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"U.S. government spending on big data to grow exponentially."
Wide Area Network Detection (WAND)
The WAND program will enable the detection, identification, localization, tracking, and estimation of threats and threat networks over wide areas and in settings with high population densities. To achieve this goal, WAND will develop automated processing techniques that integrate wide area motion imagery (WAMI) with other sensor data and combine this sensor information with HUMINT-derived and other prior threat network information. WAND tools will enable users to visualize sensor data, track information, threat network attributes and estimates, and sensor resource allocations. WAND will also provide users with the capability to actively manage sensing resources and to prioritize information collection activities.
U.S. government spending on big data to grow exponentially
By Rawlson King
August 9, 2013 -
Biometrics Research Group, Inc. has observed that national security and military applications are driving a large proportion of “Big Data” research spending.
Big Data is a term used to describe large and complex data sets that can provide insightful conclusions when analyzed and visualized in a meaningful way. Conventional database tools do not have capabilities to manage large volumes of unstructured data. The U.S. Government is therefore investing in programs to develop new tools and technologies to manage highly complex data. The basic components of Big Data include hardware, software, services and storage.
Biometrics Research Group estimates that federal agencies spent approximately US$5 billion on Big Data resources in the 2012 fiscal year. We estimate that annual spending will grow to US$6 billion in 2014 and then to US$8 billion by 2017 at a compound annual growth rate of 10 percent. Our industry analysis projects that most of this spending will be directed through the military apparatus of the U.S. government in the near to midterm. Currently, federal agencies are pursuing over 150 Big Data projects involving procurements, grants or related activities.
Reminiscent of the emergence of the Internet, Big Data research is being mainly driven by the military establishment, with over 30 projects led by the U.S. Department of Defense. Specifically, the Defense Advanced Research Projects Agency (DARPA) is leading nine major projects focused on algorithmic improvement, espionage and surveillance. Some DARPA Big Data projects are also attempting to make improvements to natural speech recognition and video and image retrieval systems.
DARPA’s Anomaly Detection at Multiple Scales (ADAMS) program addresses the problem of anomaly detection and characterization in massive data sets. In this context, anomalies in data are intended to cue collection of additional, actionable information in a wide variety of real-world contexts. The initial ADAMS application domain is insider threat detection, in which anomalous actions by an individual are detected against a background of routine network activity.
The Cyber-Insider Threat (CINDER) program seeks to develop novel approaches to detect activities consistent with cyber espionage in military computer networks. As a means to expose hidden operations, CINDER will apply various models of adversary missions to “normal” activity on internal networks. CINDER also aims to increase the accuracy, rate and speed with which cyber threats are detected.
The Insight program addresses key shortfalls in current intelligence, surveillance and reconnaissance systems. Automation and integrated human-machine reasoning enable operators to analyze greater numbers of potential threats ahead of time-sensitive situations. The Insight program aims to develop a resource management system to automatically identify threat networks and irregular warfare operations through the analysis of information from imaging and non-imaging sensors and other sources.
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