A Lightweight and Intelligent Micro-Transaction Verification Framework for Secure FinTech Applications
Abstract
The FinTech applications need secure and low-latency, resource-efficient verification of transactions that require microtransactions. This type of repetitive, small-amount transactions requires special cryptographic solutions to ensure integrity and authenticity. Current verification methods employ complex cryptographic algorithms, which impose significant time and energy overhead on processors. Mobile and IoT FinTech systems are particularly affected. These inefficiencies may hurt scalability and usability. Bloom filter Framework verification is introduced using Bloom filter data structures and lightweight cryptographic hashing techniques. This will address the raised issues. The Bloom Filter-Based Lightweight Verification Framework is effective for pre-validation of signature-based microtransactions and for probabilistic membership checks, and it reduces unnecessary cryptographic messages, thereby enhancing security. The experimental results indicate that BFLVF reduces computation cost by a factor of 40 and verification effectiveness by a factor of 55 relative to existing cryptographic algorithms, but exhibits a high false-positive probability. The architecture offers scalable, secure, and efficient micro-transaction validation. The plan enhances the legitimacy of FinTechs. The BFLVF uses 40 percent less CPU overhead, 55 % faster invalidation, and 35% less energy than cryptographic-only systems. It minimizes verification time to 3.1 ms, maximizes throughput to 260 Tx / s, minimizes false positives to 0.8 or less, and scales to 1 M signatures with a Bloom filter error rate of 0.18%.