摘要
自动化渗透测试通过将人工找寻可能攻击路径的过程自动化,可大幅降低渗透测试的成本。现有方法主要利用单一Agent执行攻击任务,导致攻击动作执行耗时长,渗透效率不高;若考虑多个Agent协同攻击,由于每个Agent的局部状态有多个维度,总的规划问题的状态空间会呈指数级增长。针对上述问题,提出了基于多Agent联合决策的队组协同攻击规划方法。该方法首先将多Agent协同攻击路径规划问题转化为联合决策约束下的攻击目标分配问题,建立多Agent集中决策模式;然后以CDSO-CAP为模型基础,利用联合决策矢量矩阵JDVM计算渗透攻击奖励,并采用贪婪策略搜索多Agent的最优攻击目标。实验结果表明,与单Agent规划方法相比,该方法的收敛性相近,但执行轮次更短,更适合在多目标网络场景内进行快速攻击规划。
Automated penetration testing can greatly reduce the cost of penetration testing by automating the process of manually finding possible attack paths.Existing methods mainly use a single agent to perform attack tasks,which leads to long execution of attack actions and low penetration efficiency.If multi-agent cooperative attack is considered,the state space scale of planning problem will grow exponentially due to the multi-dimensional local state of each agent.Aiming at the above problems,a team cooperative attack planning method based on multi-agent jointdecision is proposed.Firstly,the multi-agent cooperative attack path planning problem is transformed into the attack target assignment problem under the jointdecision constraints,and the multi-agent centralized decision-making mode is established.Secondly,the joint decision vector matrix JDVM is used to calculate the penetration attack reward based on the CDSO-CAP model,and the greedy strategy is used to search the optimal target of attack.The experimental results show that compared with the single agent planning method,the proposed method has similar algorithm convergence with shorter execution rounds.Thus it is more suitable for rapid attack planning in multi-target network scenarios.
作者
周天阳
曾子懿
臧艺超
王清贤
ZHOU Tian-yang;ZENG Zi-yi;ZANG Yi-chao;WANG Qing-xian(Information Engineering University,Zhengzhou 450001,China;National Digital Switching System Engineering&Technological Research Center,Zhengzhou 450001,China)
出处
《计算机科学》
CSCD
北大核心
2021年第5期301-307,共7页
Computer Science
关键词
渗透测试
自动化
攻击规划
智能体
联合决策
队组协同
Penetration test
Automation
Attack planning
Agent
Joint decision
Team collaboration
