SE-VFC: A Secure Framework for Computation Outsourcing in Vehicular Fog Computing Environments

Abstract

SE-VFC is a proposed computing scheme that addresses the challenge of providing secure and efficient outsourcing computing in vehicular fog computing. Vehicular fog computing is a paradigm that involves the utilization of computing resources in vehicles to provide various computing services to end- users. However, since fog vehicles may be untrusted, there is a potential for malicious operations that can cause serious accidents. To address this challenge, SE-VFC proposes the use of a secure and efficient outsourcing computing scheme that involves fog vehicles with computing resources. The scheme utilizes lightweight Boneh-Lynn-Shacham (BLS) signature and group signature for batch anonymous authentication of fog vehicles while preserving their privacy in multiple outsourcing tasks. This means that fog vehicles are authenticated and verified without revealing their identities, which helps to protect their privacy. Additionally, SE-VFC ensures the correctness of the computing results by verifying them. This helps to ensure that the results produced are accurate and reliable. Compared to existing schemes, SE-VFC has relatively low communication and computation overhead, making it efficient for batch authentication in multiple computing tasks. The effectiveness and practicality of the proposed scheme have been verified through extensive simulation results. Overall, SE-VFC is an important contribution to the field of vehicular fog computing, as it addresses the challenge of providing secure and efficient outsourcing computing while also ensuring the privacy and correctness of the computing results.

Introduction

I. INTRODUCTION

Vehicular Ad-hoc Networks (VANETs) have evolved from providing simple internet services to advanced applications like video streaming, augmented and virtual reality. However, ensuring the secure and reliable delivery of data in VANETs poses challenges due to privacy and security concerns. Attribute- based encryption (ABE) has been proposed to provide secure information dissemination in highly dynamic vehicular communication environments. Nonetheless, the decryption time of ABE increases with the number of attributes, limiting its practical application in VANETs. As an alternative, vehicular fog computing has been proposed to enhance the performance of latency-critical applications. This paradigm employs end-users like vehicles and mobile devices as infrastructures, utilizing their communication and computational resources. However, fog vehicles may forge identities, leading to malicious activities. To address these issues, we propose a secure and efficient outsourcing computing scheme in vehicular fog computing (SE- VFC), which allows the source vehicle to outsource complex ciphertext policy ABE decryption operation to fog vehicles while ensuring secure and efficient real-time information services.

The proposed scheme employs a lightweight Boneh-Lynn- Shacham (BLS) signature and group signature algorithm to achieve batch anonymous authentication of fog vehicles while ensuring their privacy in multiple outsourcing tasks. The scheme also employs verifiable outsourcing CP-ABE algorithm to prevent malicious fog vehicles from performing incorrect outsourcing computing.

The passage discusses the challenges of security and privacy in vehicular ad-hoc networks (VANETs) and proposes a solution called Secure and Efficient Outsourcing Computing Scheme in Vehicular Fog Computing (SE-VFC). VANETs are becoming increasingly complex, with applications ranging from simple email services to video streaming and augmented/virtual reality.

However, ensuring the secure and reliable delivery of data is challenging due to the highly dynamic vehicular communication environment. Attribute-based encryption (ABE) has been proposed to provide secure information dissemination, but its decryption time increases as the number of attributes increases, limiting its practical application. Therefore, SE-VFC proposes to delegate part of the complex decryption to fog vehicles, which are vehicles that voluntarily join and leave the vehicular fog computing network. The proposed scheme uses a lightweight Boneh-Lynn-Shacham (BLS) signature and group signature algorithm to achieve batch anonymous authentication of fog vehicles while protecting their privacy. The fog vehicles' integrity is verified using verifiable outsourcing CP-ABE algorithm to prevent malicious fog vehicles from stealing or tampering with information. The proposed solution aims to ensure the secure and efficient delivery of real-time information services in VANETs.

This paper presents the proposed scheme's contributions, which include secure and efficient outsourcing computing in vehicular fog computing, an efficient batch anonymous authentication scheme for fog vehicles, and the employment of verifiable outsourcing CP-ABE algorithm to ensure the correctness of outsourcing computing results. The paper is structured as follows: Section II presents literature survey on vehicular fog computing and attribute-based encryption in VANETs. Section III outlines the consolidated table. Section IV evaluates the acknowledgement, and Section V concludes the conclusion and future scope.

II. LITERATURE SURVEY

In this section, we review the vehicular fog computing and attribute-based encryption in VANETs, and analyze the security problems.

A. Vehicular Fog Computing in VANETs

Different from vehicular cloud computing, vehicular fog computing supports the mobility and location awareness of nearby vehicles and uses the idle computing and storage resources of vehicles located inside VANETs to generate fog instantly [8, 13]. In vehicular fog computing, many researchers paid attention to task allocation [14–16], fog node selection [17] and secure data sharing [13, 18]. Task allocation approaches mainly focused on optimized task allocation for minimizing average service latency [15], dynamic task allocation solutions using reinforcement learning [14], reliable task offloading under information uncertainty [16] and an application-aware offloading policy by the semi markov decision process [19]. They adopted different methods to make task allocation efficient and reliable. Security issues such as malicious fog vehicles are important issues that greatly affect the reliable of task allocation in vehicular fog computing. So we focus on authenticating the fog vehicles and verifying the correctness of the results in fog task computation. To attract the fog-capable vehicles to participate in the vehicular fog computing network, Wang et al. [20] designed a contract-based resource allocation framework to attract nearby vehicles to participate through an effective incentive mech anism. Hao et al. [17] proposed a vehicular fog computing architecture to implement cooperative sensing among multiple adjacent vehicles driving in the form of a platoon. However, fog vehicles sometimes may be untrusted, and results from the malicious operations will cause serious accidents. We identify the security research challenges that need to be addressed to select fog node and improve tasks’ offloading performance.

B. Security Issues in Vehicular Fog Computing

Researchers proposed that fog server was aided and assisted in the secure cloud-based data sharing. Xue et al. [13] pro posed a fog-to-cloud-based architecture for data sharing, in which data cloud be offloaded to the fog vehicles in advance based on a user’s mobility prediction. And the encryption task and decryption task were outsourced to semi-trusted fog servers and the cloud server, respectively. The scheme could provide verifiable auditing of fog servers’ reports with the assumption that there was no collusion between different providers for the cloud and fog servers. Yao et al.[18] explored a mechanism for provisioning client-vehicles with reliable and secure vehicular fog service provided by a group of server vehicles. They applied the existing public key algorithms in vehicular fog contruction and vehicular fog service access to achieve reliability and security, but did not address the security issues such as verification in vehicular fog service. Due to the openness and dynamic nature of vehicular fog computing, when malicious fog vehicles join the network, they might send false reports [21], steal users privacy [13] or even perform incorrect computing. Therefore, under the influence of malicious mobile vehicles, fog computing is greatly threatened by security attacks. Zheng et al. [22] studied the security of offloading in multi-vehicle edge cloud system based on cloud blockchain, which used blockchain-based access control to protect the cloud from illegal offloading actions. Liao et al.

[23] developed a secure and intelligent task offloading framework, which exploited blockchain and smart contract to facilitate fair task offloading and mitigate various security attacks. The scheme considered the malicious behavior of fog nodes and used signature based on asymmetric cryptosystem and smart contracts to authenticate fog nodes. Wei et al. [24] designed a secure and efficient outsourcing algorithm, which used identity-based signature to achieve unforgeability. How ever, the above schemes ignored the situation that malicious fog vehicles may perform incorrect outsourcing computing, which would cause the failure of the entire task offloading in vehicular fog computing.

C. Attribute-based Encryption in VANETs

Ciphertext policy attribute-based encryption (CP-ABE) was first proposed by Waters et al. [25] and considered to be a promising encryption mechanism for access control of en crypted data. CP-ABE schemes have been extensively studied in VANETs. Safi et al. [4] proposed a cloud-based security and privacy-aware information dissemination scheme to achieve fine-grained information sharing between vehicle nodes and cloud systems. Pan et al. [26] proposed a scheme for sharing data between different domains, which used ABE and ellip tic curve cryptography to ensure information confidentiality. Many researchers have proposed lots of variants of ABE scheme in different environments [27, 28], including non monotonic access structure, attribute revocation and so on. In summary, the CP-ABE algorithms have been widely used in VANET’s applications such as information sharing and information storage, but the computation costs in the decryption increase with the number of attributes in the access formula, which required many parings in most of existing traditional CP-ABE schemes. Green et al. [29] introduced the outsourcing decryption of the ABE ciphertext. Zhou et al proposed to outsource some encryption and decryption computing to the cloud. The method based on outsourcing computing could effectively solve the problem of efficiency, but it introduces security problems that need to be solved urgently. Zuo et al. [31] proposed a concrete chosen-ciphertext security (CCA) ABE scheme with outsourcing decryption. A CP-ABE system with outsourcing computing should ensure that an adversary (including a malicious cloud or fog) would not be able to learn anything about the encrypted message and guarantee the correctness of the computation done by them [32, 33].

III. CONSOLIDATED TABLE

IV. ACKNOWLEDGEMENT

Any achievement does not depend solely on the individual efforts but on the guidance, encouragement and co-operation of intellectuals, elders and friends. We extend our sincere thanks to Dr. Kamalakshi Naganna, Professor and Head, Department of Computer Science and Engineering, Sapthagiri College of Engineering, and Dr Praveen Kumar K V Professor, Department of Computer Science and Engineering, Sapthagiri College of Engineering, for constant support, advice and regular assistance throughout the work. Finally, we thank our parents and friends for their moral support.

Conclusion

The paper proposes a secure and efficient framework for outsourcing computation tasks in vehicular fog computing (VFC) environments. The proposed framework uses secure multi-party computation (MPC) and homomorphic encryption to enable multiple vehicles to jointly perform computations on their data without revealing any sensitive information to each other or to the fog server. The framework also ensures data integrity and confidentiality by using digital signatures and secure communication protocols. The authors evaluate the proposed framework using simulation experiments and demonstrate its effectiveness and efficiency. Although the proposed framework is effective and efficient in addressing the secure outsourcing of computation tasks in vehicular fog computing environments, there is still room for improvement. Some future research directions are: 1) Scalability: The proposed framework needs to be evaluated for scalability to handle a larger number of vehicles and computation tasks. 2) Robustness: The proposed framework needs to be evaluated for robustness against various types of attacks, including attacks on communication channels and computation tasks. 3) Real-World Experiments: The proposed framework needs to be evaluated in real-world VFC environments to validate its performance and effectiveness. 4) Privacy: The proposed framework should be evaluated for its privacy guarantees, particularly in terms of the data privacy of individual vehicles. 5) Comparison: The proposed framework should be compared with other existing frameworks to evaluate its competitiveness and advantages.

References

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Copyright

Copyright © 2023 Bhavya Vaishnavi, Dr. Praveen Kumar K V . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.