Abstract

Where organizations used to rely on employees tenured with their company, the Great Resignation has presented new problems to organizational structure and fortification. Such a process usually leads to disrupted employee productivity and most importantly, increased vulnerability to cyber threats. Loyal workers, intentionally or unintentionally disloyal workers, and employees who leave the organization can compromise organizational confidential information, such as innovation, customer data, and other data that the organization considers to be highly valuable. Research has also revealed that workforce transition time is also the highest-risk activity period for insiders, wherein activities like the unauthorized download of data or accidental data leaks when offboarding an employee are likely to occur. Moreover, there are difficulties, particularly for organizations that cannot apply adequate access controls and monitoring during the notice periods, making them much more sensitive to data leaks. Further, this paper examines these paramount cybersecurity threats and offers an organized framework for their mitigation. Explores how the risks can be reduced under this through policies like strong access controls, opaque data monitoring systems, and comprehensive offboarding. To get practical recommendations for managing the problem with data sharing, the example of using machine learning to realize the mechanisms for identifying anomalies and graph-theory-based mathematical models is given. Thus, this research provides a comprehensive set of procedures to address the consequences of the Great Resignation for organizations and safeguard their assets during worker turnovers.