Abstract
In recent years, the transitioning of conventional power grid system into the smart grid infrastructure has made the power distribution network more susceptible towards faults and physical attacks. In this context, we discuss recently proposed Manipulation-of-Demand via IoT attack, False Data Injection Attacks and Electric Fault Attacks. These attacks directly or indirectly can lead to localized blackout, falsified load forecasting, imbalance in demand-response system, generator tripping, frequency instability and loss of equipment etc. To detect and trace back to the source of such attacks, in this paper we inspect the potential of the promising permissioned blockchain technology which is designed for digital transaction, but has been extended to authenticate and assure integrity of real power consumption information in a seem-less manner. This information can be picked up from the smart meters, however the trusted gathering and recording of the information is imperative for end-to-end security. In this work, we bind the smart meter readings to the underlying hardware by enabling the properties of Physically Unclonable Functions (PUFs) which works as a hardware fingerprint of the device. The proposed PUF based power profile verification scheme would further prevent the system from the injection of any false data by an illegitimate smart meter. The novelty of the proposed work is to blend these two technologies in developing a robust and privacy-aware framework which detects and prevents the above mentioned security vulnerabilities and can be easily integrated with the smart grid infrastructure. Finally an end-to-end demonstration of the attack has been presented using MATLAB and Power World simulator whereas the proposed framework has been prototyped using commercial off-the-shelf products such as Raspberry Pi and Artix 7 FPGA along with an in-house blockchain simulator and a privacy-preserving detection scheme.
We would like to thank Swarnajayanti fellowship funded by DST, India, Information Security Education Awareness Project funded by DIT India, and Cyber Security Research in CPS funded by TCG Foundation, India for partially funding our research.
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Ghosh, S., Chatterjee, U., Chatterjee, D., Masburah, R., Mukhopadhyay, D., Dey, S. (2021). Demand Manipulation Attack Resilient Privacy Aware Smart Grid Using PUFs and Blockchain. In: Zhou, J., et al. Applied Cryptography and Network Security Workshops. ACNS 2021. Lecture Notes in Computer Science(), vol 12809. Springer, Cham. https://doi.org/10.1007/978-3-030-81645-2_15
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