Resources  >  Research  >  Article


Artificial-Intelligence Based Endpoint Defender


Digital documents pose a serious cybersecurity threat to US critical networks since they can contain embedded code that may compromise a computer when the document is opened.

Automated File Anomaly Detection

Artificial-Intelligence Based Endpoint Defender (ABED) is an Air Force Research Laboratory funded product that uses advanced machine learning and artificial intelligence techniques to automatically model normal behavior of document viewers to quickly identify suspect documents before they compromise your network. Unlike complex parsers that take years to build and require reverse engineering of complex file formats, ABED can model the expected behavior of new file formats in hours, creating a baseline for effectively identifying malicious documents. ABED is a Phase II SBIR sponsored by the United States Air Force.

Key Insights:

  • Automated learning capability quickly categorizes new file formats
  • Simple to use API
  • Low false positive rate (less than one percent)
  • US Patent Pending

Ready to Get Started?

Reach out to talk to one of our experts and learn more about our research initiatives.

Privacy Settings
We use cookies to enhance your experience while using our website. If you are using our Services via a browser you can restrict, block or remove cookies through your web browser settings. We also use content and scripts from third parties that may use tracking technologies. You can selectively provide your consent below to allow such third party embeds. For complete information about the cookies we use, data we collect and how we process them, please check our Privacy Policy
Consent to display content from - Youtube
Consent to display content from - Vimeo
Google Maps
Consent to display content from - Google
Consent to display content from - Spotify
Sound Cloud
Consent to display content from - Sound