Analysis of the Security Anomalies in the Smart Metering
Infrastructure and Its Impact on Energy Profiling and Measurement
Pallab Ganguly
, Sumit Poddar
, Sourav Dutta
and Mita Nasipuri
CESC Limited, Kolkata, India
IBM, Kolkata, India
Dept. of CSE, Jadavpur University, Kolkata, India
Keywords: Encryption, Smart Grid, Smart Meter, Security, AMR, AMI, Consumer, M2M, Energy Meters.
Abstract: Security of the smart metering infrastructure, which is a part of the smart grid initiative, intended at
transitioning the legacy power grid system into a robust, reliable, adaptable and intelligent energy utility, is
an imminent problem that needs to be addressed quickly. Moreover, the increasingly intensifying integration
of smart metering infrastructure with other ecosystem applications and the underlying communication
technology is forcing both the consumer and the utility provider to meticulously look into the security and
privacy issues of the smart grid. To achieve this, improvements on the existing architecture that uses smart
meters interacting with smart grid is needed. This architecture would help in consolidation and aggregation
of the energy usage and generation as intelligent communicators instead of focusing them as isolated
passive units in the energy grid. The study presented in the paper analyses the various existing smart
metering infrastructure, threats and vulnerabilities that has the potential to disrupt the operation and
deployment of automation systems in smart grids. Furthermore, an elaborate study and subsequent analysis
have been made on a live consumer meter setup in a non-invasive manner, which shows the various security
loopholes and deficiencies of a large deployment of unattended smart meters. The study identifies the
potential gaps and suggests possible measures for a cost effective and robust solution to cater for present as
well as future needs.
The interaction between a smart house and a smart
grid based on Information and Communications
Technologies (ICT) can fully exploit the capabilities
of the smart energy network (Palensky, 2011). A
smart meter is usually an electronic device that
records consumption of electric energy at certain
intervals (frequency of which can be programmed)
and communicates that information on a regular
basis with the utility provider for monitoring and
billing. Smart meters enable two-way
communication between the meter and the central
In today’s scenario, the security of smart
metering infrastructures is a very critical issue and
plays an important role. In this study, the analysis is
made on a live consumer meter setup, where the
meter is serially connected with a communication
modem and connected to the mobile communication
network which, in turn is connected to the public
Internet. The meter data through Internet reaches the
corporate data communication network and is stored
in the aggregation server. The interim data packets
have been captured and analyzed from the live
consumer meter setup in a non-invasive manner
from the production environment and the findings
were noted. The data is sent in a special format
which is understood only by the aggregation server
and processed in a proprietary manner. But there
exists a high chance of manipulating this extracted
data. The consumer billing is directly dependent on
the meter reading parameters and if the meter data is
tampered, the consumers and most importantly the
utility service provider will be highly impacted. The
number of services like meter reading, online
pricing, information security or load control, which
is the part of the energy ecosystem could get
jeopardized. Thus, robust security mechanisms have
to be incorporated in the design of the meter
infrastructure to prevent any potential fraud. Since
the power utility is one of the most mission critical
infrastructure services today, the comprehensive
Ganguly, P., Poddar, S., Dutta, S. and Nasipuri, M.
Analysis of the Security Anomalies in the Smart Metering Infrastructure and Its Impact on Energy Profiling and Measurement.
In Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS 2016), pages 302-308
ISBN: 978-989-758-184-7
2016 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
security and privacy mechanisms are needed to
ensure robust, reliable and smooth operation of the
smart grid. A thorough analysis of technical
vulnerabilities and identification of threats is an
important step toward securing smart metering
The three most important security objectives that
must be incorporated in the smart grid systems, are:
1) Ensure data integrity is maintained throughout the
end to end communication channel, 2) Proper
authentication and authorization needs to be adopted
and 3) Confidentiality of user’s data. The smart
metering infrastructure is visualized as an unsecured
system to permit authority from various gadgets and
users. The potential security problems related to
smart metering systems have been surveyed and an
actual threat scenario has been implemented
confirming the vulnerability of the current smart
metering infrastructure.
The main sections in this paper are as follows:
Study of the previous works in the field of
security and privacy issues in smart energy
metering infrastructure, over a considerable
period focusing on recent implementations from
meter manufacturers, standards as well as
Under the hood of Smart Energy Meters,
discusses the internals as well as gives insight
into the live consumer setup for interception and
manipulation of energy metering data.
Study of Smart Meters in a live big power
utility’s grid.
Detection and Analysis of the energy metering
data for veracity, discusses the various areas that
need to be addressed for plugging the gaps.
There have been a number of works and commercial
implementations based on certain standards
throughout the world. An exhaustive study has been
done both on theoretical work as well as the
practical implementation available in the realms of
energy meter hardware, communication standards/
protocols and the Information Technology system.
The financial impact on the utility provider in the
smart metering infrastructure is also discussed.
The major problems in Advanced Metering
Infrastructure (AMI), especially embedded system
are insecure data buses and serial connections, data
capture and injection, radios and microcontroller
units causing problems like replacing or stealing
memory keys, firmware level vulnerabilities and
resetting of Joint Test Action Group (JTAG) fuses.
The AMI utility premises vulnerabilities like buffer
overflows, Structured Query Language (SQL)
injection, credential hijacking, needs firewalling in
between the system components and internet
connectivity to the head end. Only required ports
should be open in the firewall and the other ports
should be blocked by default. Researchers
(Carpenter, 2008); (Lawson, 2010) have gained
access inside the smart modules of electrical meters
and identified the microcontroller. They were able to
identify the JTAG pin outs and ultimately dumped
the program inside the microcontroller through
JTAG cable to a computer (Lawson, 2010).
However, no further analysis was reported of the
dump. The possibilities of breaking a meter were
discussed in many forums and the software flaws
and hardware weaknesses and also the disadvantages
of the Microcontroller unit is a serious issue as cited
by (Carpenter, 2008), (Lawson, 2010) and (Davis,
2009). It is important to point out that the software
dump extracted from the microcontroller memory
has severe implications across the entire AMI
There are different kinds of communication
protocols and standards used for the smart metering
infrastructure. A survey on the communication
protocols and standards used for Automated Meter
Reading (AMR) application has been mentioned by
Khalifa et al., (2011) and Feuerhahn et al., (2011).
The paper discusses about the benefits of the 3G
communication system, Device Language Message
specification/ Companion Specification for Energy
Metering standard and the Internet Protocol (IP)
based Session Initiation Protocol (SIP) for signaling
at the application level. While analyzing the future
of AMR, the researchers agreed to the concern that
the provision of data integrity in metering was given
more priority than the data privacy cited by Ye Yan
et al., (2013). In the paper by Ye Yan et al., (2012),
the authors discussed that a built-in security
mechanism is necessary in comprehensive smart
grid communication architecture. Researchers have
elaborated their points by giving the background,
requirements, challenges and current solution. In
explaining the background, they have given thrust to
the Supervisory Controlled and Data Acquisition,
Communication network and deployment. The
authors discussed the motivations, requirement and
challenges in the smart grid communication
infrastructures in Ye Yan et al., (2013). The paper
suggested how reliability, operational efficiency and
customer satisfaction can be addressed with an AMI
deployment. Authors have proposed a 2-phase
Analysis of the Security Anomalies in the Smart Metering Infrastructure and Its Impact on Energy Profiling and Measurement
method to provide security of data using dedicated
authentication server, which inhibits malicious and
unauthorized nodes to gain access to advanced meter
infrastructure communication network cited by
Mehra et al.(2013). The result found through a NS2
simulator confirms that security threats can be
reduced by adding key management system over the
existing infrastructure. The problem in this method
is the huge overhead for manageability of the key for
such a large deployment of smart metering system.
The recommendation by Florian Skopik et al.,
(2013) was to make the smart meters and
concentrator nodes physically robust and tamper
resilient. Authentication mechanism, digital
certificates and signatures, encryption of
communication data should be adopted. The author
(Farid Molazem) discusses the Security and privacy
of smart meters in detail and a security mechanism
has been developed for smart metering system. It has
been further classified into two categories viz.
intrusion detection method and remote attestation
method. The strength and weaknesses of both the
methods have been mentioned. The paper concluded
with the fact that the monitoring and the protection
system for the software running inside the meters
has to be explored and the existing security
techniques applied to the smart meters rely on the
running cryptographic algorithm on the meters but
the old meters might not have the processing power
or adequate memory to perform intense
cryptographic operations.
Similarly, the authors (Finster and Baumgart,
2015) have surveyed the privacy issue of the smart
metering infrastructure and have classified privacy
problem from a metering perspective. They have
approached the problem from two angles: metering
for billing and metering for operations. For each of
these problems they have identified generic
approaches. They have compared the various
approaches for the metering for billing issue by
smart meter complexity, infrastructure complexity
and attack complexity for trusted third parties,
trusted computing and cryptographic proofs.
Similarly they have compared the approaches to
metering for operation by the same parameters but
the approaches were for pseudonymization without
aggregation, trusted third party with aggregation,
aggregation without trusted third parties and
submission of imprecise data. They have surveyed a
number of papers and concluded that meter
deployment and simultaneously maintaining privacy
is a huge challenge and an avenue for further
Future scope of research exist in the field of
system complexity, communication path, clash in
between privacy preservation and information usage
accomplishing advanced encryption techniques and
interoperability between cryptographic system in
smart grid elements like memory usage, Central
Processing Unit utilization etc. (Bhatia and Bodade,
2014), Yonghe Guo et al., (2015). They also have
discussed the cyber-attacks pertaining to the AMI
viz. connection based attacks for communication
media or protocol based attacks and security flaws in
devices and recruitment of attack agent in metering
device like implanting malicious program inside the
meter or spread malware in the system. The subject
concluded with the facts that besides deploying
detection system, to maintain security levels,
software bugs should be removed; updating
firmware in regular intervals, updating protocol and
Software patching is to be done. The author defined
the smart grid and smart meter and discussed the
related work on policy level and technology level
Kalogridis et al., (2010), Khurana et al., (2010). The
paper by Kalogridis et al., (2010) also emphasized
on the load forecasting possibility in smart metering
system. The current practices of cryptographic key
management which is useful for small deployments
of smart meters but for large deployments the
management of the cryptographic keys would
require more staffs which is an issue for a power
utility. Aloul et al., (2012) concluded with some
proposed solutions like Identity verification through
strong authentication mechanism, organization
should have implicit deny policy, malware
protection in embedded system. The authors Liu et
al., (2012) projected an overview of smart grid and
relevant technologies and given a future research
direction in the cyber security and privacy issues of
smart grid. An archetypal attack tree approach has
been developed to guide penetration testing across
multivendor implementation by Stephen et al.,
(2010). Academic and Industrial penetration testing
efforts have found flaws in meter hardware,
firmware, network protocols and the Internet.
Ultimately it could not throw much light on the
protection mechanism present at the collector links
to the backhaul network. (Jawurek, 2011) proposed
future research work was necessary for the privacy
and protection of the above data types. The data
communication security of the advanced meter
infrastructure in smart grid is a serious problem. The
financial impact in smart metering infrastructure is a
burning issue where the financial loss to premise
owners, utility provider and the nation as a whole is
of immense importance. If the meter reading of the
consumer is altered, the premise owner has to pay
SMARTGREENS 2016 - 5th International Conference on Smart Cities and Green ICT Systems
extra bills for no reason. The attacker can also
switch off the power supply at the consumer
premises and take malicious remote control over the
appliance present in the consumer premises. There is
a chance of huge financial impact to a utility
provider if the attacker attacks the utility server and
manipulates the meter reading to lower usage than
the actual consumption by the customer. If the
attacker takes the control of the utility server, it can
send erroneous control commands to the meter on
behalf of the utility server. The customer will take
advantage and will not pay the bills. In case of even
bigger threat scenario, there could be major power
blackouts which could impact the transport
infrastructure, banking system, healthcare systems
and various industry verticals all across the targeted
country cited by Yussof et al., (2014). After the
comprehensive literature study, the major findings
indicate lack of security and privacy in the various
layers of the present smart metering infrastructure.
This paper addresses the security issues mentioned
above and attempts to focus on the AMR and the
communication mechanism as an immediate quick
fix to the larger problem.
A smart meter is an electronic device that records
consumption of utility services [such as electricity]
at fixed intervals and communicates that information
as per schedule with the aggregation server at the
utility premises for monitoring and billing. Smart
meters enable two-way communication between the
meter and the central aggregation system for
complete monitoring as well as control of the
services. As shown in Fig 1, basically all smart
meters usually contain a microcontroller with flash
memory, external data memory, a liquid crystal
display driver and a communication modem with
suitable connectivity. The programmable memory
can be a onetime erasable programmable read-only
memory, a serial Electrically Erasable
Programmable Read-Only Memory or a parallel
Electrically Erasable Programmable Read-Only
Memory. Some smart meters have external
communication modems connected with a RS232
serial interface. Different meter vendors use
different setup.
The important global standards used in Smart
Metering are IEC 62051, IEC 62056, IEC 62351,
IEEE 1377, RFC 3394, ANSI C12.19, ANSI C12.22
etc. The standard IEC 62051 is used for Data
exchange for Meter Reading, Tariff and Control.
IEC 62056 is used for Electricity meter data
exchange. The power systems management and
associated information exchange with Data and
communication security uses the IEC 62351
standard. IEEE 1377 is used for the metering
communication protocol in the application layer &
RFC 3394 is for advanced encryption standard key
wrap algorithm. ANSI C12.19 is needed for utility
industry end device data table & ANSI C12.22 is
needed for protocol specification to interface with
data communication networks. There are no specific
standards on communication and cybersecurity for
Wide Area Networks, Neighborhood Area Networks
and Home Area Networks. If we look into the global
smart metering journey, the first generation had one
way Radio Frequency or low bandwidth Power Line
Communication technology, business benefits
focused on optimized meter reading costs and
maximum deployment of smart meters took place in
the United States. The benefits of smart metering
includes improving billing efficiency, providing
meaningful consumption information, reducing
operational cost and reducing overall and peak
demand. The trends in smart metering increased the
analysis of data and frequency of reading, the
numbers and types of devices to manage
multivendor access and high volume processing on
the immediate horizon. Gradually legacy utility
application has adapted to an AMI environment. It
impacted the meter information on consumer and the
consumer information system needed to be
integrated with the meter data management system.
The device communication strategy needed to allow
multiple protocols for meaningful communication
and integration with multivendor gadgets. The
Machine to Machine (M2M) devices include the
smart meter, communication interface,
communication devices and the central aggregation
server. Different approach models like M2M device
models and Semantic models were suggested by
global system integrators. Device model is a digital
description of physical devices and their
relationships. The model should be able to integrate
cross domain functionality water, energy, transport,
public etc. Each domain has their own standards,
language, models etc. The meaning of each of the
domain can be explained with the Semantic model,
where the devices with their standards and relations
are captured. The approach makes use of storing the
devices in specified formats. The M2M devices can
either communicates directly using low level
protocols or standards or via M2M gateway or
Analysis of the Security Anomalies in the Smart Metering Infrastructure and Its Impact on Energy Profiling and Measurement
central Hub. To model a M2M gateway as a generic
model, the sensors, actuators, components could also
be defined with the device model.
Figure 1: Schematic of a Smart Meter.
Figure 2: Actual Equipment used for the test setup.
We have built an experimental setup with trial
meters inside a big power utility in India,
distributing electricity to 2.9 mil consumers. The
meters communicate with the application ecosystem
of the utility provider using extant public
communication mechanisms. The smart meters had a
General Packet Radio Service (GPRS) supported
modem built-in which communicates with the Base
Transceiver Station (BTS) of the mobile service
provider. The mobile service provider routes the
data to the Internet through which the data traverses
and enters the Utility provider’s router. It is further
channelized through the internet link load balancer
and then filtered through a packet filtering Firewall
which supports role based access-control (RBA)
stateful fire-walling. After passing through the
firewall it reaches the core switch which again
performs role based access control and according to
a particular access control statement sends the data
to the meter data acquisition system test server. Here
the data is processed and the requisite files are sent
to the test instance of the billing server for trial
customer bill statement. We have captured the data
through a packet capturing tool from the public
Internet and analyzed, re-engineered by
manipulating the meter data with our customized
algorithm and channelized into the grid to reach the
designated test server, without tampering any of the
entries in the firewall or the core switch. After
processing the data through the back-end
application, we found that the re-engineered data
was accepted in the test system and the manipulated
data were reflected in the test billing system. The
major challenges in this activity were to find the
encryption and decryption algorithms and the data
model used in the system-on-chip of the smart
meters and the head end system. We could identify
the various stages from where the data could be
manipulated, injected and/or accessed and have
come with several solutions to plug those. It is
currently under research as this has come as a
surprise even to the provider. The actual
experimental setup is given in (Fig.3).
Figure 3: Actual Experimental Setup.
In this paper we have studied meters from multiple
SMARTGREENS 2016 - 5th International Conference on Smart Cities and Green ICT Systems
vendors and have carried out the experiment on a
particular brand. But the underlying architecture
remains the same for all the vendors. The meter data
is usually passed through public internet service
providers for connectivity with the Utility Service
Provider’s aggregation systems. There is always a
possibility of the data getting manipulated under the
present setup. The meter data is usually encrypted
using very rudimentary mechanism countenancing
the possibility of manipulation of the data generated.
The veracity of data generated at the meter thus
cannot be guaranteed with the present
implementation. The study results of four meter
manufacturing vendors are provided in (Fig. 4). We
have considered the typical three high-level security
objectives for the smart grid: Availability, Integrity
and Confidentiality per the NIST guidelines (NISTIR
7628, 2010). The widely used representation for
availability is the ratio of the value of the uptime of a
system to the total of the values of the up and down
times (planned as well as unplanned).
A=Uptime / Uptime + Downtime (planned) + Outage
For the values of integrity and confidentiality, we
have taken few parameters to keep it simple at this
level e.g. for integrity – whether it is possible to
modify the meter in an unauthorized manner,
destruction of the meter data etc. and, for
confidentiality – whether the default setup is used
[known access to all], use of any standard encryption
mechanism or plain text data in complex format. As
the result indicates, the availability part is satisfied by
all the vendors. The integrity part has been handled
in a primitive manner and needs more focus. The
confidentiality issue has to be given more attention
keeping in view of the increasing use of open public
communication channels instead of point-to-point
tremendously expensive private networks.
Figure 4: Common-of-the-Shelf (COTS) Smart Grid Meter
Advanced metering infrastructure is being
implemented across the globe, and detailed
information about millions of consumers’ electricity
use will be streaming into energy utilities for various
reports and other operational analyses. It is of
paramount importance that the analysis of the
security anomalies in the smart metering
infrastructure and its impact on energy profiling and
measurement to be done with respect to the current
and future trends. This paper gives an insight into
the current smart metering techniques with its merits
and demerits. The work studied has been categorized
into end equipment [meter hardware];
communication mechanism and the back end IT
applications. With the huge deployment of smart
meters, security is a grave concern from a financial
perspective as well. The end to end traversal of data
from the smart meter at the customer premises to the
aggregation unit at the service provider’s end is
usually via the open public communication channels
basically because of ease of deployment and most
importantly, due to financial constraints. Albeit
difficult to understand, it is possible to manipulate
the data which has a huge financial as well as
operational implication. In this paper we have also
studied and analyzed a live consumer meter setup in
a non-invasive manner [of a tier-1 power service
provider] and found the various loopholes and
deficiencies of a large deployment of smart meters.
It was also found that the current metering standards
and protocols cited by Khalifa et al., (2011),
Feuerhahn et al., (2011), and Mehra et al., (2013) are
inadequate to address these security challenges. For
the successful smart grid implementation, the
Information Technology and the Operational
Technology (IT/OT) convergence needs to be
established so that the Master control center of a
power utility can be integrated with the smart
metering data management system through a
common information model. Without the mitigation
of the anomalies in the smart metering
infrastructure, the IT/OT convergence will not be
possible and potential area for research. The
execution of the ICT security measures is expected
to have a high impact, throughout the full electricity
value chain, on energy efficiency, sustainability and
grid management efficiency. Further work is being
done to address the various gaps and propose a cost
effective and robust solution to cater for present as
well as future needs.
Analysis of the Security Anomalies in the Smart Metering Infrastructure and Its Impact on Energy Profiling and Measurement
Peter Palensky “Demand Side Management: Demand
Response, Intelligent Energy Systems, and Smart
Loads” Delft University of Technology, IEEE
Transactions on Industrial Informatics, September,
Carpenter M. Hacking AMI. (2008). [Online]. Available:
Lawson N. Reverse-engineering a smart meter. (2010).
Mike Davis- Senior Security Consultant at Black Hat USA
2009, “Smart Grid Device Security Adventures in a
new medium”.
Khalifa, T.; Naik, K.; Nayak, A, "A Survey of
Communication Protocols for Automatic Meter
Reading Applications,” Communications Volume: 13,
Issue: 2 , 2011.
Feuerhahn, S.; Zillgith, M.; Wittwer, C.; Wietfeld, C,
"Comparison of the Communication Protocols
DLMS/COSEM, SML and IEC 61850 for Smart
Metering Applications," Smart Grid Communications
(SmartGridComm), IEEE International Conference,
Ye Yan, Hu R. Q, Das S. K, Sharif H,” An Efficient
Security Protocol for Advanced Metering
Infrastructure in Smart Grid. ”Network, IEEE Volume:
27, Issue: 4, Publication Year: 2013, Page(s): 64 – 71.
Ye Yan, Yi Qian, Hamid Sharif, and David Tipper, “A
Survey on Cyber Security for Smart Grid
Communications,” IEEE Communications Surveys
and Tutorials, Vol.14, Issue 4, pp.998-1010, 4th
Quarter 2012.
Ye Yan, Yi Qian, Hamid Sharif, and David Tipper, “A
Survey on Smart Grid Communication Infrastructures:
Motivations, Requirements and Challenges,” IEEE
Communications Surveys and Tutorials, Vol.15, Issue
1, pp.5-20, 1st Quarter 2013.
Mehra, T, Dehalwar, V, Kolhe, M, “Data Communication
Security of Advanced Metering Infrastructure in Smart
Grid,” 2013 5th IEEE International Conference on
Computational Intelligence and Communication
Florian Skopik, Zhengdong Ma, Thomas Bleier, Helmut
Gruneis, "A Survey on Threats and Vulnerabilities in
Smart Metering Infrastructure," International Journal
of Smart Grid and Clean Energy, August 13.
Farid Molazem, “Security and Privacy of Smart Meters: A
Survey”, University of British Columbia.
Rajiv. K. Bhatia, Varsha Bodade, "Smart Grid Security
and Privacy: Challenges, literature Survey and Issues,"
International Journal of Advanced Research in
Computer Science and Software Engineering, volume
4, Issue 1, January 2014.
Yonghe Guo, Chee-Wooi Ten, Shiyan Hu, Wayne
Weaver, “Modeling Distributed Denial of Service
Attack in Advanced Metering Infrastructure," IEEE
PES Innovative Smart Grid Technologies,
Washington, DC; December 2015.
Kalogridis, G., Efthymiou, C., Denic, S. Z., Lewis, T. A.,
and Cepeda, R. Privacy for smart meters: Towards
undetectable appliance load signatures. 2010 First
IEEE International Conference on Smart Grid
Communications (2010), 232–237.
Khurana H, Hadley M, Lu N, and Frincke D,” Smart-Grid
Security Issues.”, IEEE Security & Privacy, 2010;
F. Aloul, A. R. Al-Ali, R. Al-Dalky, M. Al-Mardini and
W. El-Hajj, " Smart Grid Security: Threats,
Vulnerabilities and Solutions," International Journal of
Smart Grid and Clean Energy (IJSGCE), 1-6,
September 2012.
J. Liu, Y. Xiao, S. Li, W. Liang, and C. L. P. Chen,
“Cyber Security and Privacy Issues in Smart Grids,’
IEEE Communication Survey and Tutorials, pp. 981-
997, Vol. 14, No. 4, 2012.
Stephen E. McLaughlin, Dmitry Podkuiko, Sergei
Miadzvezhanka, Adam Delozier, Patrick Drew
McDaniel, “Multi-vendor penetration testing in the
advanced metering infrastructure.”ACSAC 2010: 107-
Marek Jawurek, Felix C. Freiling, “Privacy Threat
Analysis of Smart Metering,” informatik 2011.
Salman Yussof, Mohd. Ezanee Rusli, Yunus Yusoff,
Roslan Ismail, Azimah Abdul Ghapar, “Financial
Impacts of Smart Meter Security and Privacy Breach,”
2014 IEEE International Conference on Information
Technology and Multimedia (ICIMU), November 18 –
20, 2014, Putrajaya, Malaysia.
Elias Leake “Privacy and the New Energy Infrastructure”,
Fall 2008, Center for Energy and Environmental
Security, CEES Working Paper No.09-001.
S Finster and I Baumgart, “Privacy-aware smart metering:
A survey", IEEE Communication Surveys and
Tutorials, 2015.
The Smart Grid Interoperability Panel – Cyber Security
Working Group, Guidelines for smart grid cyber
security, NISTIR 7628 (2010) 1–597.
SMARTGREENS 2016 - 5th International Conference on Smart Cities and Green ICT Systems