Anonymity and security improvements in heterogeneous connected vehicle networks

S. Sivasankari1, Deepak Kumar Gupta2, Ismail Keshta3, Ch. Venkata Krishna Reddy4, Poonam Singh5, Haewon Byeon6
1Vignan’s Foundation for Science, Technology and Research (Deemed to be University), Guntur, India
2Department of CSE, Institute of Technology and Management, Gwalior, India
3Computer Science and Information Systems Department, College of Applied Sciences, AlMaarefa University, Riyadh, Saudi Arabia
4Department of Electrical and Electronics Engineering, Chaitanya Bharathi Institute of Technology, Hyderabad, India
5Department of Management, Lovely Professional University, Phagwara, India
6Department of Digital Anti-aging Healthcare, Inje University, Gimhae, 50834, Republic of Korea

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Ahad, A., Tahir, M., Yau, K.-L.A.: 5G-based smart healthcare network: architecture, taxonomy, challenges and future research directions. IEEE Access 7, 100747–100762 (2019). https://doi.org/10.1109/ACCESS.2019.2930628

Alwajeeh, T., Combeau, P., Aveneau, L.: An efficient ray-tracing based model dedicated to wireless sensor network simulators for smart cities environments. IEEE Access 8, 206528–206547 (2020). https://doi.org/10.1109/ACCESS.2020.3037135

Bolla, R., Bruschi, R., Davoli, F., Lombardo, C., Pajo, J.F.: Multi-site resource allocation in a QoS-aware 5G infrastructure. IEEE Trans. Netw. Serv. Manag. 19(3), 2034–2047 (2022). https://doi.org/10.1109/TNSM.2022.3151468

Karabulut Kurt, G., et al.: A vision and framework for the high altitude platform station (HAPS) networks of the future. IEEE Commun. Surv. Tutor. 23(2), 729–779 (2021). https://doi.org/10.1109/COMST.2021.3066905

Hussain, B., Du, Q., Sun, B., Han, Z.: Deep learning-based DDoS-attack detection for cyber-physical system over 5G network. IEEE Trans. Ind. Inf. 17(2), 860–870 (2021). https://doi.org/10.1109/TII.2020.2974520

Liu, J., Zhao, B., Shao, M., Yang, Q., Simon, G.: Provisioning optimization for determining and embedding 5G end-to-end information centric network slice. IEEE Trans. Netw. Serv. Manag. 18(1), 273–285 (2021). https://doi.org/10.1109/TNSM.2020.3045051

Grasso, C., Raftopoulos, R., Schembra, G.: Smart zero-touch management of UAV-based edge network. IEEE Trans. Netw. Serv. Manage. 19(4), 4350–4368 (2022). https://doi.org/10.1109/TNSM.2022.3160858

Minoli, D., Sohraby, K., Occhiogrosso, B.: IoT considerations, requirements, and architectures for smart buildings—energy optimization and next-generation building management systems. IEEE Intern. Things J. 4(1), 269–283 (2017). https://doi.org/10.1109/JIOT.2017.2647881

Razzaq, M.A., Mahar, J.A., Mehmood, A., Choi, G.S., Ashraf, I.: Simulation and assessment of vertical scaling for a smart campus environment using the internet of things. IEEE Access 10, 96322–96330 (2022). https://doi.org/10.1109/ACCESS.2022.3204042

Bruschi, R., Davoli, F., Lago, P., Pajo, J.F.: A multi-clustering approach to scale distributed tenant networks for mobile edge computing. IEEE J. Sel. Areas Commun. 37(3), 499–514 (2019). https://doi.org/10.1109/JSAC.2019.2894236

Fernández-Caramés, T.M., Fraga-Lamas, P.: A review on human-centered iot-connected smart labels for the industry 4.0. IEEE Access 6, 25939–25957 (2018). https://doi.org/10.1109/ACCESS.2018.2833501

Gong, Y., Yao, H., Wang, J., Jiang, L., Yu, F.R.: Multi-agent driven resource allocation and interference management for deep edge networks. IEEE Trans. Veh. Technol. 71(2), 2018–2030 (2022). https://doi.org/10.1109/TVT.2021.3134467

Rawat, D.B., Reddy, S.R.: Software defined networking architecture, security and energy efficiency: a survey. IEEE Commun. Surv. Tutor. 19(1), 325–346 (2017). https://doi.org/10.1109/COMST.2016.2618874

Arfaoui, G., et al.: A security architecture for 5G networks. IEEE Access 6, 22466–22479 (2018). https://doi.org/10.1109/ACCESS.2018.2827419

Wang, F., Zhu, H., Lu, R., Zheng, Y., Li, H.: Achieve efficient and privacy-preserving disease risk assessment over multi-outsourced vertical datasets. IEEE Trans. Depend. Sec. Comput. 19(3), 1492–1504 (2022). https://doi.org/10.1109/TDSC.2020.3026631

Yang, H., Zhao, J., Lam, K.-Y., Xiong, Z., Wu, Q., Xiao, L.: Distributed deep reinforcement learning-based spectrum and power allocation for heterogeneous networks. IEEE Trans. Wirel. Commun. 21(9), 6935–6948 (2022). https://doi.org/10.1109/TWC.2022.3153175

Muñoz, P., Adamuz-Hinojosa, Ñ., Navarro-Ortiz, J., Sallent, O., Pérez-Romero, J.: Radio access network slicing strategies at spectrum planning level in 5G and beyond. IEEE Access 8, 79604–79618 (2020). https://doi.org/10.1109/ACCESS.2020.2990802

Wang, B., Sun, Y., Xu, X.: A scalable and energy-efficient anomaly detection scheme in wireless SDN-based mMTC networks for IoT. IEEE Intern. Things J. 8(3), 1388–1405 (2021). https://doi.org/10.1109/JIOT.2020.3011521

Duo, B., Wu, Q., Yuan, X., Zhang, R.: Anti-jamming 3D trajectory design for UAV-enabled wireless sensor networks under probabilistic LoS channel. IEEE Trans. Veh. Technol. 69(12), 16288–16293 (2020). https://doi.org/10.1109/TVT.2020.3040334

Kumar, S., Sharma, A.: Switched beam array antenna optimized for microwave powering of 3-D distributed nodes in clustered wireless sensor network. IEEE Trans. Antennas Propag. 70(12), 11734–11742 (2022). https://doi.org/10.1109/TAP.2022.3209744

Cui, Q., Zhang, Z., Shi, Y., Ni, W., Zeng, M., Zhou, M.: Dynamic multichannel access based on deep reinforcement learning in distributed wireless networks. IEEE Syst. J. 16(4), 5831–5834 (2022). https://doi.org/10.1109/JSYST.2021.3134820

Chu, H., Wang, P.-J., Zhu, X.-H., Hong, H.: Antenna-in-package design and robust test for the link between wireless ingestible capsule and smart phone. IEEE Access 7, 35231–35241 (2019). https://doi.org/10.1109/ACCESS.2019.2891880

Wang, S., Ouyang, J., Li, D., Liu, C.: An integrated industrial ethernet solution for the implementation of smart factory. IEEE Access 5, 25455–25462 (2017). https://doi.org/10.1109/ACCESS.2017.2770180

Docquier, T., Song, Y., Chevrier, V., Pontnau, L., Ahmed-Nacer, A.: Performance evaluation methodologies for smart grid substation communication networks: a survey. Comput. Commun. 198, 228–246 (2023). https://doi.org/10.1016/j.comcom.2022.11.005

Raza, M.A., Aman, M.M., Abro, A.G., Tunio, M.A., Khatri, K.L., Shahid, M.: Challenges and potentials of implementing a smart grid for Pakistan’s electric network. Energ. Strat. Rev. 43, 100941 (2022). https://doi.org/10.1016/j.esr.2022.100941

Halgamuge, M.N., Bojovschi, A., Fisher, P.M., Le, T.C., Adeloju, S., Murphy, S.: Internet of things and autonomous control for vertical cultivation walls towards smart food growing: a review. Urban For. Urban Green. 61, 127094 (2021). https://doi.org/10.1016/j.ufug.2021.127094

Panda, D.K., Das, S.: Smart grid architecture model for control, optimization and data analytics of future power networks with more renewable energy. J. Clean. Prod. 301, 126877 (2021). https://doi.org/10.1016/j.jclepro.2021.126877

Thakur, V.N., Han, J.I.: Triboelectric nanogenerator for smart traffic monitoring and safety. J. Ind. Eng. Chem. 124, 89–101 (2023). https://doi.org/10.1016/j.jiec.2023.04.028

Cao, Y., Wang, Y., Ding, Y., Guo, Z., Wu, Q., Liang, H.: Blockchain-empowered security and privacy protection technologies for smart grid. Comput. Stand. Interfaces 85, 103708 (2023). https://doi.org/10.1016/j.csi.2022.103708

Kim, J., Lee, J., Kang, J.: Smart cities and disaster risk reduction in South Korea by 2022: the case of Daegu. Heliyon 9(8), e18794 (2023). https://doi.org/10.1016/j.heliyon.2023.e18794

Lyden, A., Brown, C., Kolo, I., Falcone, G., Friedrich, D.: Seasonal thermal energy storage in smart energy systems: district-level applications and modelling approaches. Renew. Sustain. Energy Rev. 167, 112760 (2022). https://doi.org/10.1016/j.rser.2022.112760

Botta, A., de Donato, W., Persico, V., Pescapé, A.: Integration of cloud computing and internet of things: a survey. Fut. Gener. Comput. Syst. 56, 684–700 (2016)

Pillmann, J., Sliwa, B., Schmutzler, J., Ide, C., Wietfeld, C.: Car-to-cloud communication traffic analysis based on the common vehicle information model. In: Proceedings of the IEEE 85th Vehicular Technology Conference, 2017, pp. 1–5

Singh, S., Jeong, Y.-S., Park, J.H.: A survey on cloud computing security: Issues, threats, and solutions. J. Netw. Comput. Appl. 75, 200–222 (2016)

Farivar, F., Haghighi, M.S., Jolfaei, A., Alazab, M.: Artificial intelligence for detection, estimation, and compensation of malicious attacks in nonlinear cyber physical systems and industrial IoT. IEEE Trans. Ind. Inf. 16(4), 2716–2725 (2020)

Mouratidis, H., Diamantopoulou, V.: A security analysis method for industrial Internet of things. IEEE Trans. Ind. Inf. 14(9), 4093–4100 (2018)

Tang, M., Alazab, M., Luo, Y.: Big data for cybersecurity: vulnerability disclosure trends and dependencies. IEEE Trans. Big Data 5(3), 317–329 (2017)

Hussain Magsi, A., Ghulam, A., Memon, S., Javeed, K., Alhussein, M., Rida, I.: A machine learning-based attack detection and prevention system in vehicular named data networking. In: Computers, Materials & Continua, pp 1–21. (Tech Science Press). (2023) https://doi.org/10.32604/cmc.2023.040290

Salman, M.Y., Hasar, H.: Review on environmental aspects in smart city concept: water, waste, air pollution and transportation smart applications using IoT techniques. Sustain. Cities Soc. 94, 104567 (2023). https://doi.org/10.1016/j.scs.2023.104567

Hui, H., Ding, Y., Shi, Q., Li, F., Song, Y., Yan, J.: 5G network-based Internet of Things for demand response in smart grid: a survey on application potential. Appl. Energy 257, 113972 (2020). https://doi.org/10.1016/j.apenergy.2019.113972

Huseien, G.F., Shah, K.W.: A review on 5G technology for smart energy management and smart buildings in Singapore. Energy and AI 7, 100116 (2022). https://doi.org/10.1016/j.egyai.2021.100116

Zhang, Y., Wang, W., Wu, X., Lei, Y., Cao, J., Bowen, C., Bader, S., Yang, B.: A comprehensive review on self-powered smart bearings. Renew. Sustain. Energy Rev. 183, 113446 (2023). https://doi.org/10.1016/j.rser.2023.113446

Biazi, V., Marques, C.: Industry 4.0-based smart systems in aquaculture: a comprehensive review. Aquac. Eng. 103, 102360 (2023). https://doi.org/10.1016/j.aquaeng.2023.102360

Pliatsios, A., Kotis, K., Goumopoulos, C.: A systematic review on semantic interoperability in the IoE-enabled smart cities. Intern. Things 22, 100754 (2023). https://doi.org/10.1016/j.iot.2023.100754

Ravindran, M.A., Nallathambi, K., Vishnuram, P., Rathore, R.S., Bajaj, M., Rida, I., Alkhayyat, A.: A novel technological review on fast charging infrastructure for electrical vehicles: challenges, solutions, and future research directions. Alex. Eng. J. 82, 260–290 (2023). https://doi.org/10.1016/j.aej.2023.10.009

Zheng, W., Mehbodniya, A., Neware, R., Wawale, S.G., Ganthia, B.P., Shabaz, M.: Modular unmanned aerial vehicle platform design: multi-objective evolutionary system method. Comput. Electr. Eng. 99, 107838 (2022). https://doi.org/10.1016/j.compeleceng.2022.107838

Yapa, C., De Alwis, C., Liyanage, M., Ekanayake, J.: Survey on blockchain for future smart grids: technical aspects, applications, integration challenges and future research. Energy Rep. 7, 6530–6564 (2021). https://doi.org/10.1016/j.egyr.2021.09.112

Nain, G., Pattanaik, K., Sharma, G.: Towards edge computing in intelligent manufacturing: past, present and future. J. Manuf. Syst. 62, 588–611 (2022). https://doi.org/10.1016/j.jmsy.2022.01.010

Kumar, A., Ahuja, N.J., Thapliyal, M., Dutt, S., Kumar, T., De Jesus Pacheco, D.A., Konstantinou, C., Raymond Choo, K.: Blockchain for unmanned underwater drones: research issues, challenges, trends and future directions. J. Netw. Comput. Appl. 215, 103649 (2023). https://doi.org/10.1016/j.jnca.2023.103649

Ajaz, F., Naseem, M., Sharma, S., Dhiman, G., Shabaz, M., Vimal, S.: Architecture and routing protocols for internet of vehicles: a review. Int. J. Ad Hoc Ubiquitous Comput. 40(1/2/3), 159 (2022). https://doi.org/10.1504/ijahuc.2022.123537

Lamnabhi-Lagarrigue, F., Annaswamy, A., Engell, S., Isaksson, A., Khargonekar, P., Murray, R.M., Nijmeijer, H., Samad, T., Tilbury, D., Van den Hof, P.: Systems & control for the future of humanity, research agenda: Current and future roles, impact and grand challenges. Annu. Rev. Control. 43, 1–64 (2017). https://doi.org/10.1016/j.arcontrol.2017.04.001