Combating DDoS attacks at their sources is still in its infancy. In tttis paper, a noaparametric adaptive CUSUM （cumulative sum） method is presented, which is proven efficient in detecting SYN flooding attacks close...Combating DDoS attacks at their sources is still in its infancy. In tttis paper, a noaparametric adaptive CUSUM （cumulative sum） method is presented, which is proven efficient in detecting SYN flooding attacks close to their sources. Different from other CUSUM methods, this new method has two distinct features： （1） its detection threshold can adapt itself to various traffic conditions and （2） it can timely detect the end of an attack within a required delay. Trace-driven simulations are conducted to validate the efficacy of this method in detecting SYN flooding attacks, and the results show that the nonparametric adaptive CUSUM method excels in detecting low-rate attacks.展开更多
Remote sensing-based methods of aboveground biomass(AGB)estimation in forest ecosystems have gained increased attention,and substantial research has been conducted in the past three decades.This paper provides a surve...Remote sensing-based methods of aboveground biomass(AGB)estimation in forest ecosystems have gained increased attention,and substantial research has been conducted in the past three decades.This paper provides a survey of current biomass estimation methods using remote sensing data and discusses four critical issues–collection of field-based biomass reference data,extraction and selection of suitable variables from remote sensing data,identification of proper algorithms to develop biomass estimation models,and uncertainty analysis to refine the estimation procedure.Additionally,we discuss the impacts of scales on biomass estimation performance and describe a general biomass estimation procedure.Although optical sensor and radar data have been primary sources for AGB estimation,data saturation is an important factor resulting in estimation uncertainty.LIght Detection and Ranging(lidar)can remove data saturation,but limited availability of lidar data prevents its extensive application.This literature survey has indicated the limitations of using single-sensor data for biomass estimation and the importance of integrating multi-sensor/scale remote sensing data to produce accurate estimates over large areas.More research is needed to extract a vertical vegetation structure(e.g.canopy height)from interferometry synthetic aperture radar(InSAR)or optical stereo images to incorporate it into horizontal structures(e.g.canopy cover)in biomass estimation modeling.展开更多
基金Supported by the Special Fund of Central College Basic Scientific Research Bursary (DUT1ORC(3)225)Key Discipline Construction Fund of Liaoning Province
文摘Combating DDoS attacks at their sources is still in its infancy. In tttis paper, a noaparametric adaptive CUSUM （cumulative sum） method is presented, which is proven efficient in detecting SYN flooding attacks close to their sources. Different from other CUSUM methods, this new method has two distinct features： （1） its detection threshold can adapt itself to various traffic conditions and （2） it can timely detect the end of an attack within a required delay. Trace-driven simulations are conducted to validate the efficacy of this method in detecting SYN flooding attacks, and the results show that the nonparametric adaptive CUSUM method excels in detecting low-rate attacks.
基金a grant from Research Center of Agricultural and Forestry Carbon Sinks and Ecological Environmental Remediation,Zhejiang A&F University.
文摘Remote sensing-based methods of aboveground biomass(AGB)estimation in forest ecosystems have gained increased attention,and substantial research has been conducted in the past three decades.This paper provides a survey of current biomass estimation methods using remote sensing data and discusses four critical issues–collection of field-based biomass reference data,extraction and selection of suitable variables from remote sensing data,identification of proper algorithms to develop biomass estimation models,and uncertainty analysis to refine the estimation procedure.Additionally,we discuss the impacts of scales on biomass estimation performance and describe a general biomass estimation procedure.Although optical sensor and radar data have been primary sources for AGB estimation,data saturation is an important factor resulting in estimation uncertainty.LIght Detection and Ranging(lidar)can remove data saturation,but limited availability of lidar data prevents its extensive application.This literature survey has indicated the limitations of using single-sensor data for biomass estimation and the importance of integrating multi-sensor/scale remote sensing data to produce accurate estimates over large areas.More research is needed to extract a vertical vegetation structure(e.g.canopy height)from interferometry synthetic aperture radar(InSAR)or optical stereo images to incorporate it into horizontal structures(e.g.canopy cover)in biomass estimation modeling.
