IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i24p4691-d999787.html
   My bibliography  Save this article

A Malware Attack Enabled an Online Energy Strategy for Dynamic Wireless EVs within Transportation Systems

Author

Listed:
  • Fahad Alsokhiry

    (Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
    K. A. CARE Energy Research and Innovation Center, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Andres Annuk

    (Institute of Forestry and Engineering, Estonian University of Life Sciences, 51006 Tartu, Estonia)

  • Toivo Kabanen

    (Institute of Forestry and Engineering, Estonian University of Life Sciences, 51006 Tartu, Estonia)

  • Mohamed A. Mohamed

    (Electrical Engineering Department, Faculty of Engineering, Minia University, Minia 61519, Egypt)

Abstract

Developing transportation systems (TSs) under the structure of a wireless sensor network (WSN) along with great preponderance can be an Achilles’ heel from the standpoint of cyber-attacks, which is worthy of attention. Hence, a crucial security concern facing WSNs embedded in electrical vehicles (EVs) is malware attacks. With this in mind, this paper addressed a cyber-detection method based on the offense–defense game model to ward off malware attacks on smart EVs developed by a wireless sensor for receiving data in order to control the traffic flow within TSs. This method is inspired by the integrated Nash equilibrium result in the game and can detect the probability of launching malware into the WSN-based EV technology. For effective realization, modeling the malware attacks in conformity with EVs was discussed. This type of attack can inflict untraceable detriments on TSs by moving EVs out of their optimal paths for which the EVs’ power consumption tends toward ascending thanks to the increasing traffic flow density. In view of this, the present paper proposed an effective traffic-flow density-based dynamic model for EVs within transportation systems. Additionally, on account of the uncertain power consumption of EVs, an uncertainty-based UT function was presented to model its effects on the traffic flow. It was inferred from the results that there is a relationship between the power consumption and traffic flow for the existence of malware attacks. Additionally, the results revealed the importance of repressing malware attacks on TSs.

Suggested Citation

  • Fahad Alsokhiry & Andres Annuk & Toivo Kabanen & Mohamed A. Mohamed, 2022. "A Malware Attack Enabled an Online Energy Strategy for Dynamic Wireless EVs within Transportation Systems," Mathematics, MDPI, vol. 10(24), pages 1-20, December.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:24:p:4691-:d:999787
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/24/4691/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/10/24/4691/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mohamed, Mohamed A., 2022. "A relaxed consensus plus innovation based effective negotiation approach for energy cooperation between smart grid and microgrid," Energy, Elsevier, vol. 252(C).
    2. Qiong Zhang & Wenzheng Zhang, 2019. "Accurate detection of selective forwarding attack in wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 15(1), pages 15501477188, January.
    3. Abdulaziz Almalaq & Saleh Albadran & Mohamed A. Mohamed, 2022. "Deep Machine Learning Model-Based Cyber-Attacks Detection in Smart Power Systems," Mathematics, MDPI, vol. 10(15), pages 1, July.
    4. Norouzi, Mohammadali & Aghaei, Jamshid & Pirouzi, Sasan & Niknam, Taher & Fotuhi-Firuzabad, Mahmud & Shafie-khah, Miadreza, 2021. "Hybrid stochastic/robust flexible and reliable scheduling of secure networked microgrids with electric springs and electric vehicles," Applied Energy, Elsevier, vol. 300(C).
    5. Roustaei, M. & Niknam, T. & Salari, S. & Chabok, H. & Sheikh, M. & Kavousi-Fard, A. & Aghaei, J., 2020. "A scenario-based approach for the design of Smart Energy and Water Hub," Energy, Elsevier, vol. 195(C).
    6. Tan, Hong & Yan, Wei & Ren, Zhouyang & Wang, Qiujie & Mohamed, Mohamed A., 2022. "A robust dispatch model for integrated electricity and heat networks considering price-based integrated demand response," Energy, Elsevier, vol. 239(PA).
    7. Tianze Lan & Kittisak Jermsittiparsert & Sara T. Alrashood & Mostafa Rezaei & Loiy Al-Ghussain & Mohamed A. Mohamed, 2021. "An Advanced Machine Learning Based Energy Management of Renewable Microgrids Considering Hybrid Electric Vehicles’ Charging Demand," Energies, MDPI, vol. 14(3), pages 1-25, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Luiz Fernando Ribas Monteiro & Yuri R. Rodrigues & A. C. Zambroni de Souza, 2023. "Cybersecurity in Cyber–Physical Power Systems," Energies, MDPI, vol. 16(12), pages 1-34, June.
    2. Abdulaziz Almalaq & Saleh Albadran & Mohamed A. Mohamed, 2023. "An Adoptive Miner-Misuse Based Online Anomaly Detection Approach in the Power System: An Optimum Reinforcement Learning Method," Mathematics, MDPI, vol. 11(4), pages 1-22, February.
    3. Erdal Irmak & Ersan Kabalci & Yasin Kabalci, 2023. "Digital Transformation of Microgrids: A Review of Design, Operation, Optimization, and Cybersecurity," Energies, MDPI, vol. 16(12), pages 1-58, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tan, Hong & Yan, Wei & Ren, Zhouyang & Wang, Qiujie & Mohamed, Mohamed A., 2022. "Distributionally robust operation for integrated rural energy systems with broiler houses," Energy, Elsevier, vol. 254(PC).
    2. Fahad Alsokhiry & Pierluigi Siano & Andres Annuk & Mohamed A. Mohamed, 2022. "A Novel Time-of-Use Pricing Based Energy Management System for Smart Home Appliances: Cost-Effective Method," Sustainability, MDPI, vol. 14(21), pages 1-20, November.
    3. Abdulaziz Almalaq & Saleh Albadran & Amer Alghadhban & Tao Jin & Mohamed A. Mohamed, 2022. "An Effective Hybrid-Energy Framework for Grid Vulnerability Alleviation under Cyber-Stealthy Intrusions," Mathematics, MDPI, vol. 10(14), pages 1-20, July.
    4. Mohamed A. Mohamed & Seyedali Mirjalili & Udaya Dampage & Saleh H. Salmen & Sami Al Obaid & Andres Annuk, 2021. "A Cost-Efficient-Based Cooperative Allocation of Mining Devices and Renewable Resources Enhancing Blockchain Architecture," Sustainability, MDPI, vol. 13(18), pages 1-24, September.
    5. Khalid Alnowibet & Andres Annuk & Udaya Dampage & Mohamed A. Mohamed, 2021. "Effective Energy Management via False Data Detection Scheme for the Interconnected Smart Energy Hub–Microgrid System under Stochastic Framework," Sustainability, MDPI, vol. 13(21), pages 1-32, October.
    6. Kandpal, Bakul & Pareek, Parikshit & Verma, Ashu, 2022. "A robust day-ahead scheduling strategy for EV charging stations in unbalanced distribution grid," Energy, Elsevier, vol. 249(C).
    7. Norouzi, Mohammadali & Aghaei, Jamshid & Niknam, Taher & Alipour, Mohammadali & Pirouzi, Sasan & Lehtonen, Matti, 2023. "Risk-averse and flexi-intelligent scheduling of microgrids based on hybrid Boltzmann machines and cascade neural network forecasting," Applied Energy, Elsevier, vol. 348(C).
    8. Qingle Pang & Lin Ye & Houlei Gao & Xinian Li & Yang Zheng & Chenbin He, 2021. "Penalty Electricity Price-Based Optimal Control for Distribution Networks," Energies, MDPI, vol. 14(7), pages 1-16, March.
    9. Sun, Mingyi & Zhao, Xia & Tan, Hong & Li, Xinyi, 2022. "Coordinated operation of the integrated electricity-water distribution system and water-cooled 5G base stations," Energy, Elsevier, vol. 238(PC).
    10. Han, Fengwu & Zeng, Jianfeng & Lin, Junjie & Zhao, Yunlong & Gao, Chong, 2023. "A stochastic hierarchical optimization and revenue allocation approach for multi-regional integrated energy systems based on cooperative games," Applied Energy, Elsevier, vol. 350(C).
    11. Li Zeng & Tian Xia & Salah K. Elsayed & Mahrous Ahmed & Mostafa Rezaei & Kittisak Jermsittiparsert & Udaya Dampage & Mohamed A. Mohamed, 2021. "A Novel Machine Learning-Based Framework for Optimal and Secure Operation of Static VAR Compensators in EAFs," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
    12. Chabok, Hossein & Aghaei, Jamshid & Sheikh, Morteza & Roustaei, Mahmoud & Zare, Mohsen & Niknam, Taher & Lehtonen, Matti & Shafi-khah, Miadreza & Catalão, João P.S., 2022. "Transmission-constrained optimal allocation of price-maker wind-storage units in electricity markets," Applied Energy, Elsevier, vol. 310(C).
    13. Mostafavi Sani, Mostafa & Mostafavi Sani, Hossein & Fowler, Michael & Elkamel, Ali & Noorpoor, Alireza & Ghasemi, Amir, 2022. "Optimal energy hub development to supply heating, cooling, electricity and freshwater for a coastal urban area taking into account economic and environmental factors," Energy, Elsevier, vol. 238(PB).
    14. Muhammad Anique Aslam & Syed Abdul Rahman Kashif & Muhammad Majid Gulzar & Mohammed Alqahtani & Muhammad Khalid, 2023. "A Novel Multi Level Dynamic Decomposition Based Coordinated Control of Electric Vehicles in Multimicrogrids," Sustainability, MDPI, vol. 15(16), pages 1-29, August.
    15. Yang, Dongfeng & Xu, Yang & Liu, Xiaojun & Jiang, Chao & Nie, Fanjie & Ran, Zixu, 2022. "Economic-emission dispatch problem in integrated electricity and heat system considering multi-energy demand response and carbon capture Technologies," Energy, Elsevier, vol. 253(C).
    16. Ting Chen & Lei Gan & Sheeraz Iqbal & Marek Jasiński & Mohammed A. El-Meligy & Mohamed Sharaf & Samia G. Ali, 2023. "A Novel Evolving Framework for Energy Management in Combined Heat and Electricity Systems with Demand Response Programs," Sustainability, MDPI, vol. 15(13), pages 1-23, July.
    17. Mohamed, Mohamed A. & Jin, Tao & Su, Wencong, 2020. "An effective stochastic framework for smart coordinated operation of wind park and energy storage unit," Applied Energy, Elsevier, vol. 272(C).
    18. Wu, Min & Xu, Jiazhu & Zeng, Linjun & Li, Chang & Liu, Yuxing & Yi, Yuqin & Wen, Ming & Jiang, Zhuohan, 2022. "Two-stage robust optimization model for park integrated energy system based on dynamic programming," Applied Energy, Elsevier, vol. 308(C).
    19. Jian Chen & Tao Jin & Mohamed A. Mohamed & Andres Annuk & Udaya Dampage, 2022. "Investigating the Impact of Wind Power Integration on Damping Characteristics of Low Frequency Oscillations in Power Systems," Sustainability, MDPI, vol. 14(7), pages 1-23, March.
    20. Huafang Huang & Sharafat Ali & Yasir Ahmed Solangi, 2023. "Analysis of the Impact of Economic Policy Uncertainty on Environmental Sustainability in Developed and Developing Economies," Sustainability, MDPI, vol. 15(7), pages 1-19, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:10:y:2022:i:24:p:4691-:d:999787. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.