针对现有的蠕虫遏制方案无法应对移动互联网长短距混合蠕虫攻击这一问题,提出一种基于社区的移动互联网混合蠕虫双向反馈遏制系统.该系统分为社会信息网络(social information networks,SIN)遏制单元和地理信息网络(geographic informat...针对现有的蠕虫遏制方案无法应对移动互联网长短距混合蠕虫攻击这一问题,提出一种基于社区的移动互联网混合蠕虫双向反馈遏制系统.该系统分为社会信息网络(social information networks,SIN)遏制单元和地理信息网络(geographic information networks,GIN)反馈单元2个子系统,SIN遏制单元采用一种在线式社区隔离策略,通过识别社区间的门禁节点并设计相应的蠕虫标签投送算法,将蠕虫遏制在社区内部;GIN反馈单元收集用户的短程通信记录、GPS位置数据以及来自SIN遏制单元提交的历史安全信息,实现对节点的信任性评估,通过将结果反馈到SIN遏制单元,限制社区内部节点的下一步通信决定,从而降低蠕虫在社区内部的传播速度,实现了SIN遏制单元和GIN反馈单元的双向循环.最后通过仿真实验验证了所提方法的可行性和有效性.展开更多
Load forecasting is a critical issue for operational planning as well as grid expansion to ensure an uninterruptable electric power system. Being a small but densely populated country in South Asia, Bangladesh has man...Load forecasting is a critical issue for operational planning as well as grid expansion to ensure an uninterruptable electric power system. Being a small but densely populated country in South Asia, Bangladesh has many isolated places which are not connected to national grid yet. If concern authority opts to expand grid to those areas, they need reliable demand data for designing and dimensioning of different power system entities, e.g., capacity, overhead line capacity, tie line capacity, spinning reserve, load-shedding scheduling, etc., for reliable operation and to prevent possible obligatory redesigning. This paper represents an analysis to forecast the electricity demand of an isolated island in Bangladesh where past history of electrical load demand is not available. The analysis is based on the identification of factors, e.g., population, literacy rate, per capita income, occupation, communication, etc., on which electrical load growth of an area depends. Data has been collected from the targeted isolated area and form a grid connected area which is similar to target area from social and geographical perspective. Weights of those factors on load have been calculated by matrix inversion. Demand of the new area is forecasted using these weights factors by matrix multiplication.展开更多
文摘针对现有的蠕虫遏制方案无法应对移动互联网长短距混合蠕虫攻击这一问题,提出一种基于社区的移动互联网混合蠕虫双向反馈遏制系统.该系统分为社会信息网络(social information networks,SIN)遏制单元和地理信息网络(geographic information networks,GIN)反馈单元2个子系统,SIN遏制单元采用一种在线式社区隔离策略,通过识别社区间的门禁节点并设计相应的蠕虫标签投送算法,将蠕虫遏制在社区内部;GIN反馈单元收集用户的短程通信记录、GPS位置数据以及来自SIN遏制单元提交的历史安全信息,实现对节点的信任性评估,通过将结果反馈到SIN遏制单元,限制社区内部节点的下一步通信决定,从而降低蠕虫在社区内部的传播速度,实现了SIN遏制单元和GIN反馈单元的双向循环.最后通过仿真实验验证了所提方法的可行性和有效性.
文摘Load forecasting is a critical issue for operational planning as well as grid expansion to ensure an uninterruptable electric power system. Being a small but densely populated country in South Asia, Bangladesh has many isolated places which are not connected to national grid yet. If concern authority opts to expand grid to those areas, they need reliable demand data for designing and dimensioning of different power system entities, e.g., capacity, overhead line capacity, tie line capacity, spinning reserve, load-shedding scheduling, etc., for reliable operation and to prevent possible obligatory redesigning. This paper represents an analysis to forecast the electricity demand of an isolated island in Bangladesh where past history of electrical load demand is not available. The analysis is based on the identification of factors, e.g., population, literacy rate, per capita income, occupation, communication, etc., on which electrical load growth of an area depends. Data has been collected from the targeted isolated area and form a grid connected area which is similar to target area from social and geographical perspective. Weights of those factors on load have been calculated by matrix inversion. Demand of the new area is forecasted using these weights factors by matrix multiplication.
