Fraud Detection Concepts: Final Report

This report contains further analysis of the three different approaches considered for Fraud Detection, namely Rule Based, and both Supervised and Unsupervised Neural Networks. It presents a single combined tool, BRUTUS, which is considered to use the best parts of the three approaches, and then defines a prototype which can be achieved within the project's lifetime. In addition, further analysis of displayed results against legal and practical needs is provided. Keywords ACTS, ASPeCT, UMTS, Fraud Detection, Rule Based, Neural Networks, Supervised, Unsupervised, BRUTUS, Legal D18: Fraud Detection Concepts: Final Report Page 2 of 27 1 Contents 1 Contents 2 2 Executive Summary 3 3 Document Control 4 4 Document Cross References 5 5 Abbreviations and Glossary of Terms 6 6 Introduction 7 7 BRUTUS 8 8 B-Number analysis tool 14 9 Trials and demonstrations 17 10 Legal Aspects D18: Fraud Detection Concepts: Final Report Page 3 of 27 2 Executive Summary This document contains further anal..

Multi-structured redundancy

One-size-fits-all solutions have not worked well in storage systems. This is true in the enterprise where noSQL, Map-Reduce and column-stores have added value to traditional database workloads. This is also true outside the enterprise. A recent paper [7] illustrated that even the single-desktop store is a rich mixture of file systems, databases and key-value stores. Yet, in research one-size-fits-all solutions are always tempting and pointoptimizations emerge, with the current theme du jour being key-value stores [8]. Workloads naturally change their requirements over time (e.g., from update-intensive to query-intensive). This paper proposes research around a multi-structured storage architecture. Such architecture is composed of many lightweight data structures such as BTrees, keyvalue stores, graph stores and chunk stores. The call for modular storage and systems is not dissimilar to the Exokernel [4] or Anvil [10] approaches. The key difference that this paper argues about is that we want these data structures to co-exist in the same system. The system should then automatically use the right one at the right workload phase. To enable this technically, we propose to leverage the existing N-way redundancy in the data center and have each of N replicas embody a different data structure. 1 Introduction an

What is a file

For over 40 years the notion of the file, as devised by pioneers in the field of computing, has been the subject of much contention. Some have wanted to abandon the term altogether on the grounds that metaphors about files can confuse users and designers alike. More recently, the emergence of the ‘cloud ’ has led some to suggest that the term is simply obsolescent. In this paper we want to suggest that, despite all these conceptual debates and changes in technology, the term file still remains central to systems architectures and to the concerns of users. Notwithstanding profound changes in what users do and technologies afford, we suggest that files continue to act as a cohering concept, something like a ‘boundary object ’ between computer engineers and users. However, the effectiveness of this boundary object is now waning. There are increasing signs of slippage and muddle. Instead of throwing away the notion altogether, we propose that the definition of and use of files as a boundary object be reconstituted. New abstractions are needed, ones which reflect what users seek to do with their digital data, and which allow engineers to solve the networking, storage and data management problems that ensue when files move from the PC on to the networked world of today. Author Keywords File, file systems, databases, cloud computing, grammar o