Computer networks face a variety of cyberattacks. Most network attacks are contagious and destructive, and these types of attacks can be harmful to society and computer network security. Security evaluation is an effective method to solve network security problems. For accurate assessment of the vulnerabilities of computer networks, this paper proposes a network security risk assessment method based on a Bayesian network attack graph (B_NAG) model. First, a new resource attack graph (RAG) and the algorithm E-Loop, which is applied to eliminate loops in the B_NAG, are proposed. Second, to distinguish the confusing relationships between nodes of the attack graph in the conversion process, a related algorithm is proposed to generate the B_NAG model. Finally, to analyze the reachability of paths in B_NAG, the measuring indexs such as node attack complexity and node state transition are defined, and an iterative algorithm for obtaining the probability of reaching the target node is presented. On this basis, the posterior probability of related nodes can be calculated. A simulation environment is set up to evaluate the effectiveness of the B_NAG model. The experimental results indicate that the B_NAG model is realistic and effective in evaluating vulnerabilities of computer networks and can accurately highlight the degree of vulnerability in a chaotic relationship. 相似文献
Although it provides a feasible inbound logistics solution for steady production and low inventory management, the Milk-run mode inevitably leads to a high transportation costs due to the features of small-batch and high-frequency delivery. In order to break through the defections of the existing inbound logistics mode, an integrated inbound logistics (IIL) mode with low-carbon and high efficiency is established. An intelligent scheduling method combines Milk-run collection with drop and pull delivery together. Moreover, the LNG vehicles are simultaneously used in the whole process. With AJ company’s auto-parts inbound logistics as a case, the IIL mode is formulated with a mixed integer mathematical model. The genetic algorithm coded with Matlab is used to find the optimal solution. The results show that when compared with the original Milk-run mode, the IIL mode brings massive reductions in driving mileage, wait time and waste gas emission. It can make significant benefits in both economic and social sense. Therefore, it is entirely reasonable for management of industries to believe that the IIL mode will be a feasible and promising alternative for inbound logistics.
A water drop behaves differently from a large water body because of its strong viscosity and surface tension under the small scale. Surface tension causes the motion of a water drop to be largely determined by its boundary surface. Meanwhile, viscosity makes the interior of a water drop less relevant to its motion, as the smooth velocity field can be well approximated by an interpolation of the velocity on the boundary. Consequently, we propose a fast deformable surface model to realistically animate water drops and their flowing behaviors on solid surfaces. Our system efficiently simulates water drop motions in a Lagrangian fashion, by reducing 3D fluid dynamics over the whole liquid volume to a deformable surface model. In each time step, the model uses an implicit mean curvature flow operator to produce surface tension effects, a contact angle operator to change droplet shapes on solid surfaces, and a set of mesh connectivity updates to handle topological changes and improve mesh quality over time. Our numerical experiments demonstrate a variety of physically plausible water drop phenomena at a real-time rate, including capillary waves when water drops collide, pinch-off of water jets, and droplets flowing over solid materials. The whole system performs orders-of-magnitude faster than existing simulation approaches that generate comparable water drop effects. 相似文献