摘要：【中文】本发明属于计算机技术领域，具体涉及一种针对恶意容器的检测方法，包括以下步骤，步骤1、对被监控虚拟机中所有进程的创建行为进行监听；步骤2、判断创建的进程是否属于该虚拟机中的容器，若此进程属于该虚拟机中的容器，则读取其执行文件的信息；若此进程不属于该虚拟机中的容器，则结束；步骤3、在读取完毕后，从容器中查找该执行文件；步骤4、对执行文件进行安全扫描，若该执行文件为恶意文件，则测得其对应的容器即为恶意容器。与现有技术相比，本发明能够有效地检测出恶意容器，从而防止恶意容器对虚拟机的控制与控制，提高了系统的安全性。 【EN】The invention belongs to the technical field of computers, and particularly relates to a detection method for a malicious container, which comprises the following steps of 1, monitoring the creating behaviors of all processes in a monitored virtual machine; step 2, judging whether the created process belongs to the container in the virtual machine, and if the process belongs to the container in the virtual machine, reading information of an execution file of the process; if the process does not belong to the container in the virtual machine, ending the process; step 3, after reading, searching the execution file from the container; and 4, carrying out security scanning on the execution file, and if the execution file is a malicious file, measuring that a corresponding container is a malicious container. Compared with the prior art, the method and the system can effectively detect the malicious container, thereby preventing the malicious container from controlling and controlling the virtual machine and improving the safety of the system.

摘要：【中文】本发明属于计算机安全的技术领域，具体涉及一种维护虚拟机文件安全的检测方法，包括运行虚拟机的文件驱动，对虚拟机的磁盘进行记录，提取虚拟机中的新增文件或修改文件，对新增文件或修改文件进行安全检测。本发明对新增文件和修改文件检测的安全性强，有效地提高了文件轮询检测的效率。此外，本发明还提供了一种维护虚拟机文件安全的检测系统。 【EN】The invention belongs to the technical field of computer security, and particularly relates to a detection method for maintaining the file security of a virtual machine. The invention has strong safety for detecting the newly added files and the modified files and effectively improves the efficiency of polling detection of the files. In addition, the invention also provides a detection system for maintaining the file security of the virtual machine.

摘要：【中文】一种移动物联网中的高效、安全的多用户多任务卸载方法，涉及移动物联网移动边缘计算领域，为了实现在时间的约束下将能耗的加权总和最小化，使任务卸载能耗较低。建立通信模型；资源分配策略，量化本地计算和卸载计算的开销；压缩策略，采用JPEG算法对卸载计算时传输的用户数据进行压缩以减少能源消耗；安全策略；优化策略；构建一个考虑将资源分配、压缩和安全性的集成模型，将该模型表述为整数非线性问题，该问题的目标是在时间约束下使能量的加权总和最小化，获得任务卸载决策和任务压缩决策的最优解。减轻移动物联网的网络资源限制，在计算任务卸载的同时，兼顾考虑资源分配，传输数据压缩和安全性，实现在时间的约束下能耗的加权总和最小化。 【EN】An efficient and safe multi-user multi-task unloading method in a mobile Internet of things relates to the field of mobile edge calculation of the mobile Internet of things, and aims to minimize the weighted sum of energy consumption under the constraint of time and enable the energy consumption of task unloading to be low. Establishing a communication model; a resource allocation strategy for quantifying the overhead of local computation and offload computation; a compression strategy, wherein a JPEG algorithm is adopted to compress user data transmitted during unloading calculation so as to reduce energy consumption; a security policy; optimizing the strategy; and constructing an integrated model considering resource allocation, compression and safety, and expressing the model as an integer nonlinear problem, wherein the aim of the problem is to minimize the weighted sum of energy under the time constraint and obtain the optimal solution of task unloading decision and task compression decision. The network resource limitation of the mobile Internet of things is reduced, the resource allocation, the transmission data compression and the safety are considered while the calculation task is unloaded, and the weighted sum minimization of the energy consumption under the time constraint is realized.

摘要：【中文】一种工业物联网中针对数据驱动制造服务的节能资源分配方法，属于工业物联网优化技术。本发明为了实现对分配后的任进行实时监控调整，降低系统资源消耗，确保由云制造服务提供商交付SLA的同时降低主机能耗和冷却成本。检测CPU利用率；确定待迁移出服务，SU‑hosts上的所有D2M服务以及从SO‑hosts中选择的D2M服务；搜索合适的主机为确定移出的D2M服务分配资源，利用能源和热感知资源分配方案找到适合D2M服务迁移的主机，进行服务迁移以减少能源消耗。本发明考虑了资源分配的节能消耗，并对任务分配后进行实时监控调整，降低了系统资源消耗，确保由云制造服务提供商交付SLA的同时降低主机能耗和冷却成本。 【EN】An energy-saving resource allocation method for data-driven manufacturing service in the industrial Internet of things belongs to the industrial Internet of things optimization technology. The invention aims to realize real-time monitoring and adjustment of the distributed tasks, reduce the resource consumption of the system, ensure that SLA is delivered by a cloud manufacturing service provider and reduce the energy consumption and cooling cost of the host. Detecting the utilization rate of a CPU; determining all D2M services on SU-hosts and a D2M service selected from SO-hosts to be migrated out of the service; and searching suitable hosts to allocate resources for the D2M service determined to be moved, finding suitable hosts for D2M service migration by utilizing an energy and thermal perception resource allocation scheme, and performing service migration to reduce energy consumption. The invention considers the energy-saving consumption of resource allocation, carries out real-time monitoring and adjustment after the task allocation, reduces the resource consumption of the system, ensures that SLA is delivered by a cloud manufacturing service provider, and simultaneously reduces the energy consumption and the cooling cost of the host.

摘要：【中文】一种车辆雾计算中基于能耗和延迟权衡的计算任务动态卸载方法，属于雾计算应用技术领域。本发明为了充分利用附近车辆的计算资源，将云节点的任务从云节点下放到车辆节点上，为减轻云节点的过载，减少高峰时段的服务延迟，以及为电池供电的云节点节约电能。定义所述卸载方法对应的VFC环境；针对单个车辆节点的单个任务构建能源消耗成本，能源消耗成本为总能量消耗和总延迟的加权和：针对VFC环境下的所有节点所有任务的能耗和延迟的模型，构建联合目标函数，给出约束条件并定义优化问题；针对步骤三的优化问题求得当联合目标函数达到最小值时，每个任务所应卸载到的车辆节点，进而得到最优的任务卸载方案。本发明降低了能量消耗，降低整体处理延迟。 【EN】A dynamic unloading method for a computing task based on energy consumption and delay balance in vehicle fog computing belongs to the technical field of fog computing application. In order to fully utilize computing resources of nearby vehicles, tasks of cloud nodes are transferred from the cloud nodes to the vehicle nodes, so that overload of the cloud nodes is relieved, service delay in peak hours is reduced, and electric energy is saved for the cloud nodes powered by batteries. Defining a VFC environment corresponding to the unloading method; constructing an energy consumption cost for a single task of a single vehicle node, wherein the energy consumption cost is a weighted sum of total energy consumption and total delay: aiming at models of energy consumption and delay of all tasks of all nodes in a VFC environment, a combined objective function is constructed, constraint conditions are given, and an optimization problem is defined; and solving the vehicle nodes to which each task should be unloaded when the combined objective function reaches the minimum value aiming at the optimization problem in the third step, and further obtaining an optimal task unloading scheme. The invention reduces energy consumption and overall processing delay.