[Paper Review] Load Control and Privacy-Preserving Scheme for Data Collection in AMI Networks

Hawzhin Mohammed, Syed Rafay Hasan+1 more|arXiv (Cornell University)|Jul 30, 2018

Smart Grid Security and Resilience13 references3 citations

TL;DR

This paper proposes a lightweight, privacy-preserving data collection scheme for Advanced Metering Infrastructure (AMI) networks using symmetric key cryptography and hashing to obscure individual smart meter readings. By aggregating covered power consumption data through shared secret covers, the utility gains total consumption insights without accessing individual values, significantly reducing computational overhead and communication costs compared to homomorphic encryption or asymmetric methods.

ABSTRACT

In Advanced Metering Infrastructure (AMI) systems, smart meters (SM) send fine-grained power consumption information to the utility company, yet this power consumption information can uncover sensitive information about the consumers' lifestyle. To allow the utility company to gather the power consumption information while safeguarding the consumers' privacy, different methods that broadly utilize symmetric key and asymmetric key cryptography operation have been generally utilized. In this paper, we propose an effective method that uses symmetric key cryptography and hashing operation to gather power consumption information. Moreover, provide the utility company with an overview of the type of the appliances used by its power consumer and range of power use. The idea is based on sending cover power consumption information from the smart meters and removes these covers by including every one of the smart meters' messages, with the goal that the utility can take in the accumulated power consumption information, yet cannot take in the individual readings. Our assessments show that the cryptographic operations required in our scheme are substantially more effective than the operations required in other schemes.

Motivation & Objective

• To address privacy leakage in AMI networks where fine-grained power consumption data can reveal sensitive consumer behaviors.
• To reduce the computational and communication overhead of existing privacy-preserving schemes that rely heavily on asymmetric cryptography or homomorphic encryption.
• To enable the utility company to learn aggregate power consumption and appliance usage patterns without accessing individual meter readings.
• To design a system that maintains strong security against collusion attacks while minimizing resource usage at smart meters.
• To evaluate the performance trade-off between privacy level and system overhead in a practical AMI network setting.

Proposed method

• Each smart meter encrypts its power consumption using a shared symmetric key and a secret cover value derived via cryptographic hashing.
• The utility aggregates all covered readings, enabling it to compute the total consumption by subtracting the sum of all shared cover values.
• A key management system using asymmetric cryptography is employed only periodically for key updates, minimizing frequent heavy operations.
• The scheme relies on point addition and vector aggregation to combine covered readings, ensuring individual values remain hidden during transmission.
• The method ensures that only the aggregated result is revealed to the utility, preserving individual privacy while enabling load control and demand response.
• The system is evaluated in a tree-topology AMI network using MATLAB to compare performance against homomorphic encryption in terms of time, size, and transmission overhead.

Experimental results

Research questions

• RQ1 How can individual smart meter power consumption data be protected from exposure to the utility company while still enabling aggregate load monitoring?
• RQ2 What is the performance trade-off between increased privacy protection and system resource overhead in AMI networks?
• RQ3 Can symmetric key cryptography and hashing be used effectively to achieve both privacy and efficiency in AMI data collection?
• RQ4 How does the proposed scheme compare in efficiency and security to existing homomorphic encryption-based approaches?
• RQ5 What is the impact of network size on the scalability and performance of the proposed scheme?

Key findings

• The proposed scheme reduces cryptographic overhead significantly compared to homomorphic encryption, with point addition showing nearly constant computation time regardless of the number of smart meters.
• Homomorphic encryption time increases linearly with the number of smart meters, while point addition remains stable, making it more scalable for large networks.
• The scheme achieves strong security against collusion attacks through the use of shared secret covers and symmetric key operations.
• Simulation results show reduced transmission size, lower packet transmission, and less delay compared to existing schemes.
• The system demonstrates a favorable trade-off between privacy level and system overhead, where higher privacy can be achieved by increasing key and cover size without compromising functionality.
• Performance evaluation in a binary and tri-tree topology confirms consistent efficiency across different network structures, with point addition outperforming homomorphic encryption in convergence time.