Community Health Information Tracking System using Short Message Service (chitSMS) is an extension of CHITS which is a system that stores health records of patients in the barangay. Another project incorporated a mobi...
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Random scale-free overlay topologies provide a number of properties like for example high resilience against failures of random nodes, small (average) diameter as well as good expansion and congestion characteristics ...
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Malicious botnets threaten the Internet by DDoS-attacks, spam, information theft and other criminal activities. They are using increasingly sophisticated techniques to hide the Command and Control traffic. Many existi...
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ISBN:
(纸本)9781424488629
Malicious botnets threaten the Internet by DDoS-attacks, spam, information theft and other criminal activities. They are using increasingly sophisticated techniques to hide the Command and Control traffic. Many existing detection techniques can be defeated by encryption, tunneling in popular protocols, delays, and flow perturbation. We introduce a new DNS-based detection approach, that detects botnet collusion by anomalies in the degree distribution of visited domains, without any assumption about message content and statistical properties of the traffic. The proposed technique is difficult to evade, without major changes in the bot Command and Control Infrastructure or reduced utility. We evaluate evasion possibilities, derive a theoretical model of the detector performance and test the detector with a combination of captured Internet traffic and simulated botnet-traffic.
P2P systems can benefit from reputation mechanisms to promote cooperation and help peers to identify good service providers. However, in spite of a large number of proposed reputation mechanisms, few have been investi...
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P2P systems can benefit from reputation mechanisms to promote cooperation and help peers to identify good service providers. However, in spite of a large number of proposed reputation mechanisms, few have been investigated in real situations. BarterCast is a distributed reputation mechanism used by our Internet-deployed Bittorent-based file-sharing client Tribler. In BarterCast, each peer uses messages received from other peers to build a weighted, directed subjective graph that represents the upload and download activity in the system. A peer calculates the reputations of other peers by applying the maxflow algorithm to its subjective graph. For efficiency reasons, only paths of at most two hops are considered in this calculation. In this paper, we identify and assess three potential modifications to BarterCast for improving its accuracy and coverage (fraction of peers for which a reputation value can be computed). First, a peer executes maxflow from the perspective of the node with the highest betweenness centrality in its subjective graph instead of itself. Second, we assume a gossiping protocol that gives each peer complete information about upload and download activities in the system, and third, we lift the path length restriction in the maxflow algorithm. To assess these modifications, we crawl the Tribler network and collect the upload and download actions of the peers for three months. We apply BarterCast with and without the modifications on the collected data and measure accuracy and coverage.
Background: Coevolutionary systems like hosts and their parasites are commonly used model systems for evolutionary studies. Inferring the coevolutionary history based on given phylogenies of both groups is often done ...
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In this paper we present the implementation of a framework for accelerating training and classification of arbitrary Convolutional Neural Networks (CNNs) on the GPU. CNNs are a derivative of standard Multilayer Percep...
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In this paper we present the implementation of a framework for accelerating training and classification of arbitrary Convolutional Neural Networks (CNNs) on the GPU. CNNs are a derivative of standard Multilayer Perceptron (MLP) neural networks optimized for two-dimensional pattern recognition problems such as Optical Character Recognition (OCR) or face detection. We describe the basic parts of a CNN and demonstrate the performance and scalability improvement that can be achieved by shifting the computation-intensive tasks of a CNN to the GPU. Depending on the network topology training and classification on the GPU performs 2 to 24 times faster than on the CPU. Furthermore, the GPU version scales much better than the CPU implementation with respect to the network size.
LEDBAT is a new congestion control algorithm which was proposed in an IETF draft in March 2009. LEDBAT's goal is to provide a less-than-best-effort data transport service, i.e. a LEDBAT flow should back-off in the...
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LEDBAT is a new congestion control algorithm which was proposed in an IETF draft in March 2009. LEDBAT's goal is to provide a less-than-best-effort data transport service, i.e. a LEDBAT flow should back-off in the presence of other competing flows (TCP flows in particular). Because of its intended friendliness to competing flows, LEDBAT has already been implemented in the popular Bittorrent client uTorrent. In this paper we present performance evaluation results for our Python implementation of LEDBAT. We ran tests both in emulated networks as well as in real world networks. One of the tests involved approximately 300 volunteers spread throughout the world.
In this paper, we propose a taxonomy that characterizes and classifies different components of autonomic application management in Grids. We also survey several representative Grid systems developed by various project...
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This paper presents a group communication system for mobile devices, called distributedGCS. Mobile communication is slow, expensive and suffers from occasional disconnections, especially when users are moving. Distrib...
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