Cyril Onwubiko
Taxonomy of Fraud based on Morphological Analysis and Attribute Listing
Biography
Dr. Cyril Onwubiko is a Senior Member IEEE, Distinguished Speaker (DVP), & Board of Governor IEEE Computer Society, Past Secretary, IEEE United Kingdom and Ireland, Past Founding Chair, IEEE United Kingdom and Ireland Blockchain Group. As an active IEEE member for over 15 years, he has served in several other roles: Executive Member of the IEEE UK and Ireland Computer Society Chapter, Member of the European Public Policy Committee (EPPC) Working Group on ICT, responsible to the IEEE Board of Directors for the coordination of public policy activities, Reviewer to the IEEE Security & Privacy, IEEE Intelligence & Security Informatics (ISI), Young Professionals, Women in Engineering etc. He is also a Trustee, Board Member and Volunteer to other Charity organisations.
Cyril has over 20 years of experience in Enterprise Security Architecture, Cyber Situational Awareness, Cyber Security, Artificial Intelligence & Blockchain. Currently, he is Director, Enterprise Security Architecture at Pearson Plc, the world’s learning company. He is also Director, Artificial Intelligence, Blockchain & Cyber Security at Research Series Limited, where he directs strategy and governance in AI, Blockchain & Cyber Security. Prior to Pearson Plc, he had worked in the Financial Services, Telecommunication, Health, Government and Public Services Sectors.
He holds a PhD in Computer Network Security from Kingston University, London, UK; MSc in Internet Engineering, and BSc, first class honours, in Computer Science & Mathematics. He has authored and edited several books (8) and published over 40 peer-reviewed articles in leading and prestigious academic journals and conferences. He is the Editor of the Cyber Science series, Editor-in-Chief of the International Journal on Cyber Situational Awareness (IJCSA), and Founder of the Centre for Multidisciplinary Research, Innovation and Collaboration (C-MRiC), a not for profit and nongovernmental organisation dedicated to the advancement of outstanding research and innovation through collaboration (https://www.c-mric.com). For more information, please visit https://www.c-mric.com/cyril
Abstract
A comprehensive taxonomy of fraud is presented based on morphological analysis, attribute listing and matrix analysis. Fraud matrix and tree classification frameworks are presented and discussed. They are then utilized to classify and explain a number of the different types of frauds, shown as products, in the fraud matrix classification framework. First, triangular attributes of fraud are formulated, followed by fraud channels and elementary fraud features. Several well-known fraud types are identified using the proposed fraud classification framework. Further, new fraud types are discovered using the framework, for example, transactional frauds, automated frauds, synchronized fraud, unwitting accomplice, and ‘Robin Hood’ fraud. The importance of the taxonomy is that it can be used to classify both existing and newly identified fraud types in a way and manner that has not been previously reported; that is, it offers understanding to the different classes of frauds, the inherent threat actors behind such frauds, their capabilities, intent and the resulting nature of the frauds. This taxonomy has potential to offer insight in how appropriate countermeasures to mitigating the different types of frauds could be formulated.
