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.
Specifically, mobile usage patterns such as swapping SIM cards within phones that have the same ESN, MEID or IMEI number are deemed indicative of covert activities.
[1][5] According to NSA, the SKYNET project is able to accurately reconstruct crucial information about the suspects including their social relationships, habits, and patterns of movements through graph-based visualization of GSM data.
[3] However, scholars criticize that current security literature conflate statistical discrepancies with behavioral abnormalities and that the anomaly detection methodology SKYNET perpetuates the self/other binary.
[6] For example, Al-Jazeera's bureau chief in Islamabad, Ahmad Zaidan, was wrongly identified as the most probable member of al-Qaeda and the Muslim Brotherhood on their records.