912 resultados para PACKET MARKING


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The future convergence of voice, video and data applications on the Internet requires that next generation technology provides bandwidth and delay guarantees. Current technology trends are moving towards scalable aggregate-based systems where applications are grouped together and guarantees are provided at the aggregate level only. This solution alone is not enough for interactive video applications with sub-second delay bounds. This paper introduces a novel packet marking scheme that controls the end-to-end delay of an individual flow as it traverses a network enabled to supply aggregate- granularity Quality of Service (QoS). IPv6 Hop-by-Hop extension header fields are used to track the packet delay encountered at each network node and autonomous decisions are made on the best queuing strategy to employ. The results of network simulations are presented and it is shown that when the proposed mechanism is employed the requested delay bound is met with a 20% reduction in resource reservation and no packet loss in the network.

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拒绝服务攻击是一类最难对付的网络安全问题.近来,人们提出了多种对策.其中由Savage等人提出的一类基于概率的包标记方案比较有研究价值.这里先对拒绝服务攻击的对策作一简述,然后分析了几种包标记方案,指出了它们的一些缺陷,并提出了一些改进措施.其中,对基本型概率包标记方案的一个修改使得计算量大大减少.

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拒绝服务(DoS)攻击是目前最难处理的网络难题之一.最近,研究人员针对DoS攻击提出了多种方案,这些方案都各有优缺点.其中,由Savage等人提出的概率包标记方案受到了广泛的重视,也有不少的变种出现.在这一类的标记方案中,路由器以固定的概率选择是否标记一个数据包,这导致受害需要较多的数据包进行攻击路径的重构.本文提出一种自适应的标记策略,经实验验证受害者用较少的数据包即可重构攻击路径,这不仅为受害者及早地响应攻击争取了更多的时间,还限制了攻击者的伪造能力.

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拒绝服务攻击由于其高发性、大危害、难防范而成为因特网上的一大难题.研究人员为此提出了各种各样的对策,其中概率包标记具有较大的潜力.然而,现有的标记方案都存在各种各样的缺点.提出了一个新的标记方案,与其他标记方法相比,该方案具有反映灵敏,误报率低和计算量小的优点.此外,该方法还限制了攻击者伪造追踪信息的能力.

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DDoS攻击以其高发性、高破坏力和难以防范的特点,近年来成为互联网的主要安全威胁之一.研究者们提出了多种对抗DDoS攻击的方法.:乓中,Savage等人提出的概率包标记方案以其易于实施、消耗资源小等优点,引起人们的重视.然而概率包标记方案存在两个明显缺陷:多攻击路径重构时的高误报率和高计算复杂度.在概率包标记的基础上,提出了一种分块包标记方案,该方案与概率包标记方案相比具有较低的误报率和较低的计算复杂度,因而具有更高的实际应用意义.

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Road features extraction from remote sensed imagery has been a long-term topic of great interest within the photogrammetry and remote sensing communities for over three decades. The majority of the early work only focused on linear feature detection approaches, with restrictive assumption on image resolution and road appearance. The widely available of high resolution digital aerial images makes it possible to extract sub-road features, e.g. road pavement markings. In this paper, we will focus on the automatic extraction of road lane markings, which are required by various lane-based vehicle applications, such as, autonomous vehicle navigation, and lane departure warning. The proposed approach consists of three phases: i) road centerline extraction from low resolution image, ii) road surface detection in the original image, and iii) pavement marking extraction on the generated road surface. The proposed method was tested on the aerial imagery dataset of the Bruce Highway, Queensland, and the results demonstrate the efficiency of our approach.

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This paper addresses a previously unconsidered history — that of Aboriginal characters in Australian soap operas. Rejecting critical approaches which have obtained even into the 1990s, it refuses to judge these characters as 'good' or 'bad' manifestations of indigeneity. Rather, using the idea that genre is a way of closing down interpretive possibilities, the paper looks at the manner in which generic expectations around soap operas produce particular valences for these representations of Aboriginality. It points to the many ways in which these indigenous characters are insistently constructed as liminal in soap operas' structural communities - simultaneously inside and outside of the group. This is seen to accord with the suggestions of Jakubowicz et al about the ways in which Aboriginal people are positioned by wider social discourses.

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This paper describes the feasibility of the application of an Imputer in a multiple choice answer sheet marking system based on image processing techniques.

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Many existing schemes for malware detection are signature-based. Although they can effectively detect known malwares, they cannot detect variants of known malwares or new ones. Most network servers do not expect executable code in their in-bound network traffic, such as on-line shopping malls, Picasa, Youtube, Blogger, etc. Therefore, such network applications can be protected from malware infection by monitoring their ports to see if incoming packets contain any executable contents. This paper proposes a content-classification scheme that identifies executable content in incoming packets. The proposed scheme analyzes the packet payload in two steps. It first analyzes the packet payload to see if it contains multimedia-type data (such as . If not, then it classifies the payload either as text-type (such as or executable. Although in our experiments the proposed scheme shows a low rate of false negatives and positives (4.69% and 2.53%, respectively), the presence of inaccuracies still requires further inspection to efficiently detect the occurrence of malware. In this paper, we also propose simple statistical and combinatorial analysis to deal with false positives and negatives.