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EdgeHawk Security

EdgeHawk Security provides a cloud-native platform that utilizes containerized detectors on network routers to analyze traffic legitimacy and mitigate DDoS and IoT attacks in real-time. By leveraging embedded compute resources, the solution enhances network visibility and response times while reducing the need for additional hardware.

Tel Aviv, IsraelFounded 202015300+ followers
Updated 4 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Product

Problem

Traditional network security solutions often struggle to keep pace with the evolving threat landscape, particularly distributed denial-of-service (DDoS) attacks and threats originating from IoT devices. Legacy scrubbing centers face scalability and cost challenges, while new network architectures like 5G and broadband access introduce additional attack surfaces.

Solution

EdgeHawk Security offers a cloud-native platform that leverages containerized detectors deployed on network routers to analyze traffic legitimacy and mitigate DDoS and IoT attacks in real-time. By utilizing spare CPU and memory resources on existing network infrastructure, EdgeHawk enhances network visibility and reduces the need for additional hardware appliances. The EdgeHawk Controller centrally manages detectors, providing security settings management, health monitoring, real-time attack insights, mitigation orchestration, and event reporting. This distributed architecture enables scalable and cost-effective security implementations, adapting to the dynamic nature of modern networks.

Target Audience

EdgeHawk's primary customers are Communication Service Providers (CSPs) seeking to enhance network security, improve visibility, and mitigate DDoS and IoT attacks across their infrastructure.

Features

  • Containerized detectors deployed on network routers for real-time traffic analysis
  • Centralized management controller for security settings, health monitoring, and attack insights
  • Patented anomaly detection algorithm based on fast, unsupervised machine learning
  • Spatial and near real-time comparison for rapid threat detection
  • Cloud-native platform built from clusters of containers for easy deployment and migration
  • Mitigation policies applied to router ingress ports using ACL rules
  • Support for Internet Exchange Points (IXPs), 5G networks, and broadband access networks
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