of your network infrastructure with real-time monitoring of network traffic, system logs, and application behavior. Identify potential vulnerabilities, track suspicious activities, and proactively address issues before they are impacts.
Challenges
Vulnerability Insight
Visualize network traffic through heat maps and help predict vulnerabilities through continuous scanning and identification. Alert and assist in known CVES remediation.
Behavioral Analysis
Know and understand spikes in unusual traffic from known entities. Detect insider threat or external threats through tipping and queueing on traced network traffic.
Real Time Identification and Remediation
Follow and acknowledge known attack vectors through machine learning. Short circuit attacks by identifying and defending the network through threat reduction.
Volume Data Analysis
Pay attention to all actions instead of prioritized network traffic or networked hardware.
Results
Provide central awareness of infrastructure, usage and mission capabilities through a managed web application; know thyself.