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CLAD: Classification Labeling of Aggregated Data

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8750-10-C-0082
Agency Tracking Number: F083-040-0776
Amount: $746,472.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: AF083-040
Solicitation Number: 2008.3
Solicitation Year: 2008
Award Year: 2010
Award Start Date (Proposal Award Date): 2010-04-22
Award End Date (Contract End Date): 2012-04-20
Small Business Information
4515 Seton Center Parkway Suite 320
Austin, TX -
United States
DUNS: 158034665
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: Yes
Principal Investigator
 Laura Hitt
 Principal Investigator
 (512) 342-0010
Business Contact
 Irene Williams
Title: CEO
Phone: (512) 342-0010
Research Institution

21st Century Technologies (21CT) proposes the Classification Labeling of Aggregated Data (CLAD) Phase 2 effort. CLAD addresses three key challenges in maintaining secure access of documents: 1) ensuring that all documents are properly labeled according to the most current guidelines, 2) providing a security classification level for a collection of documents, for which the aggregation of information could result in a higher classification level than any of the individual documents, and 3) preventing unauthorized visibility of a collection of documents when the collection’s aggregated classification exceeds the user’s credentials or system’s certification and accreditation. CLAD provides a secure web service to ensure that all data passing through it is clad with appropriate labels or routed to another service to gather appropriate labeling so that the most accurate classification is maintained. CLAD balances the need to quickly and securely disseminate information to those with need-to-know based on credentials, and without leaking sensitive data. This ultimately supports the goal of allowing the analysts to discover and retrieve as much information as needed to perform their jobs efficiently and effectively, without compromising individual and national security. BENEFIT: CLAD provides two substantial improvements to the current methodology for marking and classifying documents – an automated label completion verifier and an automated aggregation classifier. Having these two components as an automated tool enables a more uniform implementation of markings and classifications, a more efficient determination of errors, and a decrease in costs. CLAD provides assurance that all data passing to the user is clad with appropriate labels, and provides automated detection of situations when the combination of information in documents causes the aggregation’s security classification to increase beyond that of any individual document in the collection. The CLAD functionality is carried out via a secure web service capable of scaling into an enterprise environment, and allows analysts access to as much information as possible without violation of security requirements on classified data, so they may perform their missions efficiently and effectively.

* Information listed above is at the time of submission. *

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