6 research outputs found

    Content-based Publish/Subscribe in Software-defined Networks

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    With SDN, content-based publish/subscribe can be implemented on the network layer instead of using an application layer broker network. We present two methods realizing notification distribution with OpenFlow and P4, respectively

    Practical high-throughput content-based routing using unicast state and probabilistic encodings

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    We address the problem that existing publish/subscribe messaging systems, including such commonly used ones as Apache’s ActiveMQ and IBM’s WebSphere MQ, exhibit degraded end-to-end throughput performance in a wide-area network setting. We contend that the cause of this problem is the lack of an appropriate routing protocol. Building on the idea of a content-based network, we introduce a protocol called B-DRP that can demonstrably improve the situation. A content-based network is a content-based publish/subscribe system architected as a datagram network: a message is forwarded hop-by-hop and delivered to any and all hosts that have expressed interest in the message content. This fits well with the character of a wide-area messaging system. B-DRP is based on two main techniques: a message delivery mechanism that utilizes and exploits unicast forwarding state, which can be easily maintained using standard protocols, and a probabilistic data structure to effciently represent and evaluate receiver interests. We present the design of B-DRP and the results of an experimental evaluation that demonstrates its support for improved throughput in a wide-area setting

    Congestion avoidance in overlay networks through multipath routing

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    Overlay networks relying on traditional multicast routing approaches use only a single path between a sender and a receiver. This path is selected based on latency, with the goal of achieving fast delivery. Content is routed through links with low latency, ignoring slower links of the network which remain unused. With the increasing size of content on the Internet, this leads to congestion, messages are dropped and have to be retransmitted. A multicast multipath congestion-avoidance routing scheme which uses multiple bottleneck-disjoint paths between senders and receivers was developed, as was a linear programming model of the network to distribute messages intelligently across these paths according to two goals: minimum network usage and load-balancing. The former aims to use as few links as possible to perform routing, while the latter spreads messages across as many links as possible, evenly distributing the traffic. Another technique, called message splitting, was also used. This allows nodes to send a single copy of a message with multiple receivers, which will then be duplicated by a node closer to the receivers and sent along separate paths only when required. The model considers all of the messages in the network and is a global optimisation. Nevertheless, it can be solved quickly for large networks and workloads, with the cost of routing remaining almost entirely the cost of finding multiple paths between senders and receivers. The Gurobi linear programming solver was used to find solutions to the model. This routing approach was implemented in the NS-3 network simulator. The work is presented as a messaging middleware scheme, which can be applied to any overlay messaging network.Open Acces

    Community-Based Intrusion Detection

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    Today, virtually every company world-wide is connected to the Internet. This wide-spread connectivity has given rise to sophisticated, targeted, Internet-based attacks. For example, between 2012 and 2013 security researchers counted an average of about 74 targeted attacks per day. These attacks are motivated by economical, financial, or political interests and commonly referred to as “Advanced Persistent Threat (APT)” attacks. Unfortunately, many of these attacks are successful and the adversaries manage to steal important data or disrupt vital services. Victims are preferably companies from vital industries, such as banks, defense contractors, or power plants. Given that these industries are well-protected, often employing a team of security specialists, the question is: How can these attacks be so successful? Researchers have identified several properties of APT attacks which make them so efficient. First, they are adaptable. This means that they can change the way they attack and the tools they use for this purpose at any given moment in time. Second, they conceal their actions and communication by using encryption, for example. This renders many defense systems useless as they assume complete access to the actual communication content. Third, their actions are stealthy — either by keeping communication to the bare minimum or by mimicking legitimate users. This makes them “fly below the radar” of defense systems which check for anomalous communication. And finally, with the goal to increase their impact or monetisation prospects, their attacks are targeted against several companies from the same industry. Since months can pass between the first attack, its detection, and comprehensive analysis, it is often too late to deploy appropriate counter-measures at businesses peers. Instead, it is much more likely that they have already been attacked successfully. This thesis tries to answer the question whether the last property (industry-wide attacks) can be used to detect such attacks. It presents the design, implementation and evaluation of a community-based intrusion detection system, capable of protecting businesses at industry-scale. The contributions of this thesis are as follows. First, it presents a novel algorithm for community detection which can detect an industry (e.g., energy, financial, or defense industries) in Internet communication. Second, it demonstrates the design, implementation, and evaluation of a distributed graph mining engine that is able to scale with the throughput of the input data while maintaining an end-to-end latency for updates in the range of a few milliseconds. Third, it illustrates the usage of this engine to detect APT attacks against industries by analyzing IP flow information from an Internet service provider. Finally, it introduces a detection algorithm- and input-agnostic intrusion detection engine which supports not only intrusion detection on IP flow but any other intrusion detection algorithm and data-source as well
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