当前,越来越多的分布式拒绝服务(distributed denial of service,DDoS)攻击的攻击源迁移至云中,给云计算的可控性及整个网络空间的安全带来了严重挑战.然而关于有效控制云中该类攻击源的研究还比较缺乏.为此设计了一种面向可控云计算的D...当前,越来越多的分布式拒绝服务(distributed denial of service,DDoS)攻击的攻击源迁移至云中,给云计算的可控性及整个网络空间的安全带来了严重挑战.然而关于有效控制云中该类攻击源的研究还比较缺乏.为此设计了一种面向可控云计算的DDoS攻击源控制系统pTrace,该系统包括入口流量过滤inFilter和恶意进程溯源mpTrace两部分.其中,inFilter过滤伪造源地址信息的数据包;mpTrace先识别攻击流及其源地址信息,依据源地址信息追溯并管控发送攻击流的恶意进程.在Openstack和Xen环境下实现了pTrace的原型系统,分析及实验表明,inFilter可以有效地防止含有虚假源地址信息的DDoS攻击包流出云外;当攻击流速率约为正常流量的2.5倍时,mpTrace即可正确识别攻击流信息,并可在ms级的时间内正确追溯攻击流量发送进程.该方法有效控制了位于云中的DDoS攻击源,减小了对云内傀儡租户及云外攻击目标的影响.展开更多
Abstract Most papers in scheduling research have treated individual job processing times as fixed parameters. However, in many practical situations, a manager may control processing time by reallocating resources. In ...Abstract Most papers in scheduling research have treated individual job processing times as fixed parameters. However, in many practical situations, a manager may control processing time by reallocating resources. In this paper, authors consider a machine scheduling problem with controllable processing times. In the first part of this paper, a special case where the processing times and compression costs are uniform among jobs is discussed. Theoretical results are derived that aid in developing an O(n 2) algorithm to slove the problem optimally. In the second part of this paper, authors generalize the discussion to general case. An effective heuristic to the general problem will be presented.展开更多
文摘当前,越来越多的分布式拒绝服务(distributed denial of service,DDoS)攻击的攻击源迁移至云中,给云计算的可控性及整个网络空间的安全带来了严重挑战.然而关于有效控制云中该类攻击源的研究还比较缺乏.为此设计了一种面向可控云计算的DDoS攻击源控制系统pTrace,该系统包括入口流量过滤inFilter和恶意进程溯源mpTrace两部分.其中,inFilter过滤伪造源地址信息的数据包;mpTrace先识别攻击流及其源地址信息,依据源地址信息追溯并管控发送攻击流的恶意进程.在Openstack和Xen环境下实现了pTrace的原型系统,分析及实验表明,inFilter可以有效地防止含有虚假源地址信息的DDoS攻击包流出云外;当攻击流速率约为正常流量的2.5倍时,mpTrace即可正确识别攻击流信息,并可在ms级的时间内正确追溯攻击流量发送进程.该方法有效控制了位于云中的DDoS攻击源,减小了对云内傀儡租户及云外攻击目标的影响.
文摘Abstract Most papers in scheduling research have treated individual job processing times as fixed parameters. However, in many practical situations, a manager may control processing time by reallocating resources. In this paper, authors consider a machine scheduling problem with controllable processing times. In the first part of this paper, a special case where the processing times and compression costs are uniform among jobs is discussed. Theoretical results are derived that aid in developing an O(n 2) algorithm to slove the problem optimally. In the second part of this paper, authors generalize the discussion to general case. An effective heuristic to the general problem will be presented.
