Intrusion detection is an important area of research. Traditionally, the approach taken to nd attacks is to inspect the contents of every packet. However, packet inspection cannot easily be performed at high-speeds. Therefore, researchers and operators started investigating alternative approaches, such as ow-based intrusion detection. In that approach the ow of data through the network is analyzed, instead of the contents of each individual packet. The goal of this paper is to provide a survey of current research in the area of ow-based intrusion detection. The survey starts with a motivation why ow-based intrusion detection is needed. The concept of ows is explained, and relevant standards are identied. The paper provides a classication of attacks and defense techniques and shows how ow-based techniques can be used to detect scans, worms, Botnets and Denial of Service (DoS) attacks.

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The increasing assortment of devices with IP connectivity contributes to the high popularity of video sharing over the Internet. High traffic generated by such applications at the source can be better distributed using a peer-to-peer overlay, since every user forwards information to other users. Current implementations target either live or on demand video streaming. LiveShift is an application that combines both approaches. While video is transmitted through the peer-to-peer network in a live fashion, all peers participate in a distributed storage. This adds ability to replay time-shifted streams from other peers in a distributed and scalable manner. For the demonstration, a decentralized network is used, with peers running on EMANICSLab nodes and notebook computers. LiveShift: Peer-to-peer Live Streaming with Distributed Time-Shifting

-Analysis of IP traffic is highly important, since it determines the starting point of many network management operations, such as intrusion detection, network planning, network monitoring, or accounting and billing. One of the most utilized metering data formats in analysis applications are IP (Internet Protocol) flow records. With the increase of IP traffic, such traffic analysis applications need to cope with a constantly increasing number of flow records. Typically, centralized approaches to IP traffic analysis have scalability problems, which are addressed by replacing existing hardware with more powerful CPUs and faster memory. In contrast, this paper developed and implemented SCRIPT (Scalable Real-time IP Flow Record Analysis), which defines a scalable analysis framework that can be used to distribute flow records to multiple nodes performing traffic analysis in order to balance the overall workload among those nodes. Due to its generic design, the framework developed can be extended and used to distribute other metering data, such as packet headers, payloads, or accounting records.

Grid networks aim to build a future architecture for efficient resource sharing and distributed service provisioning in a multi-provider environment. However, mobility, QoS support, and commercial service provisioningall essential issues in future networks -pose new challenges to grid networks, both from a technical and economic point of view. Therefore, the Akogrimo project aims at developing an integrated service architecture for commercial mobile grid networks. This paper presents the Akogrimo architecture and its key characteristics, integrating mobility and network layer QoS support in a commercial grid environment.