3 research outputs found
An empiric path towards fraud detection and protection for NFC-enabled mobile payment system
The synthesis of NFC technology accompanying mobile payment is a state-of-the-art resolution for payment users. In view of rapid development in electronic payment system there is rise in fraudulent activity in banking transactions associated with credit cards and card-not-present transaction. M-Commerce aid the consumers and helps to bestow real-time information in payment system. Due to the familiarization of m-commerce there is cogent increase in the number of fraudulent activities, emerging in billions of dollar loss every year worldwide. To absolute the security breaches, payment transactions could be confined by considering various parameters like user and device authentication, consumer behavior pattern, geolocation and velocity. In this paper we formally assay NFC-enabled mobile payment fraud detection ecosystem using score-based evaluation method. The fraud detection ecosystem will provide a solution based on transaction risk-modeling, scoring transaction, business rule-based, and cross-field referencing. The score-based evaluation method will analyze the transaction and reckon every transaction for fraud risk and take pertinent decision
An empiric path towards fraud detection and protection for NFC-enabled mobile payment system
The synthesis of NFC technology accompanying mobile payment is a state-of-the-art resolution for payment users. In view of rapid development in electronic payment system there is rise in fraudulent activity in banking transactions associated with credit cards and card-not-present transaction. M-Commerce aid the consumers and helps to bestow real-time information in payment system. Due to the familiarization of m-commerce there is cogent increase in the number of fraudulent activities, emerging in billions of dollar loss every year worldwide. To absolute the security breaches, payment transactions could be confined by considering various parameters like user and device authentication, consumer behavior pattern, geolocation and velocity. In this paper we formally assay NFC-enabled mobile payment fraud detection ecosystem using score-based evaluation method. The fraud detection ecosystem will provide a solution based on transaction risk-modeling, scoring transaction, business rule-based, and cross-field referencing. The score-based evaluation method will analyze the transaction and reckon every transaction for fraud risk and take pertinent decision. Copyright © 2019 Universitas Ahmad Dahlan. All rights reserved
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A Framework for the Systematic Evaluation of Malware Forensic Tools
Following a series of high profile miscarriages of justice linked to questionable expert evidence, the post of the Forensic Science Regulator was created in 2008 with a remit to improve the standard of practitioner competences and forensic procedures. It has since moved to incorporate a greater level of scientific practice in these areas, as used in the production of expert evidence submitted to the UK Criminal Justice System. Accreditation to their codes of practice and conduct will become mandatory for all forensic practitioners by October 2017. A variety of challenges with expert evidence are explored and linked to a lack of a scientific methodology underpinning the processes followed. In particular, the research focuses upon investigations where malicious software (‘malware’) has been identified.
A framework, called the ‘Malware Analysis Tool Evaluation Framework’ (MATEF), has been developed to address this lack of methodology to evaluate software tools used during investigations involving malware. A prototype implementation of the framework was used to evaluate two tools against a population of over 350,000 samples of malware. Analysis of the findings indicated that the choice of tool could impact on the number of artefacts observed in malware forensic investigations as well as identifying the optimal execution time for a given tool when observing malware artefacts.
Three different measures were used to evaluate the framework. The first of these evaluated the framework against the requirements and determined that these were largely met. Where the requirements were not met these are attributed to matters either outside scope or the fledgling nature of the research. Another measure used to evaluate the framework was to consider its performance in terms of speed and resource utilisation. This identified scope for improvement in terms of the time to complete a test and the need for more economical use of disk space. Finally, the framework provides a scientific means to evaluate malware analysis tools, hence addressing the Research Question subject to the level at which ground truth is established.
A number of contributions are produced as the output of this work. First there is confirmation for the case for a lack of trusted practice in the field of malware forensics. Second, the MATEF itself, as it facilitates the production of empirical evidence of a tool’s ability to detect malware artefacts. A third contribution is a set of requirements for establishing trusted practice in the use of malware artefact detection tools. Finally, empirical evidence that supports both the notion that the choice of tool can impact on the number of artefacts observed in malware forensic investigations as well as identifying the optimal execution time for a given tool when observing malware artefacts