Date of Award


Document Type


Degree Name

Master of Science in Computer Engineering


Department of Electrical and Computer Engineering

First Advisor

Patrick J. Sweeney, PhD


This research introduces SLIVer, a Simulation-based Logic Bomb Identification/Verification methodology, for finding logic bombs hidden within Unmanned Aerial Vehicle (UAV) autopilot code without having access to the device source code. Effectiveness is demonstrated by executing a series of test missions within a high-fidelity software-in-the-loop (SITL) simulator. In the event that a logic bomb is not detected, this methodology defines safe operating areas for UAVs to ensure to a high degree of confidence the UAV operates normally on the defined flight plan. SLIVer uses preplanned flight paths as the baseline input space, greatly reducing the input space that must be searched to have confidence that the UAV will not encounter a logic bomb trigger condition during its mission. This research discusses the process for creating a logic bomb in the ArduPilot autopilot software, creating test flight profiles, UAV log file parsing, and the analysis of the methodology. SLIVer can accommodate multiple flight profiles and parses through the corresponding log files to create a safety corridor through which the UAV is able to safely traverse through with a desired level of confidence. By utilizing SLIVer, UAV operators and planners alike are afforded increased confidence that the aircraft will operate normally throughout the duration of a mission. The proof of concept implementation shows that the input space required to validate a UAV mission is reduced by approximately 60%, a far better result than brute force input testing. As UAVs are continually called upon to fill critical civilian and military roles, it is essential that planners and users of these devices have a methodology in place to assure that logic bombs are absent from the device.

AFIT Designator