US government and private sector developing ‘precrime’ system to anticipate cyber-attacks


Martin Anderson at The Stack: “The USA’s Office of the Director of National Intelligence (ODNI) is soliciting the involvement of the private and academic sectors in developing a new ‘precrime’ computer system capable of predicting cyber-incursions before they happen, based on the processing of ‘massive data streams from diverse data sets’ – including social media and possibly deanonymised Bitcoin transactions….
At its core the predictive technologies to be developed in association with the private sector and academia over 3-5 years are charged with the mission ‘to invest in high-risk/high-payoff research that has the potential to provide the U.S. with an overwhelming intelligence advantage over our future adversaries’.
The R&D program is intended to generate completely automated, human-free prediction systems for four categories of event: unauthorised access, Denial of Service (DoS), malicious code and scans and probes which are seeking access to systems.
The CAUSE project is an unclassified program, and participating companies and organisations will not be granted access to NSA intercepts. The scope of the project, in any case, seems focused on the analysis of publicly available Big Data, including web searches, social media exchanges and trawling ungovernable avalanches of information in which clues to future maleficent actions are believed to be discernible.
Program manager Robert Rahmer says: “It is anticipated that teams will be multidisciplinary and might include computer scientists, data scientists, social and behavioral scientists, mathematicians, statisticians, content extraction experts, information theorists, and cyber-security subject matter experts having applied experience with cyber capabilities,”
Battelle, one of the concerns interested in participating in CAUSE, is interested in employing Hadoop and Apache Spark as an approach to the data mountain, and includes in its preliminary proposal an intent to ‘de-anonymize Bitcoin sale/purchase activity to capture communication exchanges more accurately within threat-actor forums…’.
Identifying and categorising quality signal in the ‘white noise’ of Big Data is a central plank in CAUSE, and IARPA maintains several offices to deal with different aspects of it. Its pointedly-named ‘Office for Anticipating Surprise’  frames the CAUSE project best, since it initiated it. The OAS is occupied with ‘Detecting and forecasting the emergence of new technical capabilities’, ‘Early warning of social and economic crises, disease outbreaks, insider threats, and cyber attacks’ and ‘Probabilistic forecasts of major geopolitical trends and rare events’.
Another concerned department is The Office of Incisive Analysis, which is attempting to break down the ‘data static’ problem into manageable mission stages:
1) Large data volumes and varieties – “Providing powerful new sources of information from massive, noisy data that currently overwhelm analysts”
2) Social-Cultural and Linguistic Factors – “Analyzing language and speech to produce insights into groups and organizations. “
3) Improving Analytic Processes – “Dramatic enhancements to the analytic process at the individual and group level. “
The Office of Smart Collection develops ‘new sensor and transmission technologies, with the seeking of ‘Innovative approaches to gain access to denied environments’ as part of its core mission, while the Office of Safe and Secure Operations concerns itself with ‘Revolutionary advances in science and engineering to solve problems intractable with today’s computers’.
The CAUSE program, which attracted 150 developers, organisations, academics and private companies to the initial event, will announce specific figures about funding later in the year, and practice ‘predictions’ from participants will begin in the summer, in an accelerating and stage-managed program over five years….(More)”