SKYNET (surveillance program)

SKYNET is a program by the U.S. National Security Agency that performs machine learning analysis on communications data to extract information about possible terror suspects. The tool is used to identify targets, such as al-Qaeda couriers, who move between GSM cellular networks. These couriers often swap SIM cards within phones that have the same ESN, MEID or IMEI number. The tool uses classification techniques like random forest analysis. Because the data set includes a very large proportion of true negatives and a small training set, there is a risk of overfitting. Bruce Schneier argues that a false positive rate of 0.008% would be low for commercial applications where "if Google makes a mistake, people see an ad for a car they don't want to buy" but "if the government makes a mistake, they kill innocents."

Participation and Partnerships

NSA directorates participating:

• Signals Intelligence: S21, S22, SSG
• Research: R6
• Technology: T12, T14

It has partnerships with TMAC/FASTSCOPE, MIT Lincoln labs and Harvard.

See also

• Global surveillance

Further reading

• http://arstechnica.co.uk/security/2016/02/the-nsas-skynet-program-may-be-killing-thousands-of-innocent-people/
• https://theintercept.com/document/2015/05/08/skynet-applying-advanced-cloud-based-behavior-analytics/
• https://theintercept.com/2015/12/18/erroneous-claims-made-about-basic-classification-data-in-the-intercepts-spy-gear-documents/