In this paper, we present Real-Time Flow Filter (RTFF) -a system that adopts a middle ground between coarse-grained volume anomaly detection and deep packet inspection. RTFF was designed with the goal of scaling to hi...In this paper, we present Real-Time Flow Filter (RTFF) -a system that adopts a middle ground between coarse-grained volume anomaly detection and deep packet inspection. RTFF was designed with the goal of scaling to high volume data feeds that are common in large Tier-1 ISP networks and providing rich, timely information on observed attacks. It is a software solution that is designed to run on off-the-shelf hardware platforms and incorporates a scalable data processing architecture along with lightweight analysis algorithms that make it suitable for deployment in large networks. RTFF also makes use of state of the art machine learning algorithms to construct attack models that can be used to detect as well as predict attacks.展开更多
Herein symmetrical four-legged suspension lunar lander was used as the research object, the six-degree-of-freedom dynamic model was built and the model of the lunar soil friction coefficient was improved. For the low-...Herein symmetrical four-legged suspension lunar lander was used as the research object, the six-degree-of-freedom dynamic model was built and the model of the lunar soil friction coefficient was improved. For the low-gravity simulation on objects outside earth for future work, the law of dynamic similarity for detectors was deduced. A new method was proposed for simulating the low-gravity field on the surface of objects outside earth, which was achieved by changing initial conditions of the landing by the probe and by subsequent treatment of experimental data. The prototype tested the limitation of this method was verified. It is shown that the prototypes of detectors can be used in detectors low-gravity simulation test with this method, and equipments are simple and operationally effective. This method can be used for later lunar exploration, and low-gravity simulations on extraterrestrial objects.展开更多
文摘In this paper, we present Real-Time Flow Filter (RTFF) -a system that adopts a middle ground between coarse-grained volume anomaly detection and deep packet inspection. RTFF was designed with the goal of scaling to high volume data feeds that are common in large Tier-1 ISP networks and providing rich, timely information on observed attacks. It is a software solution that is designed to run on off-the-shelf hardware platforms and incorporates a scalable data processing architecture along with lightweight analysis algorithms that make it suitable for deployment in large networks. RTFF also makes use of state of the art machine learning algorithms to construct attack models that can be used to detect as well as predict attacks.
基金supported by the National Natural Science Foundation of China(Grant No.51105196)Natural Science Foundation of Jiangsu Province(Grant No.BK2011733)
文摘Herein symmetrical four-legged suspension lunar lander was used as the research object, the six-degree-of-freedom dynamic model was built and the model of the lunar soil friction coefficient was improved. For the low-gravity simulation on objects outside earth for future work, the law of dynamic similarity for detectors was deduced. A new method was proposed for simulating the low-gravity field on the surface of objects outside earth, which was achieved by changing initial conditions of the landing by the probe and by subsequent treatment of experimental data. The prototype tested the limitation of this method was verified. It is shown that the prototypes of detectors can be used in detectors low-gravity simulation test with this method, and equipments are simple and operationally effective. This method can be used for later lunar exploration, and low-gravity simulations on extraterrestrial objects.
