Multi-Dimensional Risk Analysis of Insider Threats to Confidential Data in Distributed E-Commerce Clouds

Abstract

Insider threats pose a critical risk to distributed e-commerce clouds, given that legitimate users possess direct access to systems, privileged credentials, and organizational processes. Individuals within an enterprise—employees, contractors, or third-party associates—can exploit their positions to steal sensitive data, sabotage infrastructure, or bypass security controls. E-commerce operations store financial information, personal data, and intellectual property in interconnected cloud environments, creating an extensive attack surface when insider threats materialize. Unintentional insider threats may arise from misconfigured controls, negligent handling of credentials, or human error in day-to-day tasks. Motivated insiders, however, target confidential data for economic gain, corporate espionage, or personal vendettas, often escaping detection because of their familiarity with internal procedures and security gaps. Distributed e-commerce clouds complicate conventional security measures by segmenting data and services across multiple regions, availability zones, and microservices. The resulting infrastructure relies on complex orchestration mechanisms, software-defined networks, and dynamic scaling of resources. Access control models may inadvertently assign broader privileges than necessary, especially when teams manage large volumes of user roles and credentials. Incomplete visibility over containerized workloads, serverless functions, and multi-cloud integrations compounds the challenge of detecting suspicious insider activities. Even seemingly benign actions, such as resource provisioning or routine maintenance, can escalate into data exfiltration attempts if not supervised and logged effectively