Investigating the Impacts of Cyber-Attacks on Pricing Data of Home Energy Management Systems in Demand Response Programs
Provision of security involves protecting lives and properties, and properties in this context include data and services. This paper investigates the impact of cyber-attacks on load scheduling applications by simulating various possible modes for these attacks while observing possible effects on the users. The attack modes used are in the form of denial of service (DoS) and phishing attacks whereby the attacker is able to interfere with data intake to the Home Energy Management Systems (HEMS) or a modification of critical data to the HEMS. The dynamic pricing information and load profile data is the target here although other types of data utilized by the central controller for load scheduling purposes can also be targeted. The test-bed uses load scheduling applications based on genetic algorithm optimization. Results show the impact on optimized load profiles and how they can discourage active demand response participation if such attacks are not properly managed.