Secure VANETs: Trusted Communication Scheme Between Vehicles and Infrastructure Based on Fog Computing

In the Vehicular Ad-hoc Networks (VANETs), a vehicle or the vehicle driver could be recognized and tracked by eavesdropping its queries (e.g., beacons) by an adversary as these contains personal information like location, speed, and communication of the vehicles. This attack leads to threats to the vehicle`s location and leakage of personal information. The current solution, is to use the anonymizer as a third trusted party between the vehicles and the LBS. In this paper we refer to the use of a Fog server with Fog anonymizer to secure the communication among the vehicles and LBS. Our scheme consists of four phases. In first phase, the vehicle driver initiates the communication process and generate the encrypted messages. These messages may contain the sub-messages. In phase 2, the Fog server received the messages via different roots. The Fs combined the messages and decrypt the messages based on the PK received by the vehicle. All the Fog server perform the same task for encryption and decryption. If any of the Fog server was compromised, we still had the link for communication. In Phase 3, the Fog anonymizer receive the messages from the Fog node, anonymize them based on the anonymization process. Thereafter, the Fog anonymizer send these messages to LBS to achieve desired goals. The Fog anonymizer perform the same job for anonymization and de-anonymization, while sending and receiving the messages from the LBS. In the last phase, the LBS received the messages from the Fog anonymizer, understand the communication messages, compile the desired results, and sent them back to the Fog anonymizer. Our analysis shows that the proposed scheme preserved the location privacy based on the queries at low communication and computational cost.

[1]  Zhili Sun,et al.  Security and Privacy in Location-Based Services for Vehicular and Mobile Communications: An Overview, Challenges, and Countermeasures , 2018, IEEE Internet of Things Journal.

[2]  Seungju Yoon,et al.  Real-world exhaust temperature profiles of on-road heavy-duty diesel vehicles equipped with selective catalytic reduction. , 2018, The Science of the total environment.

[3]  Daniel Egiegba Agbiboa,et al.  Conflict Analysis in ‘World Class’ Cities: Urban Renewal, Informal Transport Workers, and Legal Disputes in Lagos , 2018 .

[4]  Jemal H. Abawajy,et al.  A trajectory privacy-preserving scheme based on query exchange in mobile social networks , 2018, Soft Comput..

[5]  Keshav P. Dahal,et al.  Personalized location prediction for group travellers from spatial-temporal trajectories , 2018, Future Gener. Comput. Syst..

[6]  Dongqing Xie,et al.  Multi‐dimensional fuzzy trust evaluation for mobile social networks based on dynamic community structures , 2017, Concurr. Comput. Pract. Exp..

[7]  Jie Cui,et al.  Efficient conditional privacy-preserving and authentication scheme for secure service provision in VANET , 2016 .

[8]  Weijia Jia,et al.  Heterogeneous vehicular communications: A comprehensive study , 2018, Ad Hoc Networks.

[9]  Yaghoub Farjami,et al.  NECPPA: A novel and efficient conditional privacy-preserving authentication scheme for VANET , 2018, Comput. Networks.

[10]  Josep Domingo-Ferrer,et al.  Balanced Trustworthiness, Safety, and Privacy in Vehicle-to-Vehicle Communications , 2010, IEEE Transactions on Vehicular Technology.

[11]  Tsz Hon Yuen,et al.  Improvements on an authentication scheme for vehicular sensor networks , 2014, Expert Syst. Appl..

[12]  Bob Gill,et al.  Security, SDN, and VANET technology of driver-less cars , 2018, 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC).

[13]  Albert Y. Zomaya,et al.  A New Spectrum Management Scheme for Road Safety in Smart Cities , 2018, IEEE Transactions on Intelligent Transportation Systems.

[14]  Walid G. Aref,et al.  Casper*: Query processing for location services without compromising privacy , 2006, TODS.

[15]  Josep Domingo-Ferrer,et al.  A Scalable Robust Authentication Protocol for Secure Vehicular Communications , 2010, IEEE Transactions on Vehicular Technology.

[16]  Alistair Sutcliffe,et al.  Simulation-based evaluation of an in-vehicle smart situation awareness enhancement system , 2018, Ergonomics.

[17]  Pingzhi Fan,et al.  b-SPECS+: Batch Verification for Secure Pseudonymous Authentication in VANET , 2013, IEEE Transactions on Information Forensics and Security.

[18]  Siu-Ming Yiu,et al.  SPECS: Secure and privacy enhancing communications schemes for VANETs , 2011, Ad Hoc Networks.

[19]  Qun Li,et al.  A Survey of Fog Computing: Concepts, Applications and Issues , 2015, Mobidata@MobiHoc.

[20]  Radu Velea,et al.  Network Traffic Anomaly Detection Using Shallow Packet Inspection and Parallel K-means Data Clustering , 2017 .

[21]  Jianhong Zhang,et al.  On the Security of a Secure Batch Verification with Group Testing for VANET , 2014, Int. J. Netw. Secur..

[22]  Juan-Carlos Cano,et al.  An Intelligent Transportation System Application for Smartphones Based on Vehicle Position Advertising and Route Sharing in Vehicular Ad-Hoc Networks , 2018, Journal of Computer Science and Technology.

[23]  Byung-Seo Kim,et al.  Services and Security Threats in SDN Based VANETs: A Survey , 2018, Wirel. Commun. Mob. Comput..

[24]  Baowen Xu,et al.  An Efficient Identity-Based Conditional Privacy-Preserving Authentication Scheme for Vehicular Ad Hoc Networks , 2015, IEEE Transactions on Information Forensics and Security.

[25]  Nirvana Popescu,et al.  An Experimental Evaluation of Application Layer Protocols for the Internet of Things , 2017 .

[26]  Cheng-Chi Lee,et al.  Toward a secure batch verification with group testing for VANET , 2013, Wirel. Networks.

[27]  Hicham Lakhlef,et al.  Internet of things security: A top-down survey , 2018, Comput. Networks.

[28]  Wolfgang Rid,et al.  Assessing driving pattern factors for the specific energy use of electric vehicles: A factor analysis approach from case study data of the Mitsubishi i–MiEV minicar , 2018 .

[29]  Muhammad Arshad,et al.  A survey of local/cooperative-based malicious information detection techniques in VANETs , 2018, EURASIP J. Wirel. Commun. Netw..

[30]  Muhammad Alam,et al.  Implementation and Analysis of IEEE and ETSI Security Standards for Vehicular Communications , 2018, Mob. Networks Appl..

[31]  Yacine Ghamri-Doudane,et al.  Software defined networking-based vehicular Adhoc Network with Fog Computing , 2015, 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM).

[32]  Chen Chen,et al.  Driver’s Intention Identification and Risk Evaluation at Intersections in the Internet of Vehicles , 2018, IEEE Internet of Things Journal.

[33]  Qi Zhang,et al.  Improved Dual-Protected Ring Signature for Security and Privacy of Vehicular Communications in Vehicular Ad-Hoc Networks , 2018, IEEE Access.