Power Systems: A Matter of Security and Privacy

  • Anne V. D. M. Kayem
  • Stephen D. Wolthusen
  • Christoph Meinel
Part of the Advances in Information Security book series (ADIS, volume 71)


Studies indicate that reliable access to power is an important enabler for economic growth. To this end, modern energy management systems have seen a shift from reliance on time-consuming manual procedures , to highly automated management , with current energy provisioning systems being run as cyber-physical systems . Operating energy grids as a cyber-physical system offers the advantage of increased reliability and dependability , but also raises issues of security and privacy. In this chapter, we provide an overview of the contents of this book showing the interrelation between the topics of the chapters in terms of smart energy provisioning. We begin by discussing the concept of smart-grids in general, proceeding to narrow our focus to smart micro-grids in particular. Lossy networks also provide an interesting framework for enabling the implementation of smart micro-grids in remote/rural areas, where deploying standard smart grids is economically and structurally infeasible. To this end, we consider an architectural design for a smart micro-grid suited to low-processing capable devices. We model malicious behaviour, and propose mitigation measures based properties to distinguish normal from malicious behaviour .


Lossy networks Low-processing capable devices Smart micro-grids Security Privacy Energy 


  1. 1.
    A. Abur and A. Gómez Expósito. Power System State Estimation: Theory and Implementation. CRC Press, Boca Raton, FL, USA, 2004.CrossRefGoogle Scholar
  2. 2.
    P. L. Ambassa, A. Kayem, S. Wolthusen, and C. Meinel. Secure and reliable power consumption monitoring in untrustworthy micro-grids. In Robin Doss, Selwyn Piramuthu, and Wei ZHOU, editors, Future Network Systems and Security, volume 523 of Communications in Computer and Information Science, pages 166–180. Springer, Cham, Switzerland, 2015.CrossRefGoogle Scholar
  3. 3.
    P. L. Ambassa, S. Wolthusen, A. Kayem, and C. Meinel. Robust snapshot algorithm for power consumption monitoring in computationally constrained micro-grids. In Smart Grid Technologies - Asia (ISGT ASIA), 2015 IEEE Innovative, Bangkok, Thailand, pages 1–6, Piscataway, NJ, USA, 3–6 Nov. 2015. IEEE Press.Google Scholar
  4. 4.
    A. Baiocco, S. Wolthusen, C. Foglietta, and S. Panzieri. A model for robust distributed hierarchical electric power grid state estimation. In Innovative Smart Grid Technologies Conference (ISGT), 2014 IEEE PES, pages 1–5, Piscataway, NJ, USA, Feb 2014. IEEE Press.Google Scholar
  5. 5.
    P. Buchana and T. S. Ustun. The role of microgrids amp; renewable energy in addressing sub-saharan Africa’s current and future energy needs. In Renewable Energy Congress (IREC), 2015 6th International, pages 1–6, Sousse, Tunisia, 24–26 March 2015. IEEE Press.Google Scholar
  6. 6.
    Y. Feng, C. Foglietta, A. Baiocco, S. Panzieri, and S. Wolthusen. Malicious false data injection in hierarchical electric power grid state estimation systems. In Proceedings of the Fourth International Conference on Future Energy Systems, e-Energy ’13, pages 183–192, New York, NY, USA, 2013. ACM.Google Scholar
  7. 7.
    K. Iniewski. Smart Grid: Infrastructure and Networking. McGraw Hill, New York, NY, USA, 2013.Google Scholar
  8. 8.
    A. Kayem, C. Meinel, and S. Wolthusen. A smart micro-grid architecture for resource constrained environments. In 2017 IEEE 31st International Conference on Advanced Information Networking and Applications (AINA), pages 857–864, March 2017.Google Scholar
  9. 9.
    G. N. Korres. A distributed multiarea state estimation. IEEE Transactions on Power Systems, 26(1):73–84, Feb 2011.CrossRefGoogle Scholar
  10. 10.
    R. Kuwahata, N. Martensen, T. Ackermann, and S. Teske. The role of microgrids in accelerating energy access. In 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), pages 1–9, Piscataway, NJ, USA, Oct 2012. IEEE Press.Google Scholar
  11. 11.
    Z. Liu. Chapter 3 - a global energy outlook. In Zhenya Liu, editor, Global Energy Interconnection, pages 91–100. Academic Press, Boston, 2015.Google Scholar
  12. 12.
    A. M. C. Marufu, A. Kayem, and S. Wolthusen. A distributed continuous double auction framework for resource constrained microgrids. In 10th International Conference on Critical Information Infrastructures Security (CRITIS 2015), October 5–7, 2015, Berlin, Germany, pages 183–196. Vol. 9578, Lecture Notes in computer Science, Springer, 2015.Google Scholar
  13. 13.
    A. M. C. Marufu, A. Kayem, and S. Wolthusen. Fault-tolerant distributed continuous double auctioning on computationally constrained microgrids. In 2nd International Conference on Information systems Security and Privacy (ICISSP 2016), February 19–21, 2016, Rome, Italy, pages 448–456. SCITEPRESS, 2016.Google Scholar
  14. 14.
    A. M. C. Marufu, A. V. D. M. Kayem, and S. D. Wolthusen. Power auctioning in resource constrained micro-grids: Cases of cheating. In Grigore Havarneanu, Roberto Setola, Hypatia Nassopoulos, and Stephen Wolthusen, editors, Critical Information Infrastructures Security, pages 137–149. Springer International Publishing, Cham, 2017.Google Scholar
  15. 15.
    E. D. Moe and A. P. Moe. Off-grid power for small communities with renewable energy sources in rural Guatemalan villages. In Global Humanitarian Technology Conference (GHTC), 2011 IEEE, pages 11–16, Piscataway, NJ, USA, Oct 2011. IEEE Press.Google Scholar
  16. 16.
    D. Nikolaev, Nikovski, Z. Wang, A. Esenther, H. Sun, K. Sugiura, T. Muso, and K. Tsuru. Smart meter data analysis for power theft detection. In Petra Perner, editor, Proceedings of the 9th International Conference on Machine Learning and Data Mining in Pattern Recognition (MLDM 2013), volume 7988 of Lecture Notes in Computer Science, pages 379–389, New York, NY, USA, Jul 2013. Springer.CrossRefGoogle Scholar
  17. 17.
    T. Winther. Electricity theft as a relational issue: A comparative look at Zanzibar, Tanzania, and the Sunderban Islands, India. Energy for Sustainable Development, 16(1):111–119, 2012.CrossRefGoogle Scholar
  18. 18.
    G. K. Weldehawaryat, P. L. Ambassa, A. M. C. Marufu, S. D. Wolthusen, and A. Kayem, “Decentralised scheduling of power consumption in micro-grids: Optimisation and security,” in Security of Industrial Control Systems and Cyber-Physical Systems - Second International Workshop, CyberICPS 2016, Heraklion, Crete, Greece, September 26–30, 2016, Revised Selected Papers, vol. 10166 of Lecture Notes in Computer Science, (Heraklion, Greece), pp. 69–86, Springer, Sept 2016.Google Scholar
  19. 19.
    P. Vytelingum, S. D. Ramchurn, T. D. Voice, A. Rogers, and N. R. Jennings, “Trading agents for the smart electricity grid,” in 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), Toronto, Canada, May 10–14, 2010, Volume 1-3, pp. 897–904, International Foundation for Autonomous Agents and Multiagent Systems, 2010.Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Anne V. D. M. Kayem
    • 1
  • Stephen D. Wolthusen
    • 2
    • 3
  • Christoph Meinel
    • 1
  1. 1.Hasso-Plattner-Institute, Faculty of Digital EngineeringUniversity of PotsdamPotsdamGermany
  2. 2.Department of Mathematics and Information SecurityRoyal Holloway, University of LondonEghamUK
  3. 3.Norwegian Information Security LaboratoryGjovik University College, Norwegian University of Science and TechnologyTrondheimNorway

Personalised recommendations