New financial security system utilizes smart contract within private Ethereum consortium – Nature
A modern financial security system has been developed using smart contracts within a private ethereum consortium blockchain with a hybrid optimization strategy. In the traditional stock market, data is shared across various mediators such as financial institutions and government bodies. Institutional firms must manage large volumes of data and work cooperatively to facilitate trades on the stock exchange platform. However, this process involves a complex chain of intermediaries, leading to weak transparency, extended lead times for financial settlements, and a single point of failure.
To address these issues, a blockchain (BC) computer node network is utilized to securely share a common ledger without the need for intermediaries. This innovative approach involves using a deep learning-based smart contract within a private ethereum consortium blockchain (PEC-BC) to enhance financial security. The process begins with data collection, followed by the implementation of the Dynamic Butterfly-Billiards Optimization Algorithm (DB-BOA) to select a leader block. The chosen leader block is then integrated into the Adaptive Deep Temporal Context Networks (ADTCN) using a consensus algorithm to create secure smart contracts. Parameters are optimized through DB-BOA, resulting in the development of an effective financial security system.
The financial sector faces various challenges, including integrity corruption of financial data, malicious attacks, and limitations of conventional stock exchange platforms. These issues are compounded by centralized architectures, which lead to data management inconsistencies, errors, and extended recovery times. The existing systems often lack transparency, resulting in long settlement times and restricted access for users. To overcome these limitations, innovative technologies such as matching engines and trade execution systems have been introduced.
Despite these advancements, there are still barriers to achieving seamless trading processes, efficient settlement procedures, and transparent access to data. The introduction of edge computing has revolutionized data processing by bringing core functions, network integration, and storage closer to end users. This approach ensures real-time security, application intelligence, and privacy protection, facilitating the development of advanced data processing technologies.
The hybrid heuristic-based blockchain technology employed in the advanced financial security system aims to manage financial crises effectively. By optimizing the selection of leader blocks within the blockchain using the DB-BOA algorithm, computation time, communication costs, and memory size are reduced significantly. The DB-BOA algorithm, a combination of DBOA and BOA, plays a crucial role in estimating final solutions. Additionally, the development of the ADTCN model for smart contract execution, optimized by DB-BOA, ensures efficient tuning of hyperparameters.
In conclusion, the integration of smart contracts, deep learning algorithms, and blockchain technology in the financial sector represents a significant advancement in enhancing security and efficiency. By leveraging innovative optimization strategies and hybrid algorithms, the developed system offers a robust solution for managing financial transactions and mitigating risks in the ever-evolving market landscape.
