A Secure Transaction Execution Model for Maintaining the Integrity of Fog-Based Databases
Brajendra Panda, Anthony Pham · 2025
The highly interconnected nature of fog environments and the vast amount of data stored in them create a bigger attack surface, making the system easily susceptible to cyberattacks. Moreover, the highly interconnected nature also allows any damage to a fog-based database caused by an attacker to spread rapidly to other nodes. This is especially worrisome for real-time processing, where breaches can have a swift and significant impact. When valid transactions trigger updates based on a compromised object's value, the damage quickly extends to other nodes and the data items they contain, adversely impacting the real-time services offered by the system. The primary goal of this research is to help maintain the integrity of fog databases. Although such work has been performed before, this work is different in that it significantly reduces the system downtime by taking a proactive approach. Unlike the previously published works, which try to do damage assessment and recovery after an attack, this paper focuses on detecting and resolving malicious transactions, thus reducing the system downtime required during the recovery process. The process begins with identifying suspicious transactions based on common patterns. When a transaction is flagged, the algorithm segments groups of suspicious transactions into separate log files. Since this new segment will be a significantly small file, performing damage assessment and recovery on it will be swift. Through simulation, we have proved the efficacy of our model.