The Centralized Infrastructure-Aware Reliable Data Transaction Model in IoT-Enabled MANET and Cloud Using MFOA and DNN
Reliable Data Transaction
Keywords:
Moth Flame Optimization Algorithm (MFOA), Deep Neural Networks (DNN)Abstract
A centralized data transaction mechanism for Internet of Things-enabled MANETs is presented in this dissertation. Through the use of Deep Neural Networks (DNN) for intrusion detection and the Moth Flame Optimization Algorithm (MFOA) for effective routing, the model improves network security, lowers energy consumption, and increases throughput while achieving an impressive accuracy of 99.52%.
BACKGROUND: Historically, issues with poor routing, excessive energy consumption, and security flaws have plagued mobile ad hoc networks, or MANETs. These problems are becoming increasingly important as IoT devices grow more integrated. In order to properly manage data flow and security, an effective, secure infrastructure is required because older models lacked a centralized management system.
OBJECTIVES: Developing a centralized paradigm to enhance the security and effectiveness of data transfers in IoT-enabled MANETs is the main goal of this research. In order to guarantee dependable data transfer while reducing energy consumption and enhancing overall network performance, this is accomplished by integrating MFOA for routing path optimization with DNN for intrusion detection.
METHODS: The model makes use of DNN to instantly identify network breaches and MFOA to choose the data transmission channels that use the least amount of energy. Elliptic Curve Cryptography (ECC) is used in encryption to protect data. Important parameters including accuracy, energy consumption, and throughput are used to evaluate the model's performance in comparison to other models.
RESULTS: By attaining 99.52% accuracy, 93% energy efficiency, and 72.85% faster encryption times, the suggested approach surpassed traditional methods. 95 Mbps is the maximum network throughput, indicating a significant increase over previous versions. The device is highly suited for Internet of Things applications where safe and quick data transfer is essential due to its efficiency in energy consumption and encryption.
CONCLUSION: A solid option for safe, scalable data transfers in IoT-enabled MANETs is provided by the MFOA-DNN-based paradigm. Large networks like those in smart cities and healthcare systems benefit greatly from its enhanced security, faster encryption, and greater energy efficiency. Its capacity to optimize routing and detect intrusions with high accuracy makes it the perfect choice.
