Data Security within Cyber Defence & Engineering (CDE) serves as the backbone for effective fraud risk management. This domain focuses on protecting critical business information against unauthorized access, alteration, and loss, with the aim of preventing financial and reputational damage. In a complex environment of increasingly sophisticated attacks and insider threats, a layered security architecture is employed that combines technical controls, policy frameworks, and awareness measures. Data classification and encryption play a central role, as does monitoring data flows using advanced detection and logging systems. The goal is to ensure data confidentiality, integrity, and availability so that all organizational levels enjoy robust protection against (among others) financial mismanagement, fraud, bribery, money laundering, corruption, and violations of international sanctions.
Financial Mismanagement
Within the scope of data security, financial mismanagement can occur through manipulation of sensitive financial datasets—such as balance sheets and cash flow reports—by malicious actors who gain access to unencrypted data storage or backups. Strict role-based access controls (RBAC) and attribute-based access controls (ABAC) reduce this risk by granting read and write permissions only to specific users and applications. Encryption at rest and in transit using industry-standard algorithms (AES-256, TLS 1.3) prevent intercepted files from being usable. Regular key rotation and hardware security modules (HSMs) provide additional layers of protection for cryptographic keys. By implementing immutability settings on storage media, backups are treated as unalterable, allowing fraudulent changes to be reversed and audited at any time.
Fraud
Advanced fraud techniques such as credential stuffing, session hijacking, or API manipulation require an integrated data security framework. Monitoring user activity via Security Information and Event Management (SIEM) systems enables real-time correlation of log data, allowing unusual patterns—such as large data transfers or irregular queries—to be promptly flagged. Data Loss Prevention (DLP) tools inspect content based on context and metadata to automatically classify confidential information and quarantine suspicious data movements. Threat intelligence feeds enrich logs with indicators of compromise (IoCs) and indicators of attack (IoAs), enabling interactive, detailed forensic analyses to unravel fraudulent chains.
Bribery
Data security prevents digital bribery practices through the implementation of end-to-end audit trails for all contract and billing-related systems. Immutable ledger technologies—such as permissioned blockchains—ensure that every change to contract documents is indisputably recorded. Multi-factor authentication (MFA) combined with contextual access controls (such as geofencing and time-based restrictions) prevents unauthorized parties from viewing or altering sensitive data. Automated compliance checks continuously validate payment transactions against predefined rules, such as thresholds and vendor profiles. In case of deviations, an orchestration workflow is triggered that blocks all involved data streams and generates a detailed forensic report.
Money Laundering
A data security strategy against money laundering focuses on monitoring transactional records and API calls. Network and application layer encryption combined with deep packet inspection (DPI) enables real-time analysis of encrypted transfers for pattern anomalies indicating artificially inflated amounts or automated transaction flows. Data anomalies are detected by machine learning models that use normal user and system behavior as a baseline. Data enrichment is achieved through linkage with external sources such as PEP lists, sanction lists, and negative media indexes, so that every transaction is immediately checked against compliance requirements and risk scores are automatically updated.
Corruption
Data security combats corruption by enforcing strict change management processes for all governance and decision-making tools. Integrity monitoring systems detect unauthorized changes in policy documents and role structures by continuously validating file hashes against a trusted baseline. Secure logging with append-only storage ensures that all actions, including views and downloads, are permanently recorded. Periodic audits of audit trails and automated enforcement of governance workflows—such as via digital signatures—ensure transparency and undeniability at every step of decision-making, so any manipulation attempts are relentlessly exposed.
Violations of International Sanctions
Preventing sanctions violations through data flows requires real-time screening of all outgoing communications and transactions. Advanced proxy and gateway systems apply SSL/TLS interception to analyze encrypted payloads against sanction lists and watchlists. Geo-IP filtering and real-time DNS anomaly detection block requests to high-risk regions or entities. Data classification frameworks automatically label sensitive information, after which data exfiltration prevention modules ensure that classified data is only transmitted through approved channels. Immediately after a potential violation, an escalation to legal and compliance teams follows, including automated reports for regulators to guarantee full compliance.
