The Effect of SMiShing Attack on Security of Demand Response Programs

Elif Ustundag Soykan,Mustafa Bagriyanik

doi:10.3390/en13174542

Abstract

Demand response (DR) is a vital element for a reliable and sustainable power grid. Consumer behavior is a key factor in the success of DR programs. In this study, we focus on how consumer reaction to Short Messaging Service (SMS) messages can disturb the demand response. We present a new type of threat to DR programs using SMS phishing attacks. We follow a holistic approach starting from a risk assessment focusing on DR programs’ notification message security following the Smart Grid Information Security (SGIS) risk methodology. We identify threats, conduct impact analysis, and estimate the likelihood of the attacks for various attacker types and motivations. We implemented deterministic and randomized attack scenarios to demonstrate the success of the attack using a state-of-the-art simulator on the IEEE European Low Voltage Feeder Test System. Simulations show that the attack results in local outages, which may lead to large-scale blackouts with the cascading effect on the power system. We conclude that this is a new type of threat that has been overlooked, and it deserves more attention as mobile devices will continually be part of our lives.

Highlights

Demand Response (DR) is a way to manage consumer demand that allows balance to persist on the grid
We provide possible countermeasures for the identified risk, for both the utility and customer perspective: we provide some solutions on how the utilities should handle the attack, how they should interact with the customer to prevent Disturbing DR via SMiShing (DDRS) attacks, what kind of preventive actions they can take on the power grid to mitigate the DDRS attacks, and what the customer should do to protect themselves from SMiShing attacks
We demonstrated the effect of phishing attacks on the power grid, targeting the customer via fake Short Messaging Service (SMS) messages

Summary

Introduction

Demand Response (DR) is a way to manage consumer demand that allows balance to persist on the grid. Price-based methods [1] aim to balance the consumption of the peak periods by adopting hourly-basis prices to reflect the real-time cost to the consumers while incentive-based programs guide consumers to reduce their consumption by offering special rewards to manage excessive demand. Price-based methods comprise real-time pricing, time of use and critical peak pricing programs and aim to balance the consumption of the peak periods by adopting hourly basis prices to reflect the real-time cost to the consumers. Incentive-based programs direct consumers to reduce their consumption by offering special rewards to manage excessive demand. One of these programs, which is called behavioral demand–response, aims to reduce consumption by encouraging customers to use less energy during peak-demand events

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Discussion

Conclusion