More Web Proxy on the site http://driver.im/

research-article

Secure Data Provenance in Home Energy Monitoring Networks

Authors:

Ming Hong Chia,

Sye Loong Keoh,

Zhaohui TangAuthors Info & Claims

ICSS 2017: Proceedings of the 3rd Annual Industrial Control System Security Workshop

Pages 7 - 14

https://doi.org/10.1145/3174776.3174778

Published: 05 December 2017 Publication History

Abstract

Smart grid empowers home owners to efficiently manage their smart home appliances within a Home Area Network (HAN), by real time monitoring and fine-grained control. However, it offers the possibility for a malicious user to intrude into the HAN and deceive the smart metering system with fraudulent energy usage report. While most of the existing works have focused on how to prevent data tampering in HAN's communication channel, this paper looks into a relatively less studied security aspect namely data provenance. We propose a novel solution based on Shamir's secret sharing and threshold cryptography to guarantee that the reported energy usage is collected from the specific appliance as claimed at a particular location, and that it reflects the real consumption of the energy. A byproduct of the proposed security solution is a guarantee of data integrity. A prototype implementation is presented to demonstrate the feasibility and practicality of the proposed solution.

References

[1]

Fadi Aloul, AR Al-Ali, Rami Al-Dalky, Mamoun Al-Mardini, and Wassim El-Hajj. 2012. Smart grid security: Threats, vulnerabilities and solutions. International Journal of Smart Grid and Clean Energy 1, 1 (2012), 1--6.

[2]

Muhammad Naveed Aman, Kee Chaing Chua, and Biplab Sikdar. 2017. Secure Data Provenance for the Internet of Things. In Proceedings of the 3rd ACM International Workshop on IoT Privacy, Trust, and Security. ACM, 11--14.

Digital Library

[3]

Yi Han Ang, Sye Loong Keoh, and Zhaohui Tang. 2016. Privacy-Preserving Spatial and Temporal Aggregation of Smart Energy Data. Journal of Information Assurance & Security 11, 4 (2016).

[4]

George Robert Blakley. 1979. Safeguarding cryptographic keys. Proc. of the National Computer Conference 1979 48 (1979), 313--317.

[5]

Xavier Boyen and Brent Waters. 2007. Full-domain subgroup hiding and constant-size group signatures. In International Workshop on Public Key Cryptography. Springer, 1--15.

Digital Library

[6]

Xi Fang, Satyajayant Misra, Guoliang Xue, and Dejun Yang. 2012. Smart gridâĂŤThe new and improved power grid: A survey. IEEE communications surveys & tutorials 14, 4 (2012), 944--980.

[7]

Luiz MR Gadelha Jr and Marta Mattoso. 2008. Kairos: an architecture for securing authorship and temporal information of provenance data in grid-enabled work-flow management systems. In eScience, 2008. eScience'08. IEEE Fourth International Conference on. IEEE, 597--602.

Digital Library

[8]

Pengfei Gao, Shunfu Lin, and Wilsun Xu. 2014. A novel current sensor for home energy use monitoring. IEEE Transactions on Smart Grid 5, 4 (2014), 2021--2028.

[9]

Ashish Gehani and Ulf Lindqvist. 2007. Bonsai: Balanced lineage authentication. In Computer Security Applications Conference, 2007. ACSAC 2007. Twenty-Third Annual. IEEE, 363--373.

[10]

Ayesha Hafeez, Nourhan H Kandil, Ban Al-Omar, T Landolsi, and AR Al-Ali. 2014. Smart Home Area Networks Protocols within the Smart Grid Context. journal of Communications 9, 9 (2014).

[11]

Rong Jiang, Rongxing Lu, Ye Wang, Jun Luo, Changxiang Shen, and Xuemin Sherman Shen. 2014. Energy-theft detection issues for advanced metering infrastructure in smart grid. Tsinghua Science and Technology 19, 2 (2014), 105--120.

[12]

Sye Loong Keoh, Yi Han Ang, and Zhaohui Tang. 2015. A lightweight privacy-preserved spatial and temporal aggregation of energy data. In Information Assurance and Security (IAS), 2015 11th International Conference on. IEEE, 1--6.

[13]

Nikos Komninos, Eleni Philippou, and Andreas Pitsillides. 2014. Survey in smart grid and smart home security: Issues, challenges and countermeasures. IEEE Communications Surveys & Tutorials 16, 4 (2014), 1933--1954.

[14]

John Lyle, Andrew P Martin, and others. 2010. Trusted Computing and Provenance: Better Together. In TaPP.

Digital Library

[15]

Jenny Röbesaat, Peilin Zhang, Mohamed Abdelaal, and Oliver Theel. 2017. An Improved BLE Indoor Localization with Kalman-Based Fusion: An Experimental Study. Sensors 17, 5 (2017), 951.

[16]

Cristina Rottondi, Giacomo Verticale, and Christoph Krauss. 2013. Distributed privacy-preserving aggregation of metering data in smart grids. IEEE Journal on Selected Areas in Communications 31, 7 (2013), 1342--1354.

[17]

Adi Shamir. 1979. How to share a secret. Commun. ACM 22, 11 (1979), 612--613.

Digital Library

[18]

Victor Shoup. 2000. Practical threshold signatures. In International Conference on the Theory and Applications of Cryptographic Techniques. Springer, 207--220.

Digital Library

[19]

Yu Shyang Tan, Ryan KL Ko, and Geoff Holmes. 2013. Security and data accountability in distributed systems: A provenance survey. In High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing (HPCC_EUC), 2013 IEEE 10th International Conference on. IEEE, 1571--1578.

[20]

Mark Ward. 2014. Smart meters can be hacked to cut power bills. http://www.bbc.com/news/technology-29643276. (2014). Retrieved November 29, 2016 from http://www.bbc.com/news/technology-29643276 Online; accessed 29 November 2016.

Cited By

Faraj OMegias DGarcia-Alfaro J(2025)Security Approaches for Data Provenance in the Internet of Things: A Systematic Literature ReviewACM Computing Surveys10.1145/3718735Online publication date: 19-Feb-2025
https://dl.acm.org/doi/10.1145/3718735
Parameswarath RSikdar B(2024)Privacy-Preserving Data Provenance for Smart Meter Communications2024 Conference on Building a Secure & Empowered Cyberspace (BuildSEC)10.1109/BuildSEC64048.2024.00009(1-7)Online publication date: 19-Dec-2024
https://doi.org/10.1109/BuildSEC64048.2024.00009
Jaigirdar FTan BRudolph CBain C(2023)Security-Aware Provenance for Transparency in IoT Data PropagationIEEE Access10.1109/ACCESS.2023.328092811(55677-55691)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3280928
Show More Cited By

Index Terms

Secure Data Provenance in Home Energy Monitoring Networks
1. Security and privacy
  1. Network security
    1. Security protocols
  2. Systems security
    1. Distributed systems security

Recommendations

A Home Energy Management System for Energy-Efficient Smart Homes
CSCI '14: Proceedings of the 2014 International Conference on Computational Science and Computational Intelligence - Volume 02

As the carbon dioxide emission and global warming become the world serious issues, many researches are performed to reduce the energy consumption. Therefore, there are many new devices for energy saving scheme in the smart home area, such as smart plug, ...
Systematic Literature Review on Data Provenance in Internet of Things
Computational Science and Its Applications – ICCSA 2022 Workshops
Abstract
Internet of Things(IoT) is a concept that develops day by day and is now an indispensable part of our lives. Although it has been developed a lot, it still has many problematic areas and has many aspects that need improvement. On the other hand, ...
A secure and extensible blockchain-based data provenance framework for the Internet of Things
Abstract
As data collected and provided by Internet of Things (IoT) devices power an ever-growing number of applications and services, it is crucial that this data can be trusted. Data provenance solutions combined with blockchain technology are one way to ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Other conferences

ICSS 2017: Proceedings of the 3rd Annual Industrial Control System Security Workshop

December 2017

35 pages

ISBN:9781450363334

DOI:10.1145/3174776

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

ACSA: Applied Computing Security Assoc

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 December 2017

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Conference

ICSS 2017

ICSS 2017: 2017 Annual Industrial Control System Security Workshop

December 5, 2017

PR, San Juan, USA

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

11
Total Citations
View Citations
149
Total Downloads

Downloads (Last 12 months)12
Downloads (Last 6 weeks)0

Reflects downloads up to 07 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Faraj OMegias DGarcia-Alfaro J(2025)Security Approaches for Data Provenance in the Internet of Things: A Systematic Literature ReviewACM Computing Surveys10.1145/3718735Online publication date: 19-Feb-2025
https://dl.acm.org/doi/10.1145/3718735
Parameswarath RSikdar B(2024)Privacy-Preserving Data Provenance for Smart Meter Communications2024 Conference on Building a Secure & Empowered Cyberspace (BuildSEC)10.1109/BuildSEC64048.2024.00009(1-7)Online publication date: 19-Dec-2024
https://doi.org/10.1109/BuildSEC64048.2024.00009
Jaigirdar FTan BRudolph CBain C(2023)Security-Aware Provenance for Transparency in IoT Data PropagationIEEE Access10.1109/ACCESS.2023.328092811(55677-55691)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3280928
Dayaratne TJaigirdar FDasgupta RSakzad ARudolph C(2023)Improving Cybersecurity Situational Awareness in Smart Grid EnvironmentsPower Systems Cybersecurity10.1007/978-3-031-20360-2_5(115-134)Online publication date: 9-Feb-2023
https://doi.org/10.1007/978-3-031-20360-2_5
Sifah EXia QAgyekum KXia HSmahi AGao J(2022)A Blockchain Approach to Ensuring Provenance to Outsourced Cloud Data in a Sharing EcosystemIEEE Systems Journal10.1109/JSYST.2021.306822416:1(1673-1684)Online publication date: Mar-2022
https://doi.org/10.1109/JSYST.2021.3068224
Sun STang HDu R(2022)A Novel Blockchain-Based IoT Data Provenance Model2022 2nd International Conference on Computer Science and Blockchain (CCSB)10.1109/CCSB58128.2022.00015(46-52)Online publication date: Oct-2022
https://doi.org/10.1109/CCSB58128.2022.00015
Yin FFu Z(2022)A Data Provenance Scheme Based on Blockchain for Internet of Things2022 2nd International Conference on Computer Science and Blockchain (CCSB)10.1109/CCSB58128.2022.00014(42-45)Online publication date: Oct-2022
https://doi.org/10.1109/CCSB58128.2022.00014
Gultekin EAktas M(2022)A Business Workflow Architecture for Predictive Maintenance using Real-Time Anomaly Prediction On Streaming IoT Data2022 IEEE International Conference on Big Data (Big Data)10.1109/BigData55660.2022.10020384(4568-4575)Online publication date: 17-Dec-2022
https://doi.org/10.1109/BigData55660.2022.10020384
Gultekin EAktas M(2022)Systematic Literature Review on Data Provenance in Internet of ThingsComputational Science and Its Applications – ICCSA 2022 Workshops10.1007/978-3-031-10542-5_3(31-46)Online publication date: 23-Jul-2022
https://doi.org/10.1007/978-3-031-10542-5_3
Janita BKannan RKumaratharan N(2020)Enhancing Security in Smart Homes-A ReviewIntelligent Computing in Engineering10.1007/978-981-15-2780-7_40(361-369)Online publication date: 10-Apr-2020
https://doi.org/10.1007/978-981-15-2780-7_40
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten