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This paper explores the different insider employee-led cyber frauds (IECF) based on the recent large-scale fraud events of prominent Indian banking institutions. Examining the different types of fraud and appropriate control measures will protect the banking industry from fraudsters. In this study, we identify and classify Cyber Fraud (CF), map the severity of the fraud on a scale of priority, test the mitigation effectiveness, and propose optimal mitigation measures. The identification and classification of CF losses were based on a literature review and focus group discussions with risk and vigilance officers and cyber cell experts. The CF was analyzed using secondary data. We predicted and prioritized CF based on machine learning-derived Random Forest (RF). An efficient fraud mitigation model was developed based on an offender-victim-centric approach. Mitigation is advised both before and after fraud occurs. Through the findings of this research, banks and fraud investigators can prevent CF by detecting it quickly and controlling it on time. This study proposes a structured, sustainable CF mitigation plan that protects banks, employees, regulators, customers, and the economy, thus saving time, resources, and money. Further, these mitigation measures will improve the reputation of the Indian banking industry and ensure its survival. [ABSTRACT FROM AUTHOR]

Social networking sites and apps (SNSAs) are being used more frequently across the world and yet the nature of this online environment and associated interactions are not fully understood. With no restrictions for SNSAs use related to specific geographical regions, language, age, gender, educational level, or any other factors, it is important to find a concept to describe and explain the components of this online environment and their relationships. This paper describes the environment of SNSAs use by Saudi postgraduate students from the perspective of second-generation activity theory (AT). The findings supported the theoretical framework of AT as a useful lens in understanding SNSAs use from the perspective of students, particularly in a cultural environment where physical communication has restrictions based on gender. A similar AT model can be drawn for the use of SNSAs, taking the perspective of different groups of academic users. The flexibility of the AT model appears at the level of SNSAs as technical and physical tools, and at the level of users' community, which was managed by the explicit and implicit rules relating to communication. This feature reveals the way in which this extended framework can be used to indicate pertinent features of SNSAs. [ABSTRACT FROM AUTHOR]