Tairan Hu1, Tianyang Zhou1, Yichao Zang1, *, Qingxian Wang1, Hang Li2
CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1795-1807, 2020, DOI:10.32604/cmc.2020.011071
Abstract With serious cybersecurity situations and frequent network attacks, the demands
for automated pentests continue to increase, and the key issue lies in attack planning.
Considering the limited viewpoint of the attacker, attack planning under uncertainty is
more suitable and practical for pentesting than is the traditional planning approach, but it
also poses some challenges. To address the efficiency problem in uncertainty planning, we
propose the APU-D* Lite algorithm in this paper. First, the pentest framework is mapped
to the planning problem with the Planning Domain Definition Language (PDDL). Next,
we develop the pentest information graph to organize network information and… More >
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