Designing an Enhanced Elliptic Curve Cryptography Model for IoT Security in Smart Cities: Integrating Machine Learning for Cyber Attack Detection

The proliferation of Internet of Things (IoT) devices in smart cities has led to an explosion of interconnected systems, resulting in increased vulnerabilities to cyber-attacks. These devices often handle sensitive personal data, making them prime targets for malicious attacks. Elliptic Curve Cryptography (ECC) has been recognized for its efficient and secure encryption mechanism in IoT applications, but it still faces challenges in adapting to dynamic environments with high computational demand and network congestion typical in smart cities. The core motivation of this research is to design an enhanced ECC model tailored to the security needs of IoT systems, focusing on optimizing security while maintaining low computational overhead. The primary objective of this study is to integrate ECC with machine learning (ML) techniques to develop a hybrid model that not only secures data communication but also detects and mitigates cyber-attacks in real-time. The proposed methodology combines ECC’s cryptographic strength with machine learning algorithms to create an intelligent security framework capable of both defending against attacks and optimizing quality of service (QoS) in IoT-enabled smart cities. Key achievements include a significant reduction in the time taken to detect and respond to attacks, coupled with a notable improvement in system throughput and QoS metrics.Graphical Abstract Description:The graphical abstract will depict an IoT-enabled smart city with a network of interconnected devices, where secure communication is facilitated by an enhanced ECC model. The ECC encryption process is shown in combination with machine learning models used for cyber-attack detection. The diagram should illustrate the dynamic adjustment of ECC parameters based on network conditions and the continuous monitoring of network traffic by ML algorithms. The visual should also highlight the key benefits of the proposed system, such as attack detection, QoS optimization, and overall IoT security enhancement.