为了保护系统服务调度表(System Service Dispatch Table,SSDT),发现隐藏于该内核模块的钩子,进行了深入研究,提出异于rookit以加载驱动程序的形式的内核检测模式,即两种在用户模式下检测SSDT钩子的方法:使用\device\physical memory在...为了保护系统服务调度表(System Service Dispatch Table,SSDT),发现隐藏于该内核模块的钩子,进行了深入研究,提出异于rookit以加载驱动程序的形式的内核检测模式,即两种在用户模式下检测SSDT钩子的方法:使用\device\physical memory在用户模式下检测;用户模式使用Nt System Debug Control函数检测。实验表明,用户模式的这两种方法同样可以实现SSDT钩子的检测,并且用户程序省略了加载驱动时的繁琐步骤,避免了驱动的各种弊端。展开更多
To cope with the task scheduling problem under multi-task and transportation consideration in large-scale service oriented manufacturing systems(SOMS), a service allocation optimization mathematical model was establis...To cope with the task scheduling problem under multi-task and transportation consideration in large-scale service oriented manufacturing systems(SOMS), a service allocation optimization mathematical model was established, and then a hybrid discrete particle swarm optimization-genetic algorithm(HDPSOGA) was proposed. In SOMS, each resource involved in the whole life cycle of a product, whether it is provided by a piece of software or a hardware device, is encapsulated into a service. So, the transportation during production of a task should be taken into account because the hard-services selected are possibly provided by various providers in different areas. In the service allocation optimization mathematical model, multi-task and transportation were considered simultaneously. In the proposed HDPSOGA algorithm, integer coding method was applied to establish the mapping between the particle location matrix and the service allocation scheme. The position updating process was performed according to the cognition part, the social part, and the previous velocity and position while introducing the crossover and mutation idea of genetic algorithm to fit the discrete space. Finally, related simulation experiments were carried out to compare with other two previous algorithms. The results indicate the effectiveness and efficiency of the proposed hybrid algorithm.展开更多
文摘为了保护系统服务调度表(System Service Dispatch Table,SSDT),发现隐藏于该内核模块的钩子,进行了深入研究,提出异于rookit以加载驱动程序的形式的内核检测模式,即两种在用户模式下检测SSDT钩子的方法:使用\device\physical memory在用户模式下检测;用户模式使用Nt System Debug Control函数检测。实验表明,用户模式的这两种方法同样可以实现SSDT钩子的检测,并且用户程序省略了加载驱动时的繁琐步骤,避免了驱动的各种弊端。
基金Project(2012B091100444)supported by the Production,Education and Research Cooperative Program of Guangdong Province and Ministry of Education,ChinaProject(2013ZM0091)supported by Fundamental Research Funds for the Central Universities of China
文摘To cope with the task scheduling problem under multi-task and transportation consideration in large-scale service oriented manufacturing systems(SOMS), a service allocation optimization mathematical model was established, and then a hybrid discrete particle swarm optimization-genetic algorithm(HDPSOGA) was proposed. In SOMS, each resource involved in the whole life cycle of a product, whether it is provided by a piece of software or a hardware device, is encapsulated into a service. So, the transportation during production of a task should be taken into account because the hard-services selected are possibly provided by various providers in different areas. In the service allocation optimization mathematical model, multi-task and transportation were considered simultaneously. In the proposed HDPSOGA algorithm, integer coding method was applied to establish the mapping between the particle location matrix and the service allocation scheme. The position updating process was performed according to the cognition part, the social part, and the previous velocity and position while introducing the crossover and mutation idea of genetic algorithm to fit the discrete space. Finally, related simulation experiments were carried out to compare with other two previous algorithms. The results indicate the effectiveness and efficiency of the proposed hybrid algorithm.
