Intelligent Financial Fraud Detection Practices: An Investigation

Financial fraud is an issue with far reaching consequences in the finance industry, government, corporate sectors, and for ordinary consumers. Increasing dependence on new technologies such as cloud and mobile computing in recent years has compounded the problem. Traditional methods of detection involve extensive use of auditing, where a trained individual manually observes reports or transactions in an attempt to discover fraudulent behaviour. This method is not only time consuming, expensive and inaccurate, but in the age of big data it is also impractical. Not surprisingly, financial institutions have turned to automated processes using statistical and computational methods. This paper presents a comprehensive investigation on financial fraud detection practices using such data mining methods, with a particular focus on computational intelligence-based techniques. Classification of the practices based on key aspects such as detection algorithm used, fraud type investigated, and success rate have been covered. Issues and challenges associated with the current practices and potential future direction of research have also been identified.Comment: Proceedings of the 10th International Conference on Security and Privacy in Communication Networks (SecureComm 2014

Reinforcement learning for efficient network penetration testing

Penetration testing (also known as pentesting or PT) is a common practice for actively assessing the defenses of a computer network by planning and executing all possible attacks to discover and exploit existing vulnerabilities. Current penetration testing methods are increasingly becoming non-standard, composite and resource-consuming despite the use of evolving tools. In this paper, we propose and evaluate an AI-based pentesting system which makes use of machine learning techniques, namely reinforcement learning (RL) to learn and reproduce average and complex pentesting activities. The proposed system is named Intelligent Automated Penetration Testing System (IAPTS) consisting of a module that integrates with industrial PT frameworks to enable them to capture information, learn from experience, and reproduce tests in future similar testing cases. IAPTS aims to save human resources while producing much-enhanced results in terms of time consumption, reliability and frequency of testing. IAPTS takes the approach of modeling PT environments and tasks as a partially observed Markov decision process (POMDP) problem which is solved by POMDP-solver. Although the scope of this paper is limited to network infrastructures PT planning and not the entire practice, the obtained results support the hypothesis that RL can enhance PT beyond the capabilities of any human PT expert in terms of time consumed, covered attacking vectors, accuracy and reliability of the outputs. In addition, this work tackles the complex problem of expertise capturing and re-use by allowing the IAPTS learning module to store and re-use PT policies in the same way that a human PT expert would learn but in a more efficient way

Innovation and Employability in Knowledge Management Curriculum Design

During 2007/8, Southampton Solent University worked on a Leadership Foundation project focused on the utility of the multi-functional team approach as a vehicle to deliver innovation in strategic and operational terms in higher education (HE). The Task-Orientated Multi-Functional Team Approach (TOMFTA) project took two significant undertakings for Southampton Solent as key areas for investigation, one academic and one administrative in focus. The academic project was the development of an innovative and novel degree programme in knowledge management (KM). The new KM Honours degree programme is timely both in recognition of the increasing importance to organisations of knowledge as a commodity, and in its adoption of a distinctive structure and pedagogy. The methodology for the KM curriculum design brings together student-centred and market-driven approaches: positioning the programme for the interests of students and requirements of employers, rather than just the capabilities of staff; while looking at ways that courses can be delivered with more flexibility, e.g. accelerated and block-mode; with level-differentiated activities, common cross-year content and material that is multi-purpose for use in short courses. In order to permit context at multiple levels in common, a graduate skills strand is taught separately as part of the University’s business-facing education agenda. The KM portfolio offers a programme of practically-based courses integrating key themes in knowledge management, business, information distribution and development of the media. They develop problem-solving, communications, teamwork and other employability skills as well as the domain skills needed by emerging information management technologies. The new courses are built on activities which focus on different aspects of KM, drawing on existing content as a knowledge base. This paper presents the ongoing development of the KM programme through the key aspects in its conception and design

Connecting worlds: the translation of international auditing standards into post-Soviet audit practice

This paper analyses the use and circulation of nternational auditing standards within a large post-Soviet Russian audit firm, as it faces up to the challenges of international harmonisation. It describes this process as one of ‘connecting worlds’ and translation. In a detailed field study based investigation, it traces various attempts to articulate and link Soviet and post-Soviet worlds, old and new imagined audit worlds. The paper underscores the fragile and precarious nature of international standardisation projects. It shows how ideals of audit universalism and international comparability become enmeshed in, and challenged by, global divisions of audit labour, problems and practices of power and exclusion, and struggles for intra-professional distinction, which in turn undermine as well as promote the connecting of worlds through standards

AUDITOR\u27S ASSISTANT: A knowledge engineering tool for audit decisions

https://egrove.olemiss.edu/dl_proceedings/1039/thumbnail.jp