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<p>With the expansion of smart grids, maintenance and control costs have grown significantly. For this reason, some innovative strategies have been implemented to strengthen the control within the grid. Among these strategies, the implementation of distributed models coupled to intelligent billing systems is of high interest; it aims at achieving optimality in the system while maintaining billing fairness. Despite the advantages offered by smart grid’s paradigm, it still shows weaknesses in terms of theft and users’ fraudulence behavior detections. That is to say, the present paper focusses on three types of attacks, mainly existing in the literature, that malicious users can exploit to minimize their personal bills along with the development of related technique to troubleshot and solve such issues. Simulations and mathematical models are proposed to model these attacks, along with a mitigation strategy that has been developed.</p>

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Modeling and Mitigating Billing Attacks in Scalable Smart Grids with Distributed and Intelligent Systems

  • 期刊论文

  • 发表日期：

    2025年1月17日

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  • Abdelfattah Abassi,
  • Mostapha El Jai,
  • Ahmed Arid,
  • Hussain Benazza

摘要

With the expansion of smart grids, maintenance and control costs have grown significantly. For this reason, some innovative strategies have been implemented to strengthen the control within the grid. Among these strategies, the implementation of distributed models coupled to intelligent billing systems is of high interest; it aims at achieving optimality in the system while maintaining billing fairness. Despite the advantages offered by smart grid’s paradigm, it still shows weaknesses in terms of theft and users’ fraudulence behavior detections. That is to say, the present paper focusses on three types of attacks, mainly existing in the literature, that malicious users can exploit to minimize their personal bills along with the development of related technique to troubleshot and solve such issues. Simulations and mathematical models are proposed to model these attacks, along with a mitigation strategy that has been developed.