protocols.

The rapid growth of Internet of Things (IoT) technology has paved the way for the development of smart cities, where interconnected devices enable efficient urban management and improved quality of life. IoT devices play a pivotal role in automating and transforming city services, from smart traffic systems and intelligent lighting to waste management and air quality monitoring. However, the increased connectivity also introduces vulnerabilities, as data is continuously transmitted across public and private networks. For example, unauthorized access to smart traffic systems could lead to traffic disruptions, while breaches in healthcare systems could compromise patient data privacy [1].

Ensuring the security of data transmission in IoT-based smart city networks is imperative to maintaining the integrity, reliability, and trustworthiness of these systems. This paper addresses the core challenges associated with IoT data security, including encryption, authentication, and secure communication protocols. Our proposed solution integrates a layered security approach to comprehensively address these issues, ensuring robust data protection in smart city ecosystems [2].

devices.

manipulation.

accessing the network.

number of IoT devices.

5 Inconsistent data collection Loss of data or irregular intervals in data collection due to device manipulation.

I. Data privacy and security: ensuring secure and private transmission of sensitive data [3].

II. Scalability and interoperability: achieving seamless integration and scalability across diverse devices [4]. III. Network reliability and connectivity: maintaining stable and consistent device connectivity [5].

IV. Data management and storage: efficiently managing, processing, and storing vast data volumes [6].

V. Energy consumption and device maintenance: optimizing power use and regular device upkeep [7].

methods within IoT environments. Popular encryption techniques include:

I. Advanced Encryption Standard (AES): widely used due to its efficiency and security. AES-256 is considered secure for most IoT applications [6].

II. Rivest-Shamir-Adleman (RSA): used primarily for secure key exchange due to its asymmetric nature. III. Elliptic Curve Cryptography (ECC): provides strong security with smaller key sizes, making it suitable for resource-constrained IoT devices [7].

IV. Transport Layer Security (TLS): ensures data is encrypted in transit, preventing eavesdropping and tampering [8].

Studies have shown that while these protocols provide a basic level of security, they may not be sufficient for the diverse requirements of smart city applications. Therefore, integrating multiple layers of security is essential for robust data protection.

I. Eavesdropping: attackers can intercept unencrypted data as it is transmitted over networks, leading to data breaches [9], [10].

between devices, potentially altering or stealing data.

III. Data tampering: cybercriminals manipulate data during transmission, leading to incorrect information being processed or stored.

IV. Denial of Service (DoS): overloading network resources to make services unavailable.

V. Replay attacks: repeated transmissions of previously captured data can mislead or disrupt services.

VI. Addressing these vulnerabilities requires a multi-faceted approach that covers encryption, authentication, and secure communication protocols [2].

Our proposed solution introduces a layered security architecture to address data transmission vulnerabilities in smart city IoT networks. The methodology involves:

I. Data encryption: implementing AES-256 for high-speed data encryption, ensuring data remains confidential during transmission [11].

II. Authentication: utilizing digital certificates and Public Key Infrastructure (PKI) for robust device authentication.

III. Secure key exchange: using Diffie-Hellman key exchange to establish encrypted communication channels [12].

TLS/SSL to maintain data integrity and secure transmission over constrained devices.

K= g^{ab} mod p,

where:

g is the generator, p is a prime number,

a and b are private keys of the communicating devices.

I. C: Ciphertext — the output of the encryption process.

II. E: Encryption function — converting plaintext to ciphertext using the key.

III. k: Key — the secret key used for encryption.

IV. P: Plaintext — the original data that is to be encrypted.

I. P: plaintext — the output of the decryption process, which should match the original plaintext.

II. D: decryption function — converting ciphertext back to plaintext using the key.

III. k: key — the same secret key used for encryption.

The proposed model is a multi-layered architecture that ensures data security at every stage of communication within the IoT network. Key components include:

I. Encryption layer: AES-256 encrypts data before transmission, preventing unauthorized access to sensitive information.

participating in the network [14].

III. Secure key management: Diffie-Hellman-based key exchange enables the secure generation and distribution of encryption keys, making it difficult for attackers to intercept communications [15].

IV. Protocol layer: MQTT with TLS/SSL ensures efficient, secure communication, reducing the risk of MitM

The proposed secure communication model was tested in a simulated smart city environment that included devices such as smart traffic lights, waste management sensors, and environmental monitors.

I. H: hash function — a function that takes an input (or message) and produces a fixed-size string of bytes (the hash value or digest) that appears random. It is designed to be a one-way function, making it computationally infeasible to reverse-engineer the original message from the hash [18].

II. M: original message — the data that is being sent or stored.

III. M': received message — the data that has been received or retrieved.

The performance comparison demonstrates that the proposed model achieves faster encryption speeds, reduced latency, and decreased security breach rates. These improvements suggest that the layered approach can significantly enhance performance and security.

This paper presented a robust, scalable model for secure data transmission in IoT-based smart city networks. Our approach enhances data confidentiality, integrity, and availability by integrating encryption, authentication, and secure key exchange. Experimental results indicate that the proposed model can effectively handle real-world smart city applications, providing a secure and efficient communication environment.

Future research will focus on scaling this model to accommodate larger networks and on incorporating AI-based threat detection to address emerging security threats proactively.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

All data are included in the text.

The authors declare no conflict of interest.