Enhanced Attribution 

Office: Defense Advanced Research Projects Agency (DARPA)
Research Solicitation Number: DARPA-BAA-16-34


Synopsis:  Added: Apr 22, 2016 4:49 pm

DARPA is soliciting innovative research proposals in the area of cyber 
attribution. 

The goal of the Enhanced Attribution (EA) program is to develop technologies 
for generating operationally and tactically relevant information about multiple 
concurrent independent malicious cyber campaigns, each involving several 
operators; and the means to share such information with any of a number of 
interested parties without putting at risk the sources and methods used for 
collection. 

Proposed research should investigate innovative approaches that enable 
revolutionary advances in science, devices, or systems. 

Point of Contact: [email protected] 

Ref: 
https://www.fbo.gov/index?s=opportunity&mode=form&id=93c091efb6a2252556aa8530cdce71ed&tab=core&tabmode=list&=
Additional PDF: 
https://www.fbo.gov/utils/view?id=138959e641d75afda40b9bedb5ec8d2b


DARPA BAAs are posted on the Federal Business Opportunities (FBO) website 
(https://www.fbo.gov/).

The following information is for those wishing to respond to this BAA. 

Background

Malicious actors in cyberspace currently operate with little fear of being 
caught due to the fact that it is extremely difficult, in some cases perhaps 
even impossible, to reliably and confidently attribute actions in cyberspace to 
individuals.  The reason cyber attribution is difficult stems at least in part 
from a lack of end-to-end accountability in the current Internet 
infrastructure.  Cyber campaigns spanning jurisdictions, networks, and devices 
are only partially observable from the point of view of a defender that 
operates entirely in friendly cyber territory (e.g., an organization’s 
enterprise network).  The identities of malicious cyber operators are largely 
obstructed by the use of multiple layers of indirection.  The current 
characterization of malicious cyber campaigns based on indicators of 
compromise, such as file hashes and command-andcontrol infrastructure 
identifiers, allows malicious operators to evade the defenders and resume 
operations simply by superficially changing their tools, as well as aspects of 
their tactics, techniques, and procedures.  The lack of detailed information 
about the actions and identities of the adversary cyber operators inhibits 
policymaker considerations and decisions for both cyber and non-cyber response 
options (e.g., economic sanctions under EO-13694).

Program Scope

The Enhanced Attribution program aims to make currently opaque malicious cyber 
adversary actions and individual cyber operator attribution transparent by 
providing high-fidelity visibility into all aspects of malicious cyber operator 
actions and to increase the Government’s ability to publicly reveal the actions 
of individual malicious cyber operators without damaging sources and methods.

The program will develop techniques and tools for generating operationally and 
tactically relevant information about multiple concurrent independent malicious 
cyber campaigns, each involving several operators, and the means to share such 
information with any of a number of interested parties (e.g., as part of a 
response option).  

The program seeks to develop: 

 technologies to extract behavioral and physical biometrics from a range of 
devices and vantage points to consistently identify virtual personas and 
individual malicious cyber operators over time and across different endpoint 
devices and C2 infrastructures; 

 techniques to decompose the software tools and actions of malicious cyber 
operators into semantically rich and compressed knowledge representations; 

 scalable techniques to fuse, manage, and project such ground-truth 
information over time, toward developing a full historical and current picture 
of malicious activity; 

 algorithms for developing predictive behavioral profiles within the context 
of cyber campaigns; and 

 technologies for validating and perhaps enriching this knowledge base with 
other sources of data, including public and commercial sources of information

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