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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]

The formation of information security behavioural intention (ISBI) can be complex and dynamic in different contexts. This paper aims to examine and compare different users' ISBI formalisation mechanisms when dealing with their personal affairs (non-work users) and organisational affairs (work users). Drawing on two principles of Conservation of Resources (COR) theory (i.e. resource loss principle, and resource gain principle), we developed two models to examine how situational support affects ISBI formation. The results of a study of 432 non-worker users and 261 work users indicate a curvilinear relationship between situational support and ISBI through subjective norms and risk perception for non-worker users, whilst a linear relationship via subjective norms is found for worker users. This is the first time that COR has been applied to explain the formation of ISBI. The findings broaden the research scope of individuals' ISBI by revealing how situational support affects the formalisation mechanism for different users in cross-contexts. The theoretical and practical implications of the findings and the future study are discussed. [ABSTRACT FROM AUTHOR]

While there is a growing body of literature on information privacy suggesting different mechanisms of how people's privacy concerns might be impacting their attitudes and behaviour when using social media, recent questionable data use practices by social media platforms and third parties call for a renewed validation of existing information privacy models. The objective of this research is to re-examine the variables predicting why people disclose information on social media. Building on previous work, this paper puts forward a comprehensive Privacy Concerns and Social Media Use Model (PC-SMU) and evaluates it in a specific cultural and legal environment (social media users from a single county, Canada). The study delves into the privacy paradox and shows that the benefits of using social media are the main driver of self-disclosure, and that self-disclosing behaviours are nuanced by the users' information privacy protection strategies. We also find that higher levels of social media literacy, and concerns about organisational threats to a lesser extent, lead to higher levels of information privacy management, emphasizing the importance of educating users about how to use the different privacy and security features provided by social media platforms. [ABSTRACT FROM AUTHOR]