Cyber Early Warning System (CEWAS)

Abstract

Telcordia has developed innovative technology for the detection of packets with fictitious source IP addresses in large IP networks (e.g. NIPRNet). We present the predictive Ingress Filtering (InFilter) approach for network-based detection of spoofed IP packets near the target of cyber-attacks. Our InFilter hypothesis states that traffic entering an IP network from a specific source frequently uses the same ingress point. We have empirically validated this hypothesis by analysis of 41,000 trace-routes to 20 Internet targets from 24 Looking-Glass sites, and 30-days of Border Gateway Protocol-derived path information for the same 20 targets. We have developed a system architecture and software implementation based on the InFilter approach that can be used at Border Routers of large IP networks to detect spoofed IP traffic. Extensive experimentation revealed that CEWAS exhibited a detection rate of between 80 and 100%, depending on the attack frequency. The false positive rate for CEWAS was typically around 1.6% of all observed traffic in the target network. Both these metrics compare favorably with state-of-the-art in Intrusion Detection Systems that do not use signatures of attacks. The project has resulted in two research papers being published in high-quality peer-reviewed conferences, in addition to a patent-application.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2006
Accession Number
ADA449253

Entities

People

  • Abhrajit Ghosh
  • Rajesh Talpade

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Computer Networks
  • Computing System Architectures
  • Cyberattacks
  • Cybersecurity
  • Denial Of Service Attack
  • Detection
  • Detectors
  • Early Warning Systems
  • Graphical User Interface
  • Intrusion Detection
  • Intrusion Detection Systems
  • Intrusion Detectors
  • Network Protocols
  • Routing Protocols
  • User Interface
  • Warning Systems

Fields of Study

  • Computer science

Readers

  • Cybersecurity.
  • Materials Science and Engineering.
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • Cyber