In an article published in the journal Scientific Reports, researchers from Islamic Azad University, Iran, introduced an innovative approach called network security offloading in vehicle-to-fog-to-cloud (NSO-VFC) to address the challenge of securing data offloading within the context of the Internet of Vehicles (IoV) within a fog-cloud federation. They recognized the necessity for secure and efficient data handling in IoV environments, where vehicles generate and exchange large volumes of data.
Study: NSO-VFC in Internet of Vehicles: Securing the Road Ahead. Image credit: metamorworks/Shutterstock
Background
The Internet of Things (IoT) is a network where everyday objects are connected to the internet. This connectivity allows these objects to send and receive data, transforming them into "smart" devices capable of communicating with each other and with people. Similarly, IOV is a network of vehicles equipped with various sensors, global positioning system (GPS), and communication devices. These vehicles can exchange data not only with each other but also with cloud-based services, facilitating the development of intelligent transportation systems.
Vehicles in IoV can communicate with one another to share real-time information about road conditions, traffic patterns, and potential hazards. This exchange of data enhances road safety, optimizes traffic flow, and improves overall efficiency in transportation networks. Additionally, IoV technology enables vehicles to interact with infrastructure such as traffic lights and road signs, further enhancing the coordination and management of traffic. However, challenges remain in ensuring the security and efficiency of data offloading within IoV systems. Addressing these challenges is crucial to unlocking the full potential of IoV and realizing its benefits for transportation systems worldwide.
About the Research
In the present paper, the authors introduced a fog computing-based approach NSO-VFC. Its main objectives were to enhance the security of data offloading, improve the performance of communication and computation, and reduce costs. Fog computing is an extension of cloud computing which plays a crucial role in IoV by distributing computational tasks closer to the data source. This approach leveraged fog nodes, which were deployed at the edge of the network, to facilitate real-time data processing and reduce latency.
The proposed NSO-VFC technology incorporated several key features to achieve its objectives:
- Nonce-Based Authentication: Random numbers called nonces were utilized to establish secure communication channels between vehicles and fog nodes. Nonces prevented replay attacks and guaranteed mutual authentication, ensuring that only authorized entities could access the network.
- Session Key Generation: The scheme dynamically generated session keys for secure data transmission. These keys were unique for each communication session, protecting against eavesdropping and unauthorized access. Utilizing secure key generation algorithms, NSO-VFC allowed secure and encrypted communication channels.
- Formal Analysis: The researchers subjected NSO-VFC to both informal and formal analysis. Formal verification tools, such as automated validation of internet security protocols and applications (AVISPA), were used to confirm its resilience against active and passive attacks. This analysis ensured that the proposed technology met the required security standards.
Research Findings
The researchers assessed the performance of the newly developed NSO-VFC approach in terms of security, communication overhead, and computational costs, revealing the following outcomes:
- Security resilience: NSO-VFC effectively prevented unauthorized access, ensuring data confidentiality and integrity during offloading. Its robustness against attacks positioned it as a reliable security solution for IoV.
- Computational overhead: While enhancing security, NSO-VFC imposed additional computational overhead, requiring vehicles to perform cryptographic operations during session key generation, thus impacting processing time.
- Communication costs: NSO-VFC introduced minimal communication overhead through nonce exchange and session key negotiation. However, this trade-off remained acceptable and given security benefits.
- Packet delivery and throughput: Simulation experiments demonstrated that with increasing IoV density, packet delivery rates and throughput improved. NSO-VFC facilitated efficient data exchange even in congested scenarios.
Application
The newly designed NSO-VFC scheme has the following potential applications for IoV:
- Secure vehicular communication: NSO-VFC ensures confidential and authenticated communication between vehicles and fog nodes. It can enhance safety-critical applications such as collision avoidance and emergency alerts.
- Traffic management: By securely offloading data to fog nodes, IoV can optimize traffic flow, predict congestion, and reduce travel time. NSO-VFC contributes to efficient traffic management.
- Environmental monitoring: IoV sensors collect environmental data such as air quality and temperature. NSO-VFC protects this information, enabling informed decisions for sustainable urban planning.
Conclusion
In summary, the novel approach proved effective and efficient, promising significant enhancements in security within vehicular fog computing. Its successful deployment holds the potential for safer roads, streamlined traffic management, and heightened environmental awareness.
While acknowledging the limitations and challenges of the proposed NSO-VFC approach, the researchers suggested directions for future work. They proposed the development of secure offloading mechanisms leveraging blockchain networks and Metaverse, presenting novel opportunities for enhancing security in IoV systems. This alternative approach could address the shortcomings of NSO-VFC and provide a more robust and efficient solution for data offloading in IoV systems.
Additionally, the study recommended further investigation to enhance the performance of offloading schemes while maintaining strict security standards. This involved exploring new communication and computation methods as well as optimizing existing algorithms and techniques.
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