CAJ | 학술논문

网络安全态势评估是信息安全领域的研究热点问题. 为了解决现有评估中过度依赖专家经验问题,提出了一种基于改进D-S证据理论的网络安全态势评估方法. 该方法融合多源态势信息,利用基于遗传算法优化反向传播( Back propagation,BP)神经网络来获得D-S证据理论的基本概率分配(Basic probability assignation,BPA),由D-S证据理论对BPA依次进行合成计算,弱化人为因素对BPA的影响,提高BPA的预测精度和网络安全态势识别率. 通过真实网络环境的实验验证了该方法在网络安全态势评估中的可行性和有效性.
망락안전태세평고시신식안전영역적연구열점문제. 위료해결현유평고중과도의뢰전가경험문제,제출료일충기우개진D-S증거이론적망락안전태세평고방법. 해방법융합다원태세신식,이용기우유전산법우화반향전파( Back propagation,BP)신경망락래획득D-S증거이론적기본개솔분배(Basic probability assignation,BPA),유D-S증거이론대BPA의차진행합성계산,약화인위인소대BPA적영향,제고BPA적예측정도화망락안전태세식별솔. 통과진실망락배경적실험험증료해방법재망락안전태세평고중적가행성화유효성.
It is a hot issue for network security situational assessment in the field of information security. In order to solve the problem of over-reliance on expert experience,it proposes a security situational assessment method based on the improved D-S evidence theory. For this method,it fuses multi-source situation information and uses the back propagation ( BP ) neural network based on Genetic Algorithm to obtain the basic probability assignation( BPA) of the D-S evidence theory. The D-S evidence theory is adopted to integrate the BPA in turn, weaken the interference of artificial factors on BPA, and improve the BPA forecasting accuracy and the situational recognition rate of network security situation. Tests with a real network environment show that this method effectively improves the network security situational assessment.