Enterprise Threat Detection: Tuning, Triage, and Analysis by Experts.
Company is closed
Event Year: 2015
Company is closed
Event Year: 2015
Traversal Networks was dedicated to pioneering a novel Network Intrusion Detection System (NIDS) engineered to identify and neutralize emerging, previously unknown threats within enterprise networks. Their core offering, the Lateral Threat Detector, comprised easily deployable appliances designed for seamless integration into corporate networks. These analyst-assisted sensors were designed to intelligently learn typical traffic patterns specific to each network segment, enabling the detection of lateral movement, backdoors, botnet activity, malware infections, and reconnaissance attempts.
The Traversal Networks platform operated on a multi-faceted approach, leveraging machine learning, reputation analysis, advanced search capabilities, and continuous learning.
By combining real-world network data with specialized expertise in botnet detection, Traversal Networks developed sophisticated heuristics to effectively filter malicious traffic. Furthermore, the system incorporated IP and DNS reputation data gathered across all deployed devices to proactively identify and respond to new and evolving threats.
The Lateral Threat Detector appliances employed reinforcement learning techniques to continuously optimize filtering performance on each network segment. The system also submitted anonymized data to a cloud platform, enabling rapid, real-time search and analysis.
The Traversal Cloud Analysis platform was specifically built to empower security analysts to efficiently investigate anomalous network traffic and accurately classify it as either malicious or benign.
Traversal Networks was dedicated to pioneering a novel Network Intrusion Detection System (NIDS) engineered to identify and neutralize emerging, previously unknown threats within enterprise networks. Their core offering, the Lateral Threat Detector, comprised easily deployable appliances designed for seamless integration into corporate networks. These analyst-assisted sensors were designed to intelligently learn typical traffic patterns specific to each network segment, enabling the detection of lateral movement, backdoors, botnet activity, malware infections, and reconnaissance attempts.
The Traversal Networks platform operated on a multi-faceted approach, leveraging machine learning, reputation analysis, advanced search capabilities, and continuous learning.
By combining real-world network data with specialized expertise in botnet detection, Traversal Networks developed sophisticated heuristics to effectively filter malicious traffic. Furthermore, the system incorporated IP and DNS reputation data gathered across all deployed devices to proactively identify and respond to new and evolving threats.
The Lateral Threat Detector appliances employed reinforcement learning techniques to continuously optimize filtering performance on each network segment. The system also submitted anonymized data to a cloud platform, enabling rapid, real-time search and analysis.
The Traversal Cloud Analysis platform was specifically built to empower security analysts to efficiently investigate anomalous network traffic and accurately classify it as either malicious or benign.
Total Raised: Unknown (Y Combinator backed)
Last Round: Summer 2015
Total Raised: Unknown (Y Combinator backed)
Last Round: Summer 2015
B2B
B2B
B2B -> Security
B2B -> Security
Team size: 1
Hiring: No
Team size: 1
Hiring: No
