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The development and deployment of practical Semantic Web applications requires technologies for the storage and retrieval of RDF data that are robust and scalable. In this paper, we describe the 3store RDF storage and query engine developed within the Advanced Knowledge Technologies project, and discuss the design rationale and optimisations behind it which enable the efficient handling of large RDF knowledge bases.

We propose a new approach for reacting to a wide variety of software failures, ranging from remotely exploitable vulnerabilities to more mundane bugs that cause abnormal program termination (e.g., illegal memory dereference). Our emphasis is in creating "self-healing" software that can protect itself against a recurring fault until a more comprehensive fix is applied.

Network Intrusion Detection and Prevention Systems have

We present an architectural framework for systematically using automated diversity to provide high assurance detection and disruption for large classes of attacks. The framework executes a set of automatically diversified variants on the same inputs, and monitors their behavior to detect divergences. The benefit of this approach is that it requires an attacker to simultaneously compromise all system variants with the same input. By constructing variants with disjoint exploitation sets, we can make it impossible to carry out large classes of important attacks. In contrast to previous approaches that use automated diversity for security, our approach does not rely on keeping any secrets. In this paper, we introduce the N-variant systems framework, present a model for analyzing security properties of N-variant systems, define variations that can be used to detect attacks that involve referencing absolute memory addresses and executing injected code, and describe and present performance results from a prototype implementation. 1.

In large-scale environments, network intrusion detection systems (NIDSs) face extreme challenges with respect to traffic volume, traffic diversity, and resource management. While crucial for acceptance and operational deployment, the research literature mainly omits such practical difficulties. In this paper, we offer an evaluation based on extensive operational experience. More specifically, we identify and explore key factors with respect to resource management and efficient packet processing and highlight their impact using a set of real-world traces. On the one hand, these insights help us gauge the trade-offs of tuning a NIDS. On the other hand, they motivate us to explore several novel ways of reducing resource requirements. These enable us to improve the state management considerably as well as balance the processing load dynamically. Overall this enables us to operate a NIDS successfully in our highvolume network environments.

Choosing the most storage- and energy-e#cient block cipher specifically for wireless sensor networks (WSNs) is not as straightforward as it seems. To our knowledge so far, there is no systematic evaluation framework for the purpose. In this paper, we have identified the candidates of block ciphers suitable for WSNs based on existing literature.

We present WebSOS, a novel overlay-based architecture that provides guaranteed access to a web server that is targeted by a denial of service (DoS) attack. Our approach exploits two key characteristics of the web environment: its design around a human-centric interface, and the extensibility inherent in many browsers through downloadable "applets." We guarantee access to a web server for a large number of previously unknown users, without requiring preexisting trust relationships between users and the system.

Good performance under extreme workloads and isolation between the resource consumption of concurrent jobs are perennial design goals of computer systems ranging from multitasking servers to network routers. In this paper we present a specialized system that computes multiple summaries of IP traffic in real time and achieves robustness and isolation between tasks in a novel way: by automatically adapting the parameters of the summarization algorithms. In traditional systems, anomalous network behavior such as denial of service attacks or worms can overwhelm the memory or CPU, making the system produce meaningless results exactly when measurement is needed most. In contrast, our measurement system reacts by gracefully degrading the accuracy of the affected summaries. The types of summaries we compute are widely used by network administrators monitoring the workloads of their networks: the ports sending the most traffic, the IP addresses sending or receiving the most traffic or opening the most connections, etc. We evaluate and compare many existing algorithmic solutions for computing these summaries, as well as two new solutions we propose here: “flow sample and hold ” and “Bloom filter tuple set counting”. Compared to previous solutions, these new solutions offer better memory versus accuracy tradeoffs and have more predictable resource consumption. Finally, we evaluate the actual implementation of a complete system that combines the best of these algorithms.

There is a growing interest in designing high-speed network devices to perform packet processing at semantic levels above the network layer. Some examples are layer-7 switches, content inspection and transformation systems, and network intrusion detection/prevention systems. Such systems must maintain perflow state in order to correctly perform their higher-level processing. A basic operation inherent to per-flow state management for a transport protocol such as TCP is the task of reassembling any out-of-sequence packets delivered by an underlying unreliable network protocol such as IP. This seemingly prosaic task of reassembling the byte stream becomes an order of magnitude more difficultto soundly execute when conducted in the presence of an adversary whose goal is to either subvert the higher-level analysis or impede the operation of legitimate traffic sharing the same network path. We present a design of a hardware-based high-speed TCP reassembly mechanism that is robust against attacks. It is intended to serve as a module used to construct a variety of network analysis systems, especially intrusion prevention systems. Using trace-driven analysis of out-of-sequence packets, we first characterize the dynamics of benign TCP trafficand show how we can leverage the results to design a reassembly mechanism that is efficientwhen dealing with non-attack traffic. We then refine the mechanism to keep the system effective in the presence of adversaries. We show that although the damage caused by an adversary cannot be completely eliminated, it is possible to mitigate the damage to a great extent by careful design and resource allocation. Finally, we quantify the trade-off between resource availability and damage from an adversary in terms of Zombie equations that specify, for a given configuration of our system, the number of compromised machines an attacker must have under their control in order to exceed a specified notion of “acceptablecollateral damage.” 1