福建电脑2026，Vol.42Issue(3)：35-42,8.DOI:10.16707/j.cnki.fjpc.2026.03.007
模型上下文协议安全工具参数优化
Parameter Optimization for MCP-based Security Tools
张云飞1
作者信息
- 1. 上海信息安全技术支持中心有限公司 上海 200011
- 折叠
摘要
Abstract
To address the inefficiency caused by fixed parameters in security tool integration within model context protocols,this paper proposes a context-aware parameter adaptive optimization method.The approach employs a three-layer optimization mechanism incorporating target type awareness,network latency adaptation,and historical data learning to dynamically adjust tool parameters.A 500-line Python optimization module was implemented on the HexStrike AI v6.0 platform for parameter optimization of security tools such as Nmap.Experiments show that this method reduces the average execution time from 315 seconds to 188 seconds,improving efficiency by 40.3%,while decreasing the standard deviation of execution time by 61.5%.The success rate increased from 90.0%to 97.5%,with Web server optimization time reduced by 75.6%and port hit rate improved by 50 times.关键词
参数自适应优化/上下文感知/安全工具集成Key words
Parameter Adaptive Optimization/Context Aware/Security Tool Integration分类
信息技术与安全科学引用本文复制引用
张云飞..模型上下文协议安全工具参数优化[J].福建电脑,2026,42(3):35-42,8.
