Army network needs digital twin for training, testing, cybersecurity: NETCOM chief

Breaking Defense | Sydney J. Freedberg Jr.

The United States Army Network Command is calling on defense contractors to construct a digital twin simulation of the Department of Defense Information Network – Army to train personnel, test artificial intelligence algorithms, and harden network cybersecurity. Speaking at AFCEA’s TechNet Augusta conference, NETCOM commander Maj. Gen.

Jacqueline Denise McPhail highlighted that the service currently defends against 1.2 million cyber attacks daily, which have evolved beyond traditional denial-of-service tactics toward stealthy behavioral alterations. Integrating live operational data into a virtual network model will enable military cyber defenders to isolate anomalies from background noise, evaluate architectural vulnerabilities, and verify structural resilience under simulated combat conditions without risking live systems. Although official Pentagon policy historically restricts digital twin frameworks to physical hardware platforms, applying high-fidelity simulation to software-defined enterprise network infrastructure represents a vital initiative to anticipate adversarial intrusion and preserve operational command-and-control capabilities across contested warfighting environments.

Comment

Simulating software-defined behaviour across the Department of Defense Information Network – Army (DoDIN-A) marks a shift from static perimeter defence to dynamic telemetry baselining. Because modern adversary tactics exploit legitimate administrative credentials and low-observable lateral movement, static intrusion detection signatures fail to capture unauthorized behavioural shifts. By mirroring live network traffic across NETCOM nodes, a functional digital twin establishes a high-fidelity operational baseline for algorithmic anomaly detection. This synthetic environment allows automated defence models to isolate malicious behavioural deviations without exposing operational command nodes to live malware payloads.

Furthermore, integrating this synthetic baseline into the US Army's Persistent Cyber Training Environment provides defensive cyber protection teams with realistic operational friction during simulated hostile intrusions. Operators can stress-test response protocols against automated threat agents in an emulated DoDIN-A topology without risking service degradation across active tactical formations. Consequently, integrating live telemetry into the Persistent Cyber Training Environment transforms reactive logging into predictive threat hunting across DoDIN-A enterprise nodes.

Strategic Question for Discussion

If synthetic network models like the DoDIN-A digital twin are integrated into the Persistent Cyber Training Environment, does the speed of automated AI threat response risk outrunning human command-and-control authority during high-tempo cyber intrusions?

The trajectory of high-volume cyber warfare indicates that human operators will struggle to maintain real-time oversight when defending complex architectures against automated exploits. Integrating AI agents into DoDIN-A emulations suggests that military doctrine will increasingly favor pre-authorized algorithmic responses for immediate threat containment. This development shifts human decision-making from tactical interdiction to strategic policy oversight, redefining operational control across defense networks.

Share your assessment in the comments below.

To read in details click here