Privacy-Preserving Collection of Power Consumption Data for Enhanced AMI Networks

In this paper, we propose a privacy-preserving data collection scheme for enhanced AMI networks. The idea is that each cluster of meters is divided into members and heads. A cluster member should send encrypted subreadings with lifetime values to a number of cluster heads where the lifetime permits the cluster heads to reuse the received subreading for future reporting cycles. Then cluster heads should aggregate all the received/stored subreadings and send the result to a local aggregator which performs a further aggregation process and then send an aggregated reading for the cluster to the utility. If the reading of a cluster member does not change, it should run a countermeasure to traffic analysis to determine whether it needs to send a subreading to one of the cluster heads or not, whereas if the power reading changes or the lifetime of a subreading expires, the cluster member needs to update only one subreading to make the summation of all its subreadings gives the correct reading. In addition, the proposed scheme is more resistive to collusion attacks than existing schemes. Our analysis demonstrates that the proposed scheme can preserve consumers privacy and resist collusion attacks. Our measurements confirm that the proposed scheme can reduce the communication bandwidth by 30%.

[1]  Jeannie R. Albrecht,et al.  Smart * : An Open Data Set and Tools for Enabling Research in Sustainable Homes , 2012 .

[2]  Bart Jacobs,et al.  Privacy-Friendly Energy-Metering via Homomorphic Encryption , 2010, STM.

[3]  Steven B. Leeb,et al.  Power signature analysis , 2003 .

[4]  Chun-I Fan,et al.  Privacy-Enhanced Data Aggregation Scheme Against Internal Attackers in Smart Grid , 2014, IEEE Transactions on Industrial Informatics.

[5]  Kemal Akkaya,et al.  Privacy-Preserving Power Injection Over a Hybrid AMI/LTE Smart Grid Network , 2017, IEEE Internet of Things Journal.

[6]  Kemal Akkaya,et al.  Preserving consumer privacy on IEEE 802.11s-based smart grid AMI networks using data obfuscation , 2014, 2014 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[7]  Kemal Akkaya,et al.  Efficient Privacy-Preserving Data Collection Scheme for Smart Grid AMI Networks , 2016, 2016 IEEE Global Communications Conference (GLOBECOM).

[8]  Peng Liu,et al.  Secure and privacy-preserving information aggregation for smart grids , 2011, Int. J. Secur. Networks.

[9]  Loukas Lazos,et al.  Traffic Decorrelation Techniques for Countering a Global Eavesdropper in WSNs , 2017, IEEE Transactions on Mobile Computing.

[10]  Mohamed F. Younis,et al.  Adaptive packet-combining to counter traffic analysis in Wireless Sensor Networks , 2015, 2015 International Wireless Communications and Mobile Computing Conference (IWCMC).

[11]  Zhu Han,et al.  Efficient and Secure Wireless Communications for Advanced Metering Infrastructure in Smart Grids , 2012, IEEE Transactions on Smart Grid.