Online banking fraud occurs whenever a criminal can seize accounts and transfer funds from an individual’s online bank account.Successfully preventing this requires the detection of as many fraudsters as possible,wit...Online banking fraud occurs whenever a criminal can seize accounts and transfer funds from an individual’s online bank account.Successfully preventing this requires the detection of as many fraudsters as possible,without producing too many false alarms.This is a challenge for machine learning owing to the extremely imbalanced data and complexity of fraud.In addition,classical machine learning methods must be extended,minimizing expected financial losses.Finally,fraud can only be combated systematically and economically if the risks and costs in payment channels are known.We define three models that overcome these challenges:machine learning-based fraud detection,economic optimization of machine learning results,and a risk model to predict the risk of fraud while considering countermeasures.The models were tested utilizing real data.Our machine learning model alone reduces the expected and unexpected losses in the three aggregated payment channels by 15%compared to a benchmark consisting of static if-then rules.Optimizing the machine-learning model further reduces the expected losses by 52%.These results hold with a low false positive rate of 0.4%.Thus,the risk framework of the three models is viable from a business and risk perspective.展开更多
Privilege user is needed to manage the commercial transactions, but a super-administrator may have monopolize power and cause serious security problem. Relied on trusted computing technology, a privilege separation me...Privilege user is needed to manage the commercial transactions, but a super-administrator may have monopolize power and cause serious security problem. Relied on trusted computing technology, a privilege separation method is proposed to satisfy the security management requirement for information systems. It authorizes the system privilege to three different managers, and none of it can be interfered by others. Process algebra Communication Sequential Processes is used to model the three powers mechanism, and safety effect is analyzed and compared.展开更多
基金from any funding agency in the public,commercial,or not-for-profit sectors.
文摘Online banking fraud occurs whenever a criminal can seize accounts and transfer funds from an individual’s online bank account.Successfully preventing this requires the detection of as many fraudsters as possible,without producing too many false alarms.This is a challenge for machine learning owing to the extremely imbalanced data and complexity of fraud.In addition,classical machine learning methods must be extended,minimizing expected financial losses.Finally,fraud can only be combated systematically and economically if the risks and costs in payment channels are known.We define three models that overcome these challenges:machine learning-based fraud detection,economic optimization of machine learning results,and a risk model to predict the risk of fraud while considering countermeasures.The models were tested utilizing real data.Our machine learning model alone reduces the expected and unexpected losses in the three aggregated payment channels by 15%compared to a benchmark consisting of static if-then rules.Optimizing the machine-learning model further reduces the expected losses by 52%.These results hold with a low false positive rate of 0.4%.Thus,the risk framework of the three models is viable from a business and risk perspective.
文摘Privilege user is needed to manage the commercial transactions, but a super-administrator may have monopolize power and cause serious security problem. Relied on trusted computing technology, a privilege separation method is proposed to satisfy the security management requirement for information systems. It authorizes the system privilege to three different managers, and none of it can be interfered by others. Process algebra Communication Sequential Processes is used to model the three powers mechanism, and safety effect is analyzed and compared.
