Operator Suspicion and Human-Machine Team Performance Under Mission Scenarios of Unmanned Ground Vehicle Operation

Operator Suspicion and Human-Machine Team Performance Under Mission Scenarios of Unmanned Ground Vehicle Operation

Blog Article

Emergent cyber-attack threats against cyber-physical systems can create potentially catastrophic impacts.The operators must intervene at the right moment when suspected attacks occur, without over-reliance on systems to detect the cyber-attacks.However, military operators are normally trained to trust, rather than suspect systems.We applied suspicion theory to explore how operators detect and respond to cyber-attacks against an unmanned ground vehicle (UGV) system in the operational context of a human-machine team (HMT).We investigated the relationships between the operator suspicion and HMT performance by conducting human-in-the-loop experiments on eight mission scenarios with 32 air-force officers.

The experiment yielded a significant, negative relationship between operator suspicion Vitamin K and HMT performance (quantified both in terms of the desirability of decision response and the time to respond).Notably, operator suspicion increased with the combined effects of cyber-attacks and a sentinel Longboards alert but not with the alert alone.This finding was particularly meaningful for “false-negative” scenarios, in which no sentinel alert was sent despite cyber-attacks having occurred.Although the operators did not receive an alert, the operators grew more suspicious, seeking more information; it took longer for the operators to respond, and their decision responses were highly divergent (17.2% came with less-desirable responses, and 21.

9% were considered instances of over-reliance).In contrast, in “false-positive” scenarios, 95.3% of the operator responses were highly desirable.This experiment has implications for the role of a sentinel alert in engineering trustworthy HMT systems so that the operators can quickly transition through state-suspicion to the most desirable decision.