Hindawi Publishing Corporation
International Journal of Digital Multimedia Broadcasting
Volume 2011, Article ID 382147, 9 pages
doi:10.1155/2011/382147
Research Article
BVS: A Lightweight Forward and Backward Secure Scheme for
PMU Communications in Smart Grid
Wei Ren,
1
Jun Song,
1
Min Lei,
2
and Yi Ren
3
1
School of Computer Science, China University of Geosciences, Wuhan 430074, China
2
School of Software Engineering, Key Laboratory of Network and Information Attack and Defense Technology of MoE,
Beijing 100876, China
3
Department of Information and Communication Technology, University of Agder (UiA), Grimstad, Norway
Correspondence should be addressed to Wei Ren, weirencs@gmail.com
Received 30 November 2010; Accepted 20 April 2011
Academic Editor: Pierangela Samarati
Copyright © 2011 Wei Ren et al. This is an open access article distributed under the Creative Commons Attribution License, which
permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
In smart grid, phaser measurement units (PMUs) can upload readings to utility centers via supervisory control and data acquisition
(SCADA) or energy management system (EMS) to enable intelligent controlling and scheduling. It is critical to maintain the
secrecy of readings so as to protect customers’ privacy, together with integrity and source authentication for the reliability
and stability of power scheduling. In particular, appealing security scheme needs to perform well in PMUs that usually have
computational resource constraints, thus designed security protocols have to remain lightweight in terms of computation and
storage. In this paper, we propose a family of schemes to solve this problem. They are public key based scheme (PKS), password
based scheme (PWS) and billed value-based scheme (BVS). BVS can achieve forward and backward security and only relies on hash
functions. Security analysis justifies that the proposed schemes, especially BVS, can attain the security goals with low computation
and storage cost.
1. Introduction
Smart grid is envisioned as a long-term strategy for national
energy independence, controlling emission, and combating
global war ming [1]. Smart grid technologies utilize intelli-
gent transmission to deliver electricity, together with distri-
bution networks to enable two-way communications. These
approaches aim to improve reliability and efficiency of the
electric system via gathering consumption data, delivering
dynamic optimization of operations, and arranging energy
saving schedules.
The smart grid promises to transform traditional cen-
tralized, producer-controlled network to a decentralized,
consumer-interactive network. For example, consumers
react to pricing signals delivered by control unit from
smart meters to achieve active load adjustment. Supervisory
control And data acquisition (SCADA) or energy manage-
ment system (EMS) may collect one data points every 1 to
2 seconds, whereas phaser measurement units (PMUs) may
collect 30 to 60 data points per second [2].
The security of smart grid is a critical issue for its applica-
bility, development and deployment [3–7]. On one hand, the
security, and especially the availability of power supplying
system, affects homeland security, as it is an indispensable
infrastructure for pubic living system [8–10]. That is, any
transient interruption will result in economic and social dis-
aster. On the other hand, introduction of end devices such as
PMUs requests for data and communication security to sup-
port secure and reliable uploading of measurements [11, 12].
As the PMUs are exposed far from the central control
unit, they present as a security boundary line between
defenses and attacks. Such frontier may be tampered by
curious users who intend to make certain profits or, even
worse, hacked by malicious attackers who target for damag-
ing power scheduling performance [13, 14]. For example, in
the former case, advanced customers may try to reduce the
value of meter’s readings by revising circuits or interfering
signals outside; curious eavesdroppers may be interested
in customers’ power-consuming patterns to pry about the
consumers’ privacy such as daily behaviors or schedules. In