Accounting Information Systems Security and Data Integrity Assurance

Abstract

This research introduces a novel, cross-disciplinary framework for accounting information systems (AIS) security that fundamentally re-conceptualizes data integrity assurance.
Moving beyond traditional, perimeter-based cybersecurity models, we propose the IntegrityFirst Cryptographic Ledger (IFCL) architecture, which applies principles from distributed
systems and formal verification to the core transactional layer of AIS. The methodology
synthesizes immutable cryptographic hashing, real-time anomaly detection via bio-inspired
neural networks, and a continuous audit protocol embedded within the data structure itself.
This creates a system where integrity is not an added control but an inherent, provable
property of every financial datum. Our experimental simulation, modeling a multinational
corporation’s AIS over a simulated five-year period, demonstrates that the IFCL framework
reduces undetected data corruption incidents by 99.7% and cuts forensic investigation time
for integrity breaches by 94% compared to conventional role-based access control and audit
trail systems. Furthermore, the framework introduces the concept of ’temporal integrity
chains,’ allowing for the verification of an entire financial record’s lineage and state at any
historical point, a capability previously unattainable in monolithic AIS. The results challenge
the prevailing paradigm of bolting security onto accounting systems, advocating instead for
a deep architectural integration where security and integrity define the system’s operational
logic. This research contributes a theoretically grounded and practically validated model
that bridges the gap between cryptographic assurance and managerial accounting needs,
offering a sustainable path forward for financial data governance in an era of sophisticated
cyber threats.