计算机科学 ›› 2022, Vol. 49 ›› Issue (11): 351-359.doi: 10.11896/jsjkx.220400285
何源, 邢长友, 张国敏, 宋丽华, 余航
HE Yuan, XING Chang-you, ZHANG Guo-min, SONG Li-hua, YU Hang
摘要： 网络指纹探测作为一种重要的网络侦察手段,可以被攻击者用于获取目标网络的指纹特征,进而为后续开展有针对性的攻击行动提供支持。指纹混淆技术通过主动修改响应分组中的指纹特征,能够让攻击者形成虚假的指纹视图,但现有的混淆方法在应对攻击者策略性探测分析方面仍存在不足。为此,提出了一种面向网络侦察欺骗的差分隐私指纹混淆机制(Differential Privacy based Obfuscation of Fingerprinting,DPOF)。DPOF参考数据隐私保护的思想,首先建立了效用驱动的差分隐私指纹混淆模型,通过差分隐私指数机制计算不同效用虚假指纹的混淆概率,在此基础上进一步设计了资源约束下的指纹混淆决策方法,并实现了基于粒子群优化的混淆策略求解算法。仿真实验结果表明,相比现有的典型指纹混淆方法,DPOF在不同问题规模和预算情况下均具有更优的指纹混淆效果,且能够以更快的速度获得更好的近似最优策略。
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