Millions of automobiles with the same model could be recalled due to a cascading effect if attackers acquire the execution flow of an automotive application. To mitigate the scaling across effects induced by attacks, several security-aware obfuscated priority assignments have been proposed recently. Although these techniques can handle low-payload controller area network (CAN) messages in a nonparallel automotive application, they are unsuitable for the next generation high-bandwidth in-vehicle network architecture and parallel execution of complex safety-critical applications. In this article, we develop a new security-aware obfuscated priority assignment approach which explores CAN with flexible data-rate (CAN FD) messages in a parallel automotive application. Specifically, we propose a fast sequence pruning (FSP) technique for exploring head-based sequence pruning (HSP) and tail-based sequence pruning (TSP). Experiments with real-life parallel automotive application show that FSP can efficiently obtain millions of obfuscated priority assignments, which significantly mitigates the scaling across effects.