With the emergence of the Internet of Things (IoT), a large number of physical\nobjects in daily life have been aggressively connected to the Internet. As the number of\nobjects connected to networks increases, the security systems face a critical challenge due\nto the global connectivity and accessibility of the IoT. However, it is difficult to adapt\ntraditional security systems to the objects in the IoT, because of their limited computing\npower and memory size. In light of this, we present a lightweight security system that uses\na novel malicious pattern-matching engine. We limit the memory usage of the proposed\nsystem in order to make it work on resource-constrained devices. To mitigate performance\ndegradation due to limitations of computation power and memory, we propose two novel\ntechniques, auxiliary shifting and early decision. Through both techniques, we can efficiently\nreduce the number of matching operations on resource-constrained systems. Experiments\nand performance analyses show that our proposed system achieves a maximum speedup of\n2.14 with an IoT object and provides scalable performance for a large number of patterns.
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