基于專家系統(tǒng)的高級持續(xù)性威脅云端檢測博弈
[Abstract]:Cloud computing system is an important target of advanced persistent threat to (advanced persistent threats,APT. It is difficult for automated APT detectors to detect APT attacks accurately. Using expert system to detect suspicious behavior twice can reduce the detection errors. However, it takes an extra period of time for the expert system to complete the secondary detection, which may lead to the delay of defense response, and the expert system itself will lead to misjudgment. On the basis of synthetically considering the false alarm rate and false alarm rate of APT detector and expert system, the necessity of using expert system to carry out secondary detection in APT detection and defense of cloud computing system is discussed by using game theory method. A scheme of APT detection based on expert system is designed, and a game model of ES-APT detection is proposed, and its Nash equilibrium is deduced. Based on this, the improvement of security performance of cloud computing system by expert system is studied. In addition, when the APT attack model can not be obtained, a reinforcement learning algorithm is proposed to obtain the optimal defense strategy. The simulation results show that the dynamic ES-APT detection scheme based on WoLF-PHC algorithm can improve the effectiveness of the defender and the security of cloud computing system compared with other control schemes.
【作者單位】: 中國科學(xué)院大學(xué)網(wǎng)絡(luò)空間安全學(xué)院;物聯(lián)網(wǎng)信息安全技術(shù)北京市重點(diǎn)實(shí)驗(yàn)室(中國科學(xué)院信息工程研究所);廈門大學(xué)通信工程系;
【基金】:國家重點(diǎn)研發(fā)計(jì)劃項(xiàng)目(2016YFB0800202) 國防基礎(chǔ)科研計(jì)劃項(xiàng)目(JCKY2016602B001) 國家自然科學(xué)基金項(xiàng)目(U1636120,61671396) 北京市科委科技計(jì)劃專項(xiàng)項(xiàng)目(Z161100002616032) CCF啟明星辰鴻雁基金項(xiàng)目(2016-010)~~
【分類號】:TP393.08
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