Distributed Information Retrieval using Keyword Auctions

This report motivates the need for large-scale distributed approaches to information retrieval, and proposes solutions based on keyword auctions

Trust-aware information retrieval in peer-to-peer environments

Information Retrieval in P2P environments (P2PIR) has become an active field of research due to the observation that P2P architectures have the potential to become as appealing as traditional centralised architectures. P2P networks are formed with voluntary peers that exchange information and accomplish various tasks. Some of them may be malicious peers spreading untrustworthy resources. However, existing P2PIR systems only focus on finding relevant documents, while trustworthiness of documents and document providers has been ignored. Without prior experience and knowledge about the network, users run the risk to review,download and use untrustworthy documents, even if these documents are relevant. The work presented in this dissertation provide the first integrated framework for trust-aware Information Retrieval in P2P environments, which can retrieve not only relevant but also trustworthy documents. The proposed content trust models extend an existing P2P trust management system, PeerTrust, in the context of P2PIR to compute the trust values of documents and document providers for given queries. A method is proposed to estimate global term statistics which are integrated with existing relevance-based approaches for document ranking and peer selection. Different approaches are explored to find optimal parametersettings in the proposed trust-aware P2PIR systems. Moreover, system architectures and data management protocols are designed to implement the proposed trust-aware P2PIR systems in structured P2P networks. The experimental evaluation demonstrates that P2PIR can benefit from trust-aware P2PIR systems significantly. It can importantly reduce the possibility of untrustworthy documents in the top-ranked result list. The proposed estimated global term statistics can provide acceptable and competitive retrieval accuracy within different P2PIR scenarios.EThOS - Electronic Theses Online ServiceORSSchool ScholarshipGBUnited Kingdo

Distributed WEB caching

Ph.DDOCTOR OF PHILOSOPH

Synoptic analysis techniques for intrusion detection in wireless networks

Current system administrators are missing intrusion alerts hidden by large numbers of false positives. Rather than accumulation more data to identify true alerts, we propose an intrusion detection tool that e?ectively uses select data to provide a picture of ?network health?. Our hypothesis is that by utilizing the data available at both the node and cooperative network levels we can create a synoptic picture of the network providing indications of many intrusions or other network issues. Our major contribution is to provide a revolutionary way to analyze node and network data for patterns, dependence, and e?ects that indicate network issues. We collect node and network data, combine and manipulate it, and tease out information about the state of the network. We present a method based on utilizing the number of packets sent, number of packets received, node reliability, route reliability, and entropy to develop a synoptic picture of the network health in the presence of a sinkhole and a HELLO Flood attacker. This method conserves network throughput and node energy by requiring no additional control messages to be sent between the nodes unless an attacker is suspected. We intend to show that, although the concept of an intrusion detection system is not revolutionary, the method in which we analyze the data for clues about network intrusion and performance is highly innovative

Efficient similarity-based operations for data integration

Similarity-based operations, similarity join, similarity grouping, data integrationMagdeburg, Univ., Fak. für Informatik, Diss., 2004von Eike Schalleh