AI-ML Powered Threat Intelligence

Stay ahead of threats with AI-powered machine learning intelligence for comprehensive security


In today's increasingly sophisticated, zero-day malware landscape, threat detection that uses Artificial Intelligence (AI) is no longer an optional part of an organization's network security strategy. Security effectiveness depends on threat intelligence above all else. Harnessing the power of AI and ML, our cutting-edge technologies offer insightful analysis of DNS traffic, enabling effective detection and mitigation of modern security threats. The best way to reduce risks and detect and mitigate threats in real-time using AI-ML is to deploy TCPWave's AI ML-based Threat Intelligence. Using TCPWave's AI ML-based threat intelligence, network and security teams can have real-time protection by applying industry-first protections to disrupt attacks that use DNS. It protects networks and data while increasing productivity and efficiency.

Our solution is customized to meet your organization's specific needs and uses AI-ML algorithms to detect and respond to threats in real-time. In addition to detecting and responding to threats, the solution continuously monitors the security of your system, ensuring that it remains secure. It blocks malicious site access, command-and-control communications, and other malicious activities to strengthen the entire security ecosystem.

Our AI-ML-driven technology helps identify and auto block a source to detect anomalous traffic.
Learn to spot and close any open ports that could expose network vulnerabilities. Open ports have the potential to substantially undermine the security of a network inside an organisation.
Help organizations across all sectors to combat cyberattacks and mitigate the damage of security incidents.
Additionally, TCPWave's Advanced Threat Intelligence dashboard provides a visual representation of relevant information that helps organizations identify, analyze, and respond to potential cybersecurity threats.

Featured Resources

TCPWave DDI - Atlantis Model

Learn more about TCPWave's DNS TITAN A Atlantis, out first-ever Deep Learning model based on cutting-edge research that detects and mitigates the DNS anomalies.

TCPWave DDI - XGBoost Model Dashboard

TCPWave's DNS TITAN is upgraded with the state-of-the art ML model - XGBoost with improved accuracy and performance. Learn how to detect and mitigate the DNS anomalies with the TCPWave's ML model XGBoost.

TCPWave DDI - DNS Blackhole ACL

The use od ACL's is one of the network security practices that can protect the organization's network. Learn more about auto-blocking malicious traffic using the DNS Blackhole ACL mechanism in the TCPWave application.

TCPWave DDI - Forecasting Charts Using Machine Learning

Forecasting plays a significant role as it helps in planning the resources utilization and formulate organization plans. Learn more about forecasting the performance metrics using the SARIMA model within the TCPWave IPAM application.