The attack graph methodology can be used to identify the potential attack paths that an attack can propagate. A risk assessment model based on Bayesian attack graph is presented in this paper. Firstly, attack graphs a...The attack graph methodology can be used to identify the potential attack paths that an attack can propagate. A risk assessment model based on Bayesian attack graph is presented in this paper. Firstly, attack graphs are generated by the MULVAL（Multi-host, Multistage Vulnerability Analysis） tool according to sufficient information of vulnerabilities, network configurations and host connectivity on networks. Secondly, the probabilistic attack graph is established according to the causal relationships among sophisticated multi-stage attacks by using Bayesian Networks. The probability of successful exploits is calculated by combining index of the Common Vulnerability Scoring System, and the static security risk is assessed by applying local conditional probability distribution tables of the attribute nodes. Finally, the overall security risk in a small network scenario is assessed. Experimental results demonstrate our work can deduce attack intention and potential attack paths effectively, and provide effective guidance on how to choose the optimal security hardening strategy.展开更多
In order to protect the website and assess the security risk of website, a novel website security risk assessment method is proposed based on the improved Bayesian attack graph(I-BAG) model. First, the Improved Bayesi...In order to protect the website and assess the security risk of website, a novel website security risk assessment method is proposed based on the improved Bayesian attack graph(I-BAG) model. First, the Improved Bayesian attack graph model is established, which takes attack benefits and threat factors into consideration. Compared with the existing attack graph models, it can better describe the website's security risk. Then, the improved Bayesian attack graph is constructed with optimized website attack graph, attack benefit nodes, threat factor nodes and the local conditional probability distribution of each node, which is calculated accordingly. Finally, website's attack probability and risk value are calculated on the level of nodes, hosts and the whole website separately. The experimental results demonstrate that the risk evaluating method based on I-BAG model proposed is a effective way for assessing the website security risk.展开更多
Construction project is not a standalone engineering maneuver.It is closely linked to the well-being of local communities in concern.The city renovation in Beijing down center for Olympic 2008 transformed many antique...Construction project is not a standalone engineering maneuver.It is closely linked to the well-being of local communities in concern.The city renovation in Beijing down center for Olympic 2008 transformed many antique architecture and regional landscape.It gave a world-recognized achievement in China s modem development and manifested a major milestone in China's economic development.In the course of metro construction projects,there are substantial interwoven municipal structures influencing the success of the projects,which including,but the least,all underground cables and ducts,sewage system,the power consumption of construction works,traffic diversion,air pollution,expatriate business activities and social security.There are many US and UK project insurance companies moving into Asia Pacific.They are doing re-insurance business on major construction guarantee,such as machinery damage,project on-time,power consumption,claims from contractors and communities.Environmental information,such as water quality,indoor and outdoor air quality,people inflow and lift waiting time play deterministic roles in construction's fit-touse.Big Data is a contemporary buzzword since 2013,and the key competence is to provide real time response to heuristic syndrome in order to make short-term prediction.This paper attempts to develop a conceptual model in big data for construction展开更多
On the basis of sedimentation principles and environmental chemical characteristics of heavymetal, combine international new methods-face graph on heavy metal pollution assessment withmulti-variable graph expression, ...On the basis of sedimentation principles and environmental chemical characteristics of heavymetal, combine international new methods-face graph on heavy metal pollution assessment withmulti-variable graph expression, the article made a synthetical assessment study on state of heavymetal pollution and potential ecological risk of Taizi River sediment in Benxi City reach. The re-sults of the study indicated that the state of heavy metal pollution of Taizi River in Benxi Cityreach is very serious, appropriate counter measures should be taken.展开更多
针对智能驾驶系统在驾驶风险预警中存在的动态交互特征捕捉不足、多模态轨迹预测精度有限以及碰撞风险量化物理指标过度单一等问题,研究了基于多模态轨迹预测与概率量化耦合的预见性碰撞风险评估模型。在轨迹预测部分,研究了分层图注意...针对智能驾驶系统在驾驶风险预警中存在的动态交互特征捕捉不足、多模态轨迹预测精度有限以及碰撞风险量化物理指标过度单一等问题,研究了基于多模态轨迹预测与概率量化耦合的预见性碰撞风险评估模型。在轨迹预测部分,研究了分层图注意力网络,通过图注意力机制融合高精地图、车道线以及车辆历史轨迹特征,能够有效捕捉车辆行驶环境中的动态变化;针对传统模型中先预测再细化的两阶段解码结构,引入滑动窗口优化解码器,能够准确预测临近车辆的未来轨迹。在碰撞风险评估部分,研究了1种基于概率量化的碰撞风险评估方法,通过结合预测的未来轨迹与碰撞风险,估算自车与周边车辆发生碰撞的概率,实现对车辆危险行为的提前预警。实验结果表明:在Argoverse数据集上最小终点位移误差、最小平均位移误差和漏检率分别为0.785、1.157和0.126,与HiVT与LaneGCN相比,在终点预测方面误差分别减少了1%和15.1%。在城市交通能力仿真软件(simulation of urban mobility,SUMO)上验证预测风险与实际风险的偏差约为5%,从数据波动性上看,危险程度波动幅度为0.3,与碰撞时间(time to collision,TTC)方法和动态安全指数(dynamic safety index,DSI)方法相比,波动幅度分别减少33.3%和18.75%,在持续驾驶场景中展现出更优秀的风险评估水准;证明了基于障碍车辆轨迹预测的驾驶碰撞风险模型在预测未来潜在驾驶风险的准确性。展开更多
基金Supported by the National Natural Science Foundation of China(61373176)the Natural Science Foundation of Shaanxi Province of China(2015JQ7278)the Scientific Research Plan Projects of Shaanxi Educational Committee(17JK0304,14JK1693)
文摘The attack graph methodology can be used to identify the potential attack paths that an attack can propagate. A risk assessment model based on Bayesian attack graph is presented in this paper. Firstly, attack graphs are generated by the MULVAL（Multi-host, Multistage Vulnerability Analysis） tool according to sufficient information of vulnerabilities, network configurations and host connectivity on networks. Secondly, the probabilistic attack graph is established according to the causal relationships among sophisticated multi-stage attacks by using Bayesian Networks. The probability of successful exploits is calculated by combining index of the Common Vulnerability Scoring System, and the static security risk is assessed by applying local conditional probability distribution tables of the attribute nodes. Finally, the overall security risk in a small network scenario is assessed. Experimental results demonstrate our work can deduce attack intention and potential attack paths effectively, and provide effective guidance on how to choose the optimal security hardening strategy.
基金supported by the project of the State Key Program of National Natural Science Foundation of China (No. 90818021)supported by a grant from the national high technology research and development program of China (863program) (No.2012AA012903)
文摘In order to protect the website and assess the security risk of website, a novel website security risk assessment method is proposed based on the improved Bayesian attack graph(I-BAG) model. First, the Improved Bayesian attack graph model is established, which takes attack benefits and threat factors into consideration. Compared with the existing attack graph models, it can better describe the website's security risk. Then, the improved Bayesian attack graph is constructed with optimized website attack graph, attack benefit nodes, threat factor nodes and the local conditional probability distribution of each node, which is calculated accordingly. Finally, website's attack probability and risk value are calculated on the level of nodes, hosts and the whole website separately. The experimental results demonstrate that the risk evaluating method based on I-BAG model proposed is a effective way for assessing the website security risk.
文摘Construction project is not a standalone engineering maneuver.It is closely linked to the well-being of local communities in concern.The city renovation in Beijing down center for Olympic 2008 transformed many antique architecture and regional landscape.It gave a world-recognized achievement in China s modem development and manifested a major milestone in China's economic development.In the course of metro construction projects,there are substantial interwoven municipal structures influencing the success of the projects,which including,but the least,all underground cables and ducts,sewage system,the power consumption of construction works,traffic diversion,air pollution,expatriate business activities and social security.There are many US and UK project insurance companies moving into Asia Pacific.They are doing re-insurance business on major construction guarantee,such as machinery damage,project on-time,power consumption,claims from contractors and communities.Environmental information,such as water quality,indoor and outdoor air quality,people inflow and lift waiting time play deterministic roles in construction's fit-touse.Big Data is a contemporary buzzword since 2013,and the key competence is to provide real time response to heuristic syndrome in order to make short-term prediction.This paper attempts to develop a conceptual model in big data for construction
文摘On the basis of sedimentation principles and environmental chemical characteristics of heavymetal, combine international new methods-face graph on heavy metal pollution assessment withmulti-variable graph expression, the article made a synthetical assessment study on state of heavymetal pollution and potential ecological risk of Taizi River sediment in Benxi City reach. The re-sults of the study indicated that the state of heavy metal pollution of Taizi River in Benxi Cityreach is very serious, appropriate counter measures should be taken.
文摘针对智能驾驶系统在驾驶风险预警中存在的动态交互特征捕捉不足、多模态轨迹预测精度有限以及碰撞风险量化物理指标过度单一等问题,研究了基于多模态轨迹预测与概率量化耦合的预见性碰撞风险评估模型。在轨迹预测部分,研究了分层图注意力网络,通过图注意力机制融合高精地图、车道线以及车辆历史轨迹特征,能够有效捕捉车辆行驶环境中的动态变化;针对传统模型中先预测再细化的两阶段解码结构,引入滑动窗口优化解码器,能够准确预测临近车辆的未来轨迹。在碰撞风险评估部分,研究了1种基于概率量化的碰撞风险评估方法,通过结合预测的未来轨迹与碰撞风险,估算自车与周边车辆发生碰撞的概率,实现对车辆危险行为的提前预警。实验结果表明:在Argoverse数据集上最小终点位移误差、最小平均位移误差和漏检率分别为0.785、1.157和0.126,与HiVT与LaneGCN相比,在终点预测方面误差分别减少了1%和15.1%。在城市交通能力仿真软件(simulation of urban mobility,SUMO)上验证预测风险与实际风险的偏差约为5%,从数据波动性上看,危险程度波动幅度为0.3,与碰撞时间(time to collision,TTC)方法和动态安全指数(dynamic safety index,DSI)方法相比,波动幅度分别减少33.3%和18.75%,在持续驾驶场景中展现出更优秀的风险评估水准;证明了基于障碍车辆轨迹预测的驾驶碰撞风险模型在预测未来潜在驾驶风险的准确性。
