Temporal Analytics for Predictive Cyber Threat Intelligence
Pages 867 - 868
Abstract
Recorded Future has developed its Temporal Analytics Engine as a general purpose platform for harvesting and analyzing unstructured text from the open, deep, and dark web, and for transforming that content into a structured representation suitable for different analyses.
In this paper we present some of the key components of our system, and show how it has been adapted to the increasingly important domain of cyber threat intelligence.
We also describe how our data can be used for predictive analytics, e.g. to predict the likelihood of a product vulnerability being exploited or to assess the maliciousness of an IP address.
Reference
[1]
M. Edkrantz and A. Said. Predicting cyber vulnerability exploits with machine learning. In Scandinavian Conference on Artificial Intelligence, pages 48--57, 2015.
Index Terms
- Temporal Analytics for Predictive Cyber Threat Intelligence
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Information & Contributors
Information
Published In
April 2016
1094 pages
ISBN:9781450341448
- General Chairs:
- Jacqueline Bourdeau,
- Jim A. Hendler,
- Roger Nkambou Nkambou,
- Program Chairs:
- Ian Horrocks,
- Ben Y. Zhao
Copyright © 2016 Copyright is held by the International World Wide Web Conference Committee (IW3C2).
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- IW3C2: International World Wide Web Conference Committee
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International World Wide Web Conferences Steering Committee
Republic and Canton of Geneva, Switzerland
Publication History
Published: 11 April 2016
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WWW '16
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- IW3C2
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WWW '16 Companion Paper Acceptance Rate 115 of 727 submissions, 16%;
Overall Acceptance Rate 1,899 of 8,196 submissions, 23%
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