Journal of Computer Science

Emerging Trends in Data Science and Cybersecurity for Intelligent IoT and IoV Ecosystems

Description

The rapid evolution and widespread deployment of Internet of Things (IoT) technologies have significantly influenced various sectors, including smart healthcare, energy management, industrial automation, and urban infrastructure. These ecosystems rely heavily on autonomous systems and sensor-driven technologies that support efficient machine-to-machine (M2M) and machine-to-infrastructure (M2I) communications with minimal human involvement. An important offshoot of IoT is the Internet of Vehicles (IoV), where vehicles act as intelligent mobile nodes, interacting dynamically with surrounding infrastructure, other vehicles, and cloud-based systems. This ecosystem is fueled by a vast array of embedded sensors, enabling the continuous generation of diverse data types—such as telemetry, environmental data, and images. To process and derive insights from this data, advanced techniques in data analytics, machine learning, deep learning, and computer vision are increasingly being utilized, supporting a wide range of smart applications, including autonomous driving, remote diagnostics, and predictive system maintenance.

However, the decentralized and heterogeneous architecture of IoT and IoV systems introduces complex challenges in ensuring data security, user privacy, and system integrity. These networks often function over limited-bandwidth or unsecured channels, making them potential targets for malicious attacks. As IoT environments incorporate more image-based and intelligent visual systems, the demand for robust, privacy-aware solutions grows substantially. In response to these concerns, blockchain technology is emerging as a reliable framework for managing decentralized trust, enabling secure data verification, tamper resistance, and transparent transaction records across diverse IoT and IoV applications. This special issue aims to highlight cutting-edge research on emerging data science methodologies and cybersecurity solutions tailored for intelligent sensor networks, connected vehicles, and large-scale IoT infrastructures. We invite contributions that present theoretical developments, practical implementations, and cross-disciplinary innovations that support the secure, intelligent, and sustainable evolution of IoT ecosystems. This special issue seeks high-quality and original contributions that address recent innovations, methodologies, and challenges in IoT and IoV environments.

Topics of interest include, but are not limited to:

1. Advanced Machine Learning and Deep Learning for IoT and IoV Applications
2. Computer Vision and Image Processing in IoT Systems
3. Scalable Data Mining Techniques for IoT-Generated Big Data
4. Explainable AI (XAI) in Trustworthy IoT Intelligence
5. Cybersecurity, Privacy, and Data Provenance in IoT and IoV
6. Blockchain and Distributed Ledger Technologies for Secure IoT
7. Data Management and Automation in Industry 4.0 and Smart Manufacturing
8. Semantic Web Technologies and Interoperability in IoT Platforms
9. Big Data Architectures, Edge, Fog, and Cloud Computing for IoT

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