“一带一路”背景下城市公共交通网络暴恐袭击风险识别及防御研究

With the advance of the Belt and Road Initiative, the non-traditional security risks such as terrorist attacks are on the rise, and the real threat is growing in intensity. The urban public transport network (UPTN) has become one of the important targets of terrorist attacks. Targeting the key links in the network will cause cascade failure and even the collapse of urban transport network. The public transport network is an important guarantee for the operation of the city. Therefore, it is of great practical significance to improve the ability of urban public transportation to prevent the security risks. Under this background and from the perspective of disaster prevention, the targets identification of UPTN attacks were taken as the breakthrough point by using the identification, evaluation and prevention in risk management for reference. The mode of attack is combined with the characteristics of UPTN. The time and space evolution pattern of the network under terrorist attacks were revealed, and the key links in the network were identified. The fuzzy evidence risk assessment model was used to evaluate the risk of attack on the key links. Combined with the optimization theory of external defense facilities, the defensive strategy of internal and external coordination was constructed by using the multidisciplinary study, and then the framework of active defense theory for the network security was built.The research results are suitable for the security defense of electric power, telecommunications, water supply, and other key infrastructures of a city. They can help the public safety management departments and other departments of the government in taking scientific and effective measures.

随着“一带一路”倡议的纵深推进，暴恐袭击等非传统安全风险在不断上升，现实威胁正逐步提高。城市公共交通网络已成为暴恐袭击的重要目标之一，若以网络中的关键环节为攻击目标将会导致城市交通网络的级联失效甚至崩溃。公共交通网络是城市得以运行的重要保障，提升城市公共交通防范和抵御安全风险的能力具有极其重要的现实意义。在此背景下，课题从防灾视角，借鉴风险管理中的识别、评估、防范理论，以针对城市公共交通网络的袭击目标识别为切入点，将暴恐袭击的攻击模式与城市公共交通网络特性相结合，揭示暴恐袭击下城市公共交通网络的时间和空间演化规律，识别网络中的关键环节；建立模糊证据风险评估模型对关键环节袭击风险进行评估；运用多学科交叉研究构建内外协同的防御策略，由此形成系统的网络安全主动防御理论框架。研究成果对电力、电信、给水等其它城市关键基础设施的安全防御具有一定适用性，可为政府公共安全管理等相关部门提供决策参考。

随着“一带一路”倡议的纵深推进，暴恐袭击等非传统安全风险在不断上升，现实威胁正逐步提高。城市公共交通网络已成为暴恐袭击的重要目标之一，若以网络中的关键环节为攻击目标将会导致城市交通网络的级联失效甚至崩溃。公共交通网络是城市得以运行的重要保障，提升城市公共交通防范和抵御安全风险的能力具有极其重要的现实意义。（1）在此背景下，课题从防灾视角，借鉴风险管理中的识别、评估、防范理论，以针对城市公共交通网络的袭击目标识别为切入点，将暴恐袭击的攻击模式与城市公共交通网络特性相结合。仿真发现乌鲁木齐、昆明等边疆城市公交复杂网络的度和点强度分布极为不均，具有无标度和小世界的网络特点。（2）对暴恐袭击目标及车辆进行动态跟踪是避免袭击发生的重要手段，城市交通系统中，动态跟踪图像多阈值分割是图像多目标跟踪和优化中的关键技术之一。本研究提出了变精度粗糙集和K-L粗糙散度粒子群的图像多阈值分割算法，实验对比分析得出，该算法能够解决分割中的不确定性问题，且分割效果优于其他对比算法。（3）为及时满足受袭区域群众物资需求，本研究应用可变集理论对各受袭区域应急物资紧迫度进行等级排序，进而确定了各受袭区域应急物资分配量，在此基础上构建基于优先等级的应急设施定位-路径优化模型。（4）暴恐袭击具有突发性和难以预测性等特征，快速有效的应急救援是保证受袭区域群众生命安全的重要措施。本研究基于救援队伍连续派遣问题，利用等级置信度确定救援队伍相对各受袭区域的救援效率，考虑救援时间约束及阶段救援的动态可行性，以应急救援效率最大化为优化目标构建0-1非线性整数规划模型。研究成果对电力、电信、给水等其它城市关键基础设施的安全防御具有一定适用性，可为政府公共安全管理等相关部门提供决策参考。

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